hypothesis psychology a level

Aims, Hypotheses & Sampling

Aims and hypotheses.

Each research study specifies aims and hypotheses. An aim is what it is trying to achieve, while a hypothesis is a specific prediction of what it will find.

• A researcher usually states the aim of their study.
• This involves saying what they are trying to achieve, or what the point of their study is.
• For example, a researcher may state that they aim to find out the effect of caffeine on sleep.

• A hypothesis is different from an aim.
• It involves making a specific prediction of what will be found, expressed in terms of a change in variables.
• For example, a researcher may state a hypothesis that consuming 200mg of caffeine will increase the length of time it takes people to fall asleep compared to having no caffeine.

Experimental vs alternative

• In an experiment, the researcher’s main hypothesis is known as an experimental hypothesis. It is also referred to as H1.
• In a non-experimental study, it is typically called an alternative hypothesis.

Null hypothesis

• Most studies also clearly state a null hypothesis (sometimes referred to as H0).
• This is a statement of what will be found if the experimental/alternative hypothesis is not supported by the results.

Directional hypothesis

• A directional or one-tailed hypothesis predicts the direction in which change is expected to occur.
• It is used when previous research has suggested the direction of change.
• e.g.Alcohol increases reaction times.

Non-directional hypothesis

• A non-directional or two-tailed hypothesis simply predicts change and does not specify direction.

It is used when there is no previous research. It is non-specific and uses words like: effect, change, difference etc.

• e.g. Alcohol will affect reaction times.

NB. All variables must be fully operationalised e.g. alcohol measured in units; reaction times measured in seconds.

Populations and Samples

Any research study needs a group of participants. These are called the sample, and they are drawn from a wider group called the target population.

• Sampling means selecting a group of participants who will take part in the study.

Populations

• A sample always comes from a broader population.
• This does not necessarily mean the whole population of a country, but could be a specific group.
• For example, all sixth-form school pupils in the country is an example of a target population, and a selection of 50 sixth-form school pupils is an example of a sample.

Representation

• A key aspect of sampling is that the sample should be representative of the target population.
• This means that they should have similar characteristics.
• Studying a representative sample allows the researcher to generalise the findings to the target population. This is a key aim of any research.

Sampling Techniques

There are multiple ways of obtaining a sample for a research study. Four major sampling techniques are opportunity sampling, systematic sampling, volunteer sampling and stratified sampling.

Opportunity sampling

• Examples of opportunity sampling include conducting research on the researcher’s own friends, classmates or students.
• Opportunity sampling is very prone to bias because the most easily available participants may not be representative of the target population.

Systematic sampling

• Examples of systematic sampling include picking every 50th person that walks along a corridor, or every 100th name in the phone book, or posting a questionnaire to every 10th house in a village.
• Systematic sampling reduces researcher bias, but some potential participants may be excluded e.g. because they are not in the phone book or do not live in a house. This leads to bias.

Volunteer sampling

• Eg. posting an advert on a school noticeboard, asking people to complete your online survey.
• One source of bias with volunteer sampling is that certain personalities are more likely than others to come forward and help the research. This may have affected classic research studies such as Milgram’s obedience research and Zimbardo’s Stanford Prison experiment.

Stratified sampling

• An example of stratified sampling would involve selecting people from different ethnic groups to create a sample with the same proportions as exist in the target population.
• This reduces bias by making the sample more representative, but before stratification can occur, participants must already have been selected using another sampling technique.

Random sampling

• In random sampling like the National Lottery, all members of the target population must stand an equal chance of being selected.
• E.g. putting the names of every member of the target population into a hat and pulling a sample out (without looking!).

Evaluation of random sampling

• If the sample is large enough, the rules of probability suggest that it should be representative.
• Participants may not be willing or able to take part in the research.
• Sample could still be biased in terms of variables such as gender, age, ethnicity etc.

1 Social Influence

1.1 Social Influence

1.1.1 Conformity

1.1.2 Asch (1951)

1.1.3 Sherif (1935)

1.1.4 Conformity to Social Roles

1.1.5 BBC Prison Study

1.1.6 End of Topic Test - Conformity

1.1.7 Obedience

1.1.8 Analysing Milgram's Experiment

1.1.9 Agentic State & Legitimate Authority

1.1.10 Variables of Obedience

1.1.11 Resistance to Social Influence

1.1.12 Minority Influence & Social Change

1.1.13 Minority Influence & Social Impact Theory

1.1.14 End of Topic Test - Social Influences

1.1.15 Exam-Style Question - Conformity

1.1.16 Top Grade AO2/AO3 - Social Influence

2.1.1 Multi-Store Model of Memory

2.1.2 Short-Term vs Long-Term Memory

2.1.3 Long-Term Memory

2.1.4 Support for the Multi-Store Model of Memory

2.1.5 Duration Studies

2.1.6 Capacity Studies

2.1.7 Coding Studies

2.1.8 The Working Memory Model

2.1.9 The Working Memory Model 2

2.1.10 Support for the Working Memory Model

2.1.11 Explanations for Forgetting

2.1.12 Studies on Interference

2.1.13 Cue-Dependent Forgetting

2.1.14 Eye Witness Testimony - Loftus & Palmer

2.1.15 Eye Witness Testimony Loftus

2.1.16 Eyewitness Testimony - Post-Event Discussion

2.1.17 Eyewitness Testimony - Age & Misleading Questions

2.1.18 Cognitive Interview

2.1.19 Cognitive Interview - Geiselman & Fisher

2.1.20 End of Topic Test - Memory

2.1.21 Exam-Style Question - Memory

2.1.22 A-A* (AO3/4) - Memory

3 Attachment

3.1 Attachment

3.1.1 Caregiver-Infant Interaction

3.1.2 Condon & Sander (1974)

3.1.3 Schaffer & Emerson (1964)

3.1.4 Multiple Attachments

3.1.5 Studies on the Role of the Father

3.1.6 Animal Studies of Attachment

3.1.7 Explanations of Attachment

3.1.8 Attachment Types - Strange Situation

3.1.9 Cultural Differences in Attachment

3.1.10 Disruption of Attachment

3.1.11 Disruption of Attachment - Privation

3.1.12 Overcoming the Effects of Disruption

3.1.13 The Effects of Institutionalisation

3.1.14 Early Attachment

3.1.15 Critical Period of Attachment

3.1.16 End of Topic Test - Attachment

3.1.17 Exam-Style Question - Attachment

3.1.18 Top Grade AO2/AO3 - Attachment

4 Psychopathology

4.1 Psychopathology

4.1.1 Definitions of Abnormality

4.1.2 Definitions of Abnormality 2

4.1.3 Phobias, Depression & OCD

4.1.4 Phobias: Behavioural Approach

4.1.5 Evaluation of Behavioural Explanations of Phobias

4.1.6 Depression: Cognitive Approach

4.1.7 OCD: Biological Approach

4.1.8 Evidence for the Biological Approach

4.1.9 End of Topic Test - Psychopathy

4.1.10 Exam-Style Question - Phobias

4.1.11 Top Grade AO2/AO3 - Psychopathology

5 Approaches in Psychology

5.1 Approaches in Psychology

5.1.1 Psychology as a Science

5.1.2 Origins of Psychology

5.1.3 Reductionism & Problems with Introspection

5.1.4 The Behaviourist Approach - Classical Conditioning

5.1.5 Pavlov's Experiment

5.1.6 Little Albert Study

5.1.7 The Behaviourist Approach - Operant Conditioning

5.1.8 Social Learning Theory

5.1.9 The Cognitive Approach 1

5.1.10 The Cognitive Approach 2

5.1.11 The Biological Approach

5.1.12 Gottesman (1991) - Twin Studies

5.1.13 Brain Scanning

5.1.14 Structure of Personality & Little Hans

5.1.15 The Psychodynamic Approach (A2 only)

5.1.16 Humanistic Psychology (A2 only)

5.1.17 Aronoff (1957) (A2 Only)

5.1.18 Rogers' Client-Centred Therapy (A2 only)

5.1.19 End of Topic Test - Approaches in Psychology

5.1.20 Exam-Style Question - Approaches in Psychology

5.2 Comparison of Approaches (A2 only)

5.2.1 Psychodynamic Approach

5.2.2 Cognitive Approach

5.2.3 Biological Approach

5.2.4 Behavioural Approach

5.2.5 End of Topic Test - Comparison of Approaches

6 Biopsychology

6.1 Biopsychology

6.1.1 Nervous System Divisions

6.1.2 Neuron Structure & Function

6.1.3 Neurotransmitters

6.1.4 Endocrine System Function

6.1.5 Fight or Flight Response

6.1.6 The Brain (A2 only)

6.1.7 Localisation of Brain Function (A2 only)

6.1.8 Studying the Brain (A2 only)

6.1.9 CIMT (A2 Only) & Postmortem Examinations

6.1.10 Biological Rhythms (A2 only)

6.1.11 Studies on Biological Rhythms (A2 Only)

6.1.12 End of Topic Test - Biopsychology

6.1.13 Top Grade AO2/AO3 - Biopsychology

7 Research Methods

7.1 Research Methods

7.1.1 Experimental Method

7.1.2 Observational Techniques

7.1.3 Covert, Overt & Controlled Observation

7.1.4 Self-Report Techniques

7.1.5 Correlations

7.1.6 Exam-Style Question - Research Methods

7.1.7 End of Topic Test - Research Methods

7.2 Scientific Processes

7.2.1 Aims, Hypotheses & Sampling

7.2.2 Pilot Studies & Design

7.2.3 Questionnaires

7.2.4 Variables & Control

7.2.5 Demand Characteristics & Investigator Effects

7.2.6 Ethics

7.2.7 Limitations of Ethical Guidelines

7.2.8 Consent & Protection from Harm Studies

7.2.9 Peer Review & The Economy

7.2.10 Validity (A2 only)

7.2.11 Reliability (A2 only)

7.2.12 Features of Science (A2 only)

7.2.13 Paradigms & Falsifiability (A2 only)

7.2.14 Scientific Report (A2 only)

7.2.15 Scientific Report 2 (A2 only)

7.2.16 End of Topic Test - Scientific Processes

7.3 Data Handling & Analysis

7.3.1 Types of Data

7.3.2 Descriptive Statistics

7.3.3 Correlation

7.3.4 Evaluation of Descriptive Statistics

7.3.5 Presentation & Display of Data

7.3.6 Levels of Measurement (A2 only)

7.3.7 Content Analysis (A2 only)

7.3.8 Case Studies (A2 only)

7.3.9 Thematic Analysis (A2 only)

7.3.10 End of Topic Test - Data Handling & Analysis

7.4 Inferential Testing

7.4.1 Introduction to Inferential Testing

7.4.2 Sign Test

7.4.3 Piaget Conservation Experiment

7.4.4 Non-Parametric Tests

8 Issues & Debates in Psychology (A2 only)

8.1 Issues & Debates in Psychology (A2 only)

8.1.1 Culture Bias

8.1.2 Sub-Culture Bias

8.1.3 Gender Bias

8.1.4 Ethnocentrism

8.1.5 Cross Cultural Research

8.1.6 Free Will & Determinism

8.1.7 Comparison of Free Will & Determinism

8.1.8 Reductionism & Holism

8.1.9 Reductionist & Holistic Approaches

8.1.10 Nature-Nurture Debate

8.1.11 Interactionist Approach

8.1.12 Nature-Nurture Methods

8.1.13 Nature-Nurture Approaches

8.1.14 Idiographic & Nomothetic Approaches

8.1.15 Socially Sensitive Research

8.1.16 End of Topic Test - Issues and Debates

9 Option 1: Relationships (A2 only)

9.1 Relationships: Sexual Relationships (A2 only)

9.1.1 Sexual Selection & Human Reproductive Behaviour

9.1.2 Intersexual & Intrasexual Selection

9.1.3 Evaluation of Sexual Selection Behaviour

9.1.4 Factors Affecting Attraction: Self-Disclosure

9.1.5 Evaluation of Self-Disclosure Theory

9.1.6 Self Disclosure in Computer Communication

9.1.7 Factors Affecting Attraction: Physical Attributes

9.1.8 Matching Hypothesis Studies

9.1.9 Factors Affecting Physical Attraction

9.1.10 Factors Affecting Attraction: Filter Theory 1

9.1.11 Factors Affecting Attraction: Filter Theory 2

9.1.12 Evaluation of Filter Theory

9.1.13 End of Topic Test - Sexual Relationships

9.2 Relationships: Romantic Relationships (A2 only)

9.2.1 Social Exchange Theory

9.2.2 Evaluation of Social Exchange Theory

9.2.3 Equity Theory

9.2.4 Evaluation of Equity Theory

9.2.5 Rusbult’s Investment Model

9.2.6 Evaluation of Rusbult's Investment Model

9.2.7 Relationship Breakdown

9.2.8 Studies on Relationship Breakdown

9.2.9 Evaluation of Relationship Breakdown

9.2.10 End of Topic Test - Romantic relationships

9.3 Relationships: Virtual & Parasocial (A2 only)

9.3.1 Virtual Relationships in Social Media

9.3.2 Evaluation of Reduced Cues & Hyperpersonal

9.3.3 Parasocial Relationships

9.3.4 Attachment Theory & Parasocial Relationships

9.3.5 Evaluation of Parasocial Relationship Theories

9.3.6 End of Topic Test - Virtual & Parasocial Realtions

10 Option 1: Gender (A2 only)

10.1 Gender (A2 only)

10.1.1 Sex, Gender & Androgyny

10.1.2 Gender Identity Disorder

10.1.3 Biological & Social Explanations of GID

10.1.4 Biological Influences on Gender

10.1.5 Effects of Hormones on Gender

10.1.6 End of Topic Test - Gender 1

10.1.7 Kohlberg’s Theory of Gender Constancy

10.1.8 Evaluation of Kohlberg's Theory

10.1.9 Gender Schema Theory

10.1.10 Psychodynamic Approach to Gender Development 1

10.1.11 Psychodynamic Approach to Gender Development 2

10.1.12 Social Approach to Gender Development

10.1.13 Criticisms of Social Theory

10.1.14 End of Topic Test - Gender 2

10.1.15 Media Influence on Gender Development

10.1.16 Cross Cultural Research

10.1.17 Childcare & Gender Roles

10.1.18 End of Topic Test - Gender 3

11 Option 1: Cognition & Development (A2 only)

11.1 Cognition & Development (A2 only)

11.1.1 Piaget’s Theory of Cognitive Development 1

11.1.2 Piaget's Theory of Cognitive Development 2

11.1.3 Schema Accommodation Assimilation & Equilibration

11.1.4 Piaget & Inhelder’s Three Mountains Task (1956)

11.1.5 Conservation & Class Inclusion

11.1.6 Evaluation of Piaget

11.1.7 End of Topic Test - Cognition & Development 1

11.1.8 Vygotsky

11.1.9 Evaluation of Vygotsky

11.1.10 Baillargeon

11.1.11 Baillargeon's studies

11.1.12 Evaluation of Baillargeon

11.1.13 End of Topic Test - Cognition & Development 2

11.1.14 Sense of Self & Theory of Mind

11.1.15 Baron-Cohen Studies

11.1.16 Selman’s Five Levels of Perspective Taking

11.1.17 Biological Basis of Social Cognition

11.1.18 Evaluation of Biological Basis of Social Cognition

11.1.19 Important Issues in Social Neuroscience

11.1.20 End of Topic Test - Cognition & Development 3

11.1.21 Top Grade AO2/AO3 - Cognition & Development

12 Option 2: Schizophrenia (A2 only)

12.1 Schizophrenia: Diagnosis (A2 only)

12.1.1 Classification & Diagnosis

12.1.2 Reliability & Validity of Diagnosis

12.1.3 Gender & Cultural Bias

12.1.4 Pinto (2017) & Copeland (1971)

12.1.5 End of Topic Test - Scizophrenia Diagnosis

12.2 Schizophrenia: Treatment (A2 only)

12.2.1 Family-Based Psychological Explanations

12.2.2 Evaluation of Family-Based Explanations

12.2.3 Cognitive Explanations

12.2.4 Drug Therapies

12.2.5 Evaluation of Drug Therapies

12.2.6 Biological Explanations for Schizophrenia

12.2.7 Dopamine Hypothesis

12.2.8 End of Topic Test - Schizoprenia Treatment 1

12.2.9 Psychological Therapies 1

12.2.10 Psychological Therapies 2

12.2.11 Evaluation of Psychological Therapies

12.2.12 Interactionist Approach - Diathesis-Stress Model

12.2.13 Interactionist Approach - Triggers & Treatment

12.2.14 Evaluation of the Interactionist Approach

12.2.15 End of Topic Test - Scizophrenia Treatments 2

13 Option 2: Eating Behaviour (A2 only)

13.1 Eating Behaviour (A2 only)

13.1.1 Explanations for Food Preferences

13.1.2 Birch et al (1987) & Lowe et al (2004)

13.1.3 Control of Eating Behaviours

13.1.4 Control of Eating Behaviour: Leptin

13.1.5 Biological Explanations for Anorexia Nervosa

13.1.6 Psychological Explanations: Family Systems Theory

13.1.7 Psychological Explanations: Social Learning Theory

13.1.8 Psychological Explanations: Cognitive Theory

13.1.9 Biological Explanations for Obesity

13.1.10 Biological Explanations: Studies

13.1.11 Psychological Explanations for Obesity

13.1.12 Psychological Explanations: Studies

13.1.13 End of Topic Test - Eating Behaviour

14 Option 2: Stress (A2 only)

14.1 Stress (A2 only)

14.1.1 Physiology of Stress

14.1.2 Role of Stress in Illness

14.1.3 Role of Stress in Illness: Studies

14.1.4 Social Readjustment Rating Scales

14.1.5 Hassles & Uplifts Scales

14.1.6 Stress, Workload & Control

14.1.7 Stress Level Studies

14.1.8 End of Topic Test - Stress 1

14.1.9 Physiological Measures of Stress

14.1.10 Individual Differences

14.1.11 Stress & Gender

14.1.12 Drug Therapy & Biofeedback for Stress

14.1.13 Stress Inoculation Therapy

14.1.14 Social Support & Stress

14.1.15 End of Topic Test - Stress 2

15 Option 3: Aggression (A2 only)

15.1 Aggression: Physiological (A2 only)

15.1.1 Neural Mechanisms

15.1.2 Serotonin

15.1.3 Hormonal Mechanisms

15.1.4 Genetic Factors

15.1.5 Genetic Factors 2

15.1.6 End of Topic Test - Aggression: Physiological 1

15.1.7 Ethological Explanation

15.1.8 Innate Releasing Mechanisms & Fixed Action Pattern

15.1.9 Evolutionary Explanations

15.1.10 Buss et al (1992) - Sex Differences in Jealousy

15.1.11 Evaluation of Evolutionary Explanations

15.1.12 End of Topic Test - Aggression: Physiological 2

15.2 Aggression: Social Psychological (A2 only)

15.2.1 Social Psychological Explanation

15.2.2 Buss (1963) - Frustration/Aggression

15.2.3 Social Psychological Explanation 2

15.2.4 Social Learning Theory (SLT) 1

15.2.5 Social Learning Theory (SLT) 2

15.2.6 Limitations of Social Learning Theory (SLT)

15.2.7 Deindividuation

15.2.8 Deindividuation 2

15.2.9 Deindividuation - Diener et al (1976)

15.2.10 End of Topic Test - Aggression: Social Psychology

15.2.11 Institutional Aggression: Prisons

15.2.12 Evaluation of Dispositional & Situational

15.2.13 Influence of Computer Games

15.2.14 Influence of Television

15.2.15 Evaluation of Studies on Media

15.2.16 Desensitisation & Disinhibition

15.2.17 Cognitive Priming

15.2.18 End of Topic Test - Aggression: Social Psychology

16 Option 3: Forensic Psychology (A2 only)

16.1 Forensic Psychology (A2 only)

16.1.1 Defining Crime

16.1.2 Measuring Crime

16.1.3 Offender Profiling

16.1.4 Evaluation of Offender Profiling

16.1.5 John Duffy Case Study

16.1.6 Biological Explanations 1

16.1.7 Biological Explanations 2

16.1.8 Evaluation of the Biological Explanation

16.1.9 Cognitive Explanations

16.1.10 Moral Reasoning

16.1.11 Psychodynamic Explanation 1

16.1.12 Psychodynamic Explanation 2

16.1.13 End of Topic Test - Forensic Psychology 1

16.1.14 Differential Association Theory

16.1.15 Custodial Sentencing

16.1.16 Effects of Prison

16.1.17 Evaluation of the Effects of Prison

16.1.18 Recidivism

16.1.19 Behavioural Treatments & Therapies

16.1.20 Effectiveness of Behavioural Treatments

16.1.21 Restorative Justice

16.1.22 End of Topic Test - Forensic Psychology 2

17 Option 3: Addiction (A2 only)

17.1 Addiction (A2 only)

17.1.1 Definition

17.1.2 Brain Neurochemistry Explanation

17.1.3 Learning Theory Explanation

17.1.4 Evaluation of a Learning Theory Explanation

17.1.5 Cognitive Bias

17.1.6 Griffiths on Cognitive Bias

17.1.7 Evaluation of Cognitive Theory (A2 only)

17.1.8 End of Topic Test - Addiction 1

17.1.9 Gambling Addiction & Learning Theory

17.1.10 Social Influences on Addiction 1

17.1.11 Social Influences on Addiction 2

17.1.12 Personal Influences on Addiction

17.1.13 Genetic Explanations of Addiction

17.1.14 End of Topic Test - Addiction 2

17.2 Treating Addiction (A2 only)

17.2.1 Drug Therapy

17.2.2 Behavioural Interventions

17.2.3 Cognitive Behavioural Therapy

17.2.4 Theory of Reasoned Action

17.2.5 Theory of Planned Behaviour

17.2.6 Six Stage Model of Behaviour Change

17.2.7 End of Topic Test - Treating Addiction

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End of Topic Test - Research Methods

Pilot Studies & Design

AQA A-Level Psychology Notes

8.1.1 aims and hypotheses in research design, understanding aims in research, definition and importance.

Aims articulate the primary goals of a research study.

They provide a broad, overarching perspective, laying the groundwork for the investigation.

Clarity in aims is crucial as it ensures the research remains focused and pertinent to the subject matter.

Formulating Effective Aims

Effective aims should be clear , specific , and achievable within the scope of the study.

They should address a particular psychological issue or question, contributing to the field's existing body of knowledge.

The formulation of aims involves understanding the context of the research within the wider psychological landscape, ensuring relevance and significance.

Hypotheses in Research Design

Definition of hypotheses.

A hypothesis is a precise, testable prediction about the relationship between variables.

It acts as a bridge between the aim and the methodological execution of the research.

Role of Hypotheses

The hypothesis steers the choice of research methods, influencing how the study is conducted.

It provides a framework for structuring the research, guiding data collection and analysis.

Critical for determining the statistical methods used in the study and for interpreting the results accurately.

Directional Hypotheses

Understanding directional hypotheses.

These hypotheses predict the specific direction of the relationship between variables.

Example: "Students who sleep for 8 hours will have better memory recall than those who sleep for 4 hours."

Characteristics

They are specific, focused, and indicate an expected increase or decrease in a variable.

Implies a one-way effect where one variable directly affects another.

Significance in Research Design

Directional hypotheses are particularly useful when previous research or theories indicate a specific outcome.

They help in focusing the research design, allowing for more targeted data collection and analysis methods.

Enable the drawing of more specific, pointed conclusions from the study.

Non-Directional Hypotheses

Understanding non-directional hypotheses.

These predict that a relationship exists between variables but do not specify the direction.

Example: "There is a difference in memory recall between students who sleep for 8 hours and those who sleep for 4 hours."

Broader and less specific compared to directional hypotheses.

Open-ended, acknowledging any type of relationship between the variables.

Employed when the direction of the relationship between variables is not known or is unclear.

Ensures an unbiased approach in both data collection and analysis.

Ideal for exploratory research where the researcher is open to all possible outcomes.

Comparing Directional and Non-Directional Hypotheses

Situational usage.

Directional: Applied when existing literature or theoretical frameworks strongly suggest a particular outcome.

Non-Directional: Used in situations where previous research is sparse or inconclusive, or when exploring new areas.

Impact on Research Design

Directional: Leads to more focused research designs, guiding specific methods of data collection and statistical analysis.

Non-Directional: Requires a broader and more flexible approach to accommodate unexpected findings.

Implications for Statistical Analysis

Directional: Enables the use of one-tailed statistical tests, which are more sensitive to detecting effects in the predicted direction.

Non-Directional: Requires the use of two-tailed tests, prepared to detect effects in either direction.

Risks and Considerations

Directional: There's a risk of confirmation bias if the researcher is too committed to a specific outcome.

Non-Directional: Might lead to less definitive conclusions but is more open to novel findings.

Importance in Research Outcomes

Validity and reliability.

Properly formulated aims and hypotheses are key to enhancing the study's validity and reliability.

They help ensure that the research accurately and effectively addresses the intended psychological constructs.

Ethical Considerations

Precise aims and hypotheses contribute to maintaining ethical standards in research by preventing misleading or harmful investigations.

Contribution to Psychological Knowledge

Thoughtfully crafted aims and hypotheses significantly add to psychological knowledge.

They help in reinforcing or challenging existing theories, or in paving the way for new theoretical developments.

Enhancing Research Credibility

Clear and well-constructed aims and hypotheses enhance the credibility and acceptability of research within the scientific community.

They assist in justifying the research approach and the interpretation of results.

In conclusion, the formulation of aims and the distinction between directional and non-directional hypotheses are central to the design and effectiveness of psychological research. These components not only guide the study's focus and methodology but also significantly influence the interpretation and implications of the research findings. For AQA A-Level Psychology students, a deep understanding of these concepts is essential, as they form the core of research methodology in psychology. Recognizing the importance of these elements ensures a solid foundation for engaging in and comprehending psychological research.

How can the formulation of hypotheses impact the ethical considerations of a psychological study?

The formulation of hypotheses can significantly impact the ethical considerations of a psychological study. A well-constructed hypothesis ensures that the research question is addressed in a manner that is both respectful and responsible towards participants. For instance, if a hypothesis is too intrusive or personal, it may breach the participants' privacy or cause them discomfort, raising ethical concerns. Additionally, a hypothesis that might lead to misleading or harmful interpretations can be unethical, particularly if it risks stigmatizing a group or propagating stereotypes. Ethical research requires that hypotheses are formulated with sensitivity to potential implications, respecting participant welfare and societal norms. Researchers must ensure their hypotheses do not contribute to harm, misinformation, or the perpetuation of prejudice. This ethical mindfulness in hypothesis formulation is integral to maintaining the integrity and social responsibility of psychological research.

What are the potential consequences of poorly formulated aims and hypotheses in a research study?

Poorly formulated aims and hypotheses can have several detrimental consequences for a research study. Firstly, vague or ambiguous aims can lead to a lack of focus in the research, making it difficult to determine the scope and direction of the study. This lack of clarity can result in ineffective or inefficient research methods, as the objectives are not clear enough to guide the methodology. Similarly, an ill-defined hypothesis can complicate the data collection process, as it may not provide a specific enough prediction to test. This can lead to irrelevant or inconclusive data being collected, which can undermine the study's validity. Furthermore, poorly articulated hypotheses can make it challenging to perform appropriate statistical analyses, as the type of test used often depends on the nature of the hypothesis. Ultimately, these issues can lead to unreliable or invalid research findings, reducing the study's contribution to psychological knowledge and potentially leading to incorrect conclusions being drawn.

How does the choice between a directional and non-directional hypothesis affect the type of statistical analysis used in a study?

The choice between a directional and non-directional hypothesis significantly influences the type of statistical analysis used in a study. With a directional hypothesis, which predicts the specific direction of the relationship between variables, one-tailed statistical tests are often used. These tests are designed to determine whether there is evidence to support the hypothesis in the specified direction. For example, if a hypothesis predicts that one group will score higher than another, a one-tailed test will specifically look for evidence of this outcome. In contrast, non-directional hypotheses, which predict a relationship without specifying its direction, necessitate the use of two-tailed tests. These tests are equipped to detect significant differences or relationships in both directions. This means they are capable of identifying whether one variable is either greater than, less than, or simply different from another, without a pre-specified direction. The choice of hypothesis, therefore, directly guides the researcher in selecting the most appropriate statistical test, ensuring that the analysis is accurately aligned with the study’s predictions.

In what ways can a hypothesis contribute to the development of psychological theory?

A hypothesis can significantly contribute to the development of psychological theory in several ways. Firstly, a well-formulated hypothesis, based on existing literature and theory, can test the validity of current theoretical models. By empirically investigating these models, a hypothesis can either provide evidence to support them or challenge their assumptions, leading to their refinement or reevaluation. Furthermore, a hypothesis can also identify new areas of inquiry within a theory, suggesting novel aspects that have not been previously considered or explored. This can lead to the expansion of the theory, adding complexity and depth to our understanding of psychological phenomena. Additionally, a hypothesis can bridge gaps between different theoretical perspectives, proposing ways in which disparate ideas may be integrated or reconciled. This synthesis can foster more comprehensive and robust theories, enhancing their explanatory power. Ultimately, hypotheses play a crucial role in the dynamic process of theory development, constantly pushing the boundaries of our understanding and encouraging the evolution of psychological thought.

What role does the formulation of aims and hypotheses play in the replication of psychological studies?

The formulation of aims and hypotheses plays a critical role in the replication of psychological studies. Clear and precise aims and hypotheses allow other researchers to understand exactly what the original study intended to investigate and predict. This clarity is essential for replication, as it ensures that subsequent studies are testing the same concepts and relationships. Accurate replication requires that the aims and hypotheses are replicated as closely as possible, to ensure that any differences in findings are due to actual variations in results, not discrepancies in what was being tested. Moreover, well-defined aims and hypotheses facilitate the replication of the study’s methodology, as they guide the choice of variables, participants, and statistical analyses. Replication is a key component of the scientific method, providing a means to verify and reinforce the reliability and validity of research findings. Therefore, the precise formulation of aims and hypotheses is fundamental to the process of replication, ensuring the integrity and continuity of psychological research.

Practice Questions

Explain the difference between directional and non-directional hypotheses, providing an example for each.

A directional hypothesis predicts the specific direction of the relationship between variables. For example, "Increased sleep leads to better academic performance", implying that more sleep results in improved grades. This hypothesis is specific in predicting the nature of the effect. On the other hand, a non-directional hypothesis suggests a relationship exists but does not specify its direction. An example would be, "There is a relationship between sleep duration and academic performance." This is broader, acknowledging a link but not indicating whether more sleep improves or worsens performance. The key difference lies in the specificity of the predicted relationship.

Why is it important to have a clear aim and hypothesis in psychological research?

Having a clear aim and hypothesis in psychological research is crucial as they guide the entire research process. A well-defined aim outlines the study's goals and ensures that the research remains focused on relevant psychological issues. The hypothesis, derived from the aim, provides a testable prediction about the relationship between variables. This precision in the hypothesis is essential for selecting appropriate research methods, collecting data effectively, and applying suitable statistical analysis techniques. Moreover, clear aims and hypotheses enhance the validity and reliability of the research, ensuring that it accurately tests the intended psychological constructs and contributes meaningfully to the field.

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Understanding Hypotheses

• Hypotheses are statements made by researchers , predicting an expected outcome or relationship between variables.
• A null hypothesis (H0) predicts no relationship or difference between variables.

Types of Hypotheses

Alternative Hypothesis (H1)

• An alternative hypothesis predicts a relationship or difference between variables.
• It could be directional or non-directional.

Directional Hypotheses

• The prediction is very specific.
• It states the direction of the effect (i.e., ‘greater than’, ‘less than’).

Non-Directional Hypotheses

• It simply states that there is a difference or a relationship but does not predict the direction of this effect.

Formulation of Hypotheses in Research

• Hypotheses are formulated after thorough review of related literature and understanding of the research question.
• The alternative hypothesis is what the researcher really thinks is the case and is trying to prove.
• The null hypothesis is the “default” view - that there is no effect or difference.

Testability of Hypotheses

• A hypothesis must be testable and measurable. It should clearly define the variables and the expected relationship or difference between them.
• Operationalising variables is a key step to make them measurable.

Role of Hypotheses in Psychological Research

• Hypotheses guide the direction of the study, help design experiments, and determine analytical methods.
• They are critical for replicability of the study. Other researchers must be able to test the same hypotheses under the same conditions.
• Hypotheses are provisional. They can be supported or refuted based on the results, leading to further hypotheses and research.

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How to Write a Great Hypothesis

Hypothesis Definition, Format, Examples, and Tips

Verywell / Alex Dos Diaz

• The Scientific Method

Hypothesis Format

Falsifiability of a hypothesis.

• Operationalization

Hypothesis Types

Hypotheses examples.

• Collecting Data

A hypothesis is a tentative statement about the relationship between two or more variables. It is a specific, testable prediction about what you expect to happen in a study. It is a preliminary answer to your question that helps guide the research process.

Consider a study designed to examine the relationship between sleep deprivation and test performance. The hypothesis might be: "This study is designed to assess the hypothesis that sleep-deprived people will perform worse on a test than individuals who are not sleep-deprived."

At a Glance

A hypothesis is crucial to scientific research because it offers a clear direction for what the researchers are looking to find. This allows them to design experiments to test their predictions and add to our scientific knowledge about the world. This article explores how a hypothesis is used in psychology research, how to write a good hypothesis, and the different types of hypotheses you might use.

The Hypothesis in the Scientific Method

In the scientific method , whether it involves research in psychology, biology, or some other area, a hypothesis represents what the researchers think will happen in an experiment. The scientific method involves the following steps:

• Forming a question
• Performing background research
• Creating a hypothesis
• Designing an experiment
• Collecting data
• Analyzing the results
• Drawing conclusions
• Communicating the results

The hypothesis is a prediction, but it involves more than a guess. Most of the time, the hypothesis begins with a question which is then explored through background research. At this point, researchers then begin to develop a testable hypothesis.

Unless you are creating an exploratory study, your hypothesis should always explain what you  expect  to happen.

In a study exploring the effects of a particular drug, the hypothesis might be that researchers expect the drug to have some type of effect on the symptoms of a specific illness. In psychology, the hypothesis might focus on how a certain aspect of the environment might influence a particular behavior.

Remember, a hypothesis does not have to be correct. While the hypothesis predicts what the researchers expect to see, the goal of the research is to determine whether this guess is right or wrong. When conducting an experiment, researchers might explore numerous factors to determine which ones might contribute to the ultimate outcome.

In many cases, researchers may find that the results of an experiment  do not  support the original hypothesis. When writing up these results, the researchers might suggest other options that should be explored in future studies.

In many cases, researchers might draw a hypothesis from a specific theory or build on previous research. For example, prior research has shown that stress can impact the immune system. So a researcher might hypothesize: "People with high-stress levels will be more likely to contract a common cold after being exposed to the virus than people who have low-stress levels."

In other instances, researchers might look at commonly held beliefs or folk wisdom. "Birds of a feather flock together" is one example of folk adage that a psychologist might try to investigate. The researcher might pose a specific hypothesis that "People tend to select romantic partners who are similar to them in interests and educational level."

Elements of a Good Hypothesis

So how do you write a good hypothesis? When trying to come up with a hypothesis for your research or experiments, ask yourself the following questions:

• Is your hypothesis based on your research on a topic?
• Can your hypothesis be tested?
• Does your hypothesis include independent and dependent variables?

Before you come up with a specific hypothesis, spend some time doing background research. Once you have completed a literature review, start thinking about potential questions you still have. Pay attention to the discussion section in the  journal articles you read . Many authors will suggest questions that still need to be explored.

How to Formulate a Good Hypothesis

To form a hypothesis, you should take these steps:

• Collect as many observations about a topic or problem as you can.
• Evaluate these observations and look for possible causes of the problem.
• Create a list of possible explanations that you might want to explore.
• After you have developed some possible hypotheses, think of ways that you could confirm or disprove each hypothesis through experimentation. This is known as falsifiability.

In the scientific method ,  falsifiability is an important part of any valid hypothesis. In order to test a claim scientifically, it must be possible that the claim could be proven false.

Students sometimes confuse the idea of falsifiability with the idea that it means that something is false, which is not the case. What falsifiability means is that  if  something was false, then it is possible to demonstrate that it is false.

One of the hallmarks of pseudoscience is that it makes claims that cannot be refuted or proven false.

The Importance of Operational Definitions

A variable is a factor or element that can be changed and manipulated in ways that are observable and measurable. However, the researcher must also define how the variable will be manipulated and measured in the study.

Operational definitions are specific definitions for all relevant factors in a study. This process helps make vague or ambiguous concepts detailed and measurable.

For example, a researcher might operationally define the variable " test anxiety " as the results of a self-report measure of anxiety experienced during an exam. A "study habits" variable might be defined by the amount of studying that actually occurs as measured by time.

These precise descriptions are important because many things can be measured in various ways. Clearly defining these variables and how they are measured helps ensure that other researchers can replicate your results.

Replicability

One of the basic principles of any type of scientific research is that the results must be replicable.

Replication means repeating an experiment in the same way to produce the same results. By clearly detailing the specifics of how the variables were measured and manipulated, other researchers can better understand the results and repeat the study if needed.

Some variables are more difficult than others to define. For example, how would you operationally define a variable such as aggression ? For obvious ethical reasons, researchers cannot create a situation in which a person behaves aggressively toward others.

To measure this variable, the researcher must devise a measurement that assesses aggressive behavior without harming others. The researcher might utilize a simulated task to measure aggressiveness in this situation.

Hypothesis Checklist

• Does your hypothesis focus on something that you can actually test?
• Does your hypothesis include both an independent and dependent variable?
• Can you manipulate the variables?
• Can your hypothesis be tested without violating ethical standards?

The hypothesis you use will depend on what you are investigating and hoping to find. Some of the main types of hypotheses that you might use include:

• Simple hypothesis : This type of hypothesis suggests there is a relationship between one independent variable and one dependent variable.
• Complex hypothesis : This type suggests a relationship between three or more variables, such as two independent and dependent variables.
• Null hypothesis : This hypothesis suggests no relationship exists between two or more variables.
• Alternative hypothesis : This hypothesis states the opposite of the null hypothesis.
• Statistical hypothesis : This hypothesis uses statistical analysis to evaluate a representative population sample and then generalizes the findings to the larger group.
• Logical hypothesis : This hypothesis assumes a relationship between variables without collecting data or evidence.

A hypothesis often follows a basic format of "If {this happens} then {this will happen}." One way to structure your hypothesis is to describe what will happen to the  dependent variable  if you change the  independent variable .

The basic format might be: "If {these changes are made to a certain independent variable}, then we will observe {a change in a specific dependent variable}."

A few examples of simple hypotheses:

• "Students who eat breakfast will perform better on a math exam than students who do not eat breakfast."
• "Students who experience test anxiety before an English exam will get lower scores than students who do not experience test anxiety."​
• "Motorists who talk on the phone while driving will be more likely to make errors on a driving course than those who do not talk on the phone."
• "Children who receive a new reading intervention will have higher reading scores than students who do not receive the intervention."

Examples of a complex hypothesis include:

• "People with high-sugar diets and sedentary activity levels are more likely to develop depression."
• "Younger people who are regularly exposed to green, outdoor areas have better subjective well-being than older adults who have limited exposure to green spaces."

Examples of a null hypothesis include:

• "There is no difference in anxiety levels between people who take St. John's wort supplements and those who do not."
• "There is no difference in scores on a memory recall task between children and adults."
• "There is no difference in aggression levels between children who play first-person shooter games and those who do not."

Examples of an alternative hypothesis:

• "People who take St. John's wort supplements will have less anxiety than those who do not."
• "Adults will perform better on a memory task than children."
• "Children who play first-person shooter games will show higher levels of aggression than children who do not." 

Collecting Data on Your Hypothesis

Once a researcher has formed a testable hypothesis, the next step is to select a research design and start collecting data. The research method depends largely on exactly what they are studying. There are two basic types of research methods: descriptive research and experimental research.

Descriptive Research Methods

Descriptive research such as  case studies ,  naturalistic observations , and surveys are often used when  conducting an experiment is difficult or impossible. These methods are best used to describe different aspects of a behavior or psychological phenomenon.

Once a researcher has collected data using descriptive methods, a  correlational study  can examine how the variables are related. This research method might be used to investigate a hypothesis that is difficult to test experimentally.

Experimental Research Methods

Experimental methods  are used to demonstrate causal relationships between variables. In an experiment, the researcher systematically manipulates a variable of interest (known as the independent variable) and measures the effect on another variable (known as the dependent variable).

Unlike correlational studies, which can only be used to determine if there is a relationship between two variables, experimental methods can be used to determine the actual nature of the relationship—whether changes in one variable actually  cause  another to change.

The hypothesis is a critical part of any scientific exploration. It represents what researchers expect to find in a study or experiment. In situations where the hypothesis is unsupported by the research, the research still has value. Such research helps us better understand how different aspects of the natural world relate to one another. It also helps us develop new hypotheses that can then be tested in the future.

Thompson WH, Skau S. On the scope of scientific hypotheses .  R Soc Open Sci . 2023;10(8):230607. doi:10.1098/rsos.230607

Taran S, Adhikari NKJ, Fan E. Falsifiability in medicine: what clinicians can learn from Karl Popper [published correction appears in Intensive Care Med. 2021 Jun 17;:].  Intensive Care Med . 2021;47(9):1054-1056. doi:10.1007/s00134-021-06432-z

Eyler AA. Research Methods for Public Health . 1st ed. Springer Publishing Company; 2020. doi:10.1891/9780826182067.0004

Nosek BA, Errington TM. What is replication ?  PLoS Biol . 2020;18(3):e3000691. doi:10.1371/journal.pbio.3000691

Aggarwal R, Ranganathan P. Study designs: Part 2 - Descriptive studies .  Perspect Clin Res . 2019;10(1):34-36. doi:10.4103/picr.PICR_154_18

Nevid J. Psychology: Concepts and Applications. Wadworth, 2013.

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Hypothesis Testing

Hypothesis testing is an important feature of science, as this is how theories are developed and modified. A good theory should generate testable predictions (hypotheses), and if research fails to support the hypotheses, then this suggests that the theory needs to be modified in some way.

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Developing a Hypothesis

Rajiv S. Jhangiani; I-Chant A. Chiang; Carrie Cuttler; and Dana C. Leighton

Learning Objectives

• Distinguish between a theory and a hypothesis.
• Discover how theories are used to generate hypotheses and how the results of studies can be used to further inform theories.
• Understand the characteristics of a good hypothesis.

Theories and Hypotheses

Before describing how to develop a hypothesis, it is important to distinguish between a theory and a hypothesis. A  theory  is a coherent explanation or interpretation of one or more phenomena. Although theories can take a variety of forms, one thing they have in common is that they go beyond the phenomena they explain by including variables, structures, processes, functions, or organizing principles that have not been observed directly. Consider, for example, Zajonc’s theory of social facilitation and social inhibition (1965) [1] . He proposed that being watched by others while performing a task creates a general state of physiological arousal, which increases the likelihood of the dominant (most likely) response. So for highly practiced tasks, being watched increases the tendency to make correct responses, but for relatively unpracticed tasks, being watched increases the tendency to make incorrect responses. Notice that this theory—which has come to be called drive theory—provides an explanation of both social facilitation and social inhibition that goes beyond the phenomena themselves by including concepts such as “arousal” and “dominant response,” along with processes such as the effect of arousal on the dominant response.

Outside of science, referring to an idea as a theory often implies that it is untested—perhaps no more than a wild guess. In science, however, the term theory has no such implication. A theory is simply an explanation or interpretation of a set of phenomena. It can be untested, but it can also be extensively tested, well supported, and accepted as an accurate description of the world by the scientific community. The theory of evolution by natural selection, for example, is a theory because it is an explanation of the diversity of life on earth—not because it is untested or unsupported by scientific research. On the contrary, the evidence for this theory is overwhelmingly positive and nearly all scientists accept its basic assumptions as accurate. Similarly, the “germ theory” of disease is a theory because it is an explanation of the origin of various diseases, not because there is any doubt that many diseases are caused by microorganisms that infect the body.

A  hypothesis , on the other hand, is a specific prediction about a new phenomenon that should be observed if a particular theory is accurate. It is an explanation that relies on just a few key concepts. Hypotheses are often specific predictions about what will happen in a particular study. They are developed by considering existing evidence and using reasoning to infer what will happen in the specific context of interest. Hypotheses are often but not always derived from theories. So a hypothesis is often a prediction based on a theory but some hypotheses are a-theoretical and only after a set of observations have been made, is a theory developed. This is because theories are broad in nature and they explain larger bodies of data. So if our research question is really original then we may need to collect some data and make some observations before we can develop a broader theory.

Theories and hypotheses always have this  if-then  relationship. “ If   drive theory is correct,  then  cockroaches should run through a straight runway faster, and a branching runway more slowly, when other cockroaches are present.” Although hypotheses are usually expressed as statements, they can always be rephrased as questions. “Do cockroaches run through a straight runway faster when other cockroaches are present?” Thus deriving hypotheses from theories is an excellent way of generating interesting research questions.

But how do researchers derive hypotheses from theories? One way is to generate a research question using the techniques discussed in this chapter  and then ask whether any theory implies an answer to that question. For example, you might wonder whether expressive writing about positive experiences improves health as much as expressive writing about traumatic experiences. Although this  question  is an interesting one  on its own, you might then ask whether the habituation theory—the idea that expressive writing causes people to habituate to negative thoughts and feelings—implies an answer. In this case, it seems clear that if the habituation theory is correct, then expressive writing about positive experiences should not be effective because it would not cause people to habituate to negative thoughts and feelings. A second way to derive hypotheses from theories is to focus on some component of the theory that has not yet been directly observed. For example, a researcher could focus on the process of habituation—perhaps hypothesizing that people should show fewer signs of emotional distress with each new writing session.

Among the very best hypotheses are those that distinguish between competing theories. For example, Norbert Schwarz and his colleagues considered two theories of how people make judgments about themselves, such as how assertive they are (Schwarz et al., 1991) [2] . Both theories held that such judgments are based on relevant examples that people bring to mind. However, one theory was that people base their judgments on the  number  of examples they bring to mind and the other was that people base their judgments on how  easily  they bring those examples to mind. To test these theories, the researchers asked people to recall either six times when they were assertive (which is easy for most people) or 12 times (which is difficult for most people). Then they asked them to judge their own assertiveness. Note that the number-of-examples theory implies that people who recalled 12 examples should judge themselves to be more assertive because they recalled more examples, but the ease-of-examples theory implies that participants who recalled six examples should judge themselves as more assertive because recalling the examples was easier. Thus the two theories made opposite predictions so that only one of the predictions could be confirmed. The surprising result was that participants who recalled fewer examples judged themselves to be more assertive—providing particularly convincing evidence in favor of the ease-of-retrieval theory over the number-of-examples theory.

Theory Testing

The primary way that scientific researchers use theories is sometimes called the hypothetico-deductive method  (although this term is much more likely to be used by philosophers of science than by scientists themselves). Researchers begin with a set of phenomena and either construct a theory to explain or interpret them or choose an existing theory to work with. They then make a prediction about some new phenomenon that should be observed if the theory is correct. Again, this prediction is called a hypothesis. The researchers then conduct an empirical study to test the hypothesis. Finally, they reevaluate the theory in light of the new results and revise it if necessary. This process is usually conceptualized as a cycle because the researchers can then derive a new hypothesis from the revised theory, conduct a new empirical study to test the hypothesis, and so on. As  Figure 2.3  shows, this approach meshes nicely with the model of scientific research in psychology presented earlier in the textbook—creating a more detailed model of “theoretically motivated” or “theory-driven” research.

As an example, let us consider Zajonc’s research on social facilitation and inhibition. He started with a somewhat contradictory pattern of results from the research literature. He then constructed his drive theory, according to which being watched by others while performing a task causes physiological arousal, which increases an organism’s tendency to make the dominant response. This theory predicts social facilitation for well-learned tasks and social inhibition for poorly learned tasks. He now had a theory that organized previous results in a meaningful way—but he still needed to test it. He hypothesized that if his theory was correct, he should observe that the presence of others improves performance in a simple laboratory task but inhibits performance in a difficult version of the very same laboratory task. To test this hypothesis, one of the studies he conducted used cockroaches as subjects (Zajonc, Heingartner, & Herman, 1969) [3] . The cockroaches ran either down a straight runway (an easy task for a cockroach) or through a cross-shaped maze (a difficult task for a cockroach) to escape into a dark chamber when a light was shined on them. They did this either while alone or in the presence of other cockroaches in clear plastic “audience boxes.” Zajonc found that cockroaches in the straight runway reached their goal more quickly in the presence of other cockroaches, but cockroaches in the cross-shaped maze reached their goal more slowly when they were in the presence of other cockroaches. Thus he confirmed his hypothesis and provided support for his drive theory. (Zajonc also showed that drive theory existed in humans [Zajonc & Sales, 1966] [4] in many other studies afterward).

Incorporating Theory into Your Research

When you write your research report or plan your presentation, be aware that there are two basic ways that researchers usually include theory. The first is to raise a research question, answer that question by conducting a new study, and then offer one or more theories (usually more) to explain or interpret the results. This format works well for applied research questions and for research questions that existing theories do not address. The second way is to describe one or more existing theories, derive a hypothesis from one of those theories, test the hypothesis in a new study, and finally reevaluate the theory. This format works well when there is an existing theory that addresses the research question—especially if the resulting hypothesis is surprising or conflicts with a hypothesis derived from a different theory.

To use theories in your research will not only give you guidance in coming up with experiment ideas and possible projects, but it lends legitimacy to your work. Psychologists have been interested in a variety of human behaviors and have developed many theories along the way. Using established theories will help you break new ground as a researcher, not limit you from developing your own ideas.

Characteristics of a Good Hypothesis

There are three general characteristics of a good hypothesis. First, a good hypothesis must be testable and falsifiable . We must be able to test the hypothesis using the methods of science and if you’ll recall Popper’s falsifiability criterion, it must be possible to gather evidence that will disconfirm the hypothesis if it is indeed false. Second, a good hypothesis must be logical. As described above, hypotheses are more than just a random guess. Hypotheses should be informed by previous theories or observations and logical reasoning. Typically, we begin with a broad and general theory and use  deductive reasoning to generate a more specific hypothesis to test based on that theory. Occasionally, however, when there is no theory to inform our hypothesis, we use  inductive reasoning  which involves using specific observations or research findings to form a more general hypothesis. Finally, the hypothesis should be positive. That is, the hypothesis should make a positive statement about the existence of a relationship or effect, rather than a statement that a relationship or effect does not exist. As scientists, we don’t set out to show that relationships do not exist or that effects do not occur so our hypotheses should not be worded in a way to suggest that an effect or relationship does not exist. The nature of science is to assume that something does not exist and then seek to find evidence to prove this wrong, to show that it really does exist. That may seem backward to you but that is the nature of the scientific method. The underlying reason for this is beyond the scope of this chapter but it has to do with statistical theory.

• Zajonc, R. B. (1965). Social facilitation.  Science, 149 , 269–274 ↵
• Schwarz, N., Bless, H., Strack, F., Klumpp, G., Rittenauer-Schatka, H., & Simons, A. (1991). Ease of retrieval as information: Another look at the availability heuristic.  Journal of Personality and Social Psychology, 61 , 195–202. ↵
• Zajonc, R. B., Heingartner, A., & Herman, E. M. (1969). Social enhancement and impairment of performance in the cockroach.  Journal of Personality and Social Psychology, 13 , 83–92. ↵
• Zajonc, R.B. & Sales, S.M. (1966). Social facilitation of dominant and subordinate responses. Journal of Experimental Social Psychology, 2 , 160-168. ↵

A coherent explanation or interpretation of one or more phenomena.

A specific prediction about a new phenomenon that should be observed if a particular theory is accurate.

A cyclical process of theory development, starting with an observed phenomenon, then developing or using a theory to make a specific prediction of what should happen if that theory is correct, testing that prediction, refining the theory in light of the findings, and using that refined theory to develop new hypotheses, and so on.

The ability to test the hypothesis using the methods of science and the possibility to gather evidence that will disconfirm the hypothesis if it is indeed false.

Developing a Hypothesis Copyright © by Rajiv S. Jhangiani; I-Chant A. Chiang; Carrie Cuttler; and Dana C. Leighton is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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• How to Write a Strong Hypothesis | Steps & Examples

How to Write a Strong Hypothesis | Steps & Examples

Published on May 6, 2022 by Shona McCombes . Revised on November 20, 2023.

A hypothesis is a statement that can be tested by scientific research. If you want to test a relationship between two or more variables, you need to write hypotheses before you start your experiment or data collection .

Example: Hypothesis

Daily apple consumption leads to fewer doctor’s visits.

Table of contents

What is a hypothesis, developing a hypothesis (with example), hypothesis examples, other interesting articles, frequently asked questions about writing hypotheses.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess – it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Variables in hypotheses

Hypotheses propose a relationship between two or more types of variables .

• An independent variable is something the researcher changes or controls.
• A dependent variable is something the researcher observes and measures.

If there are any control variables , extraneous variables , or confounding variables , be sure to jot those down as you go to minimize the chances that research bias  will affect your results.

In this example, the independent variable is exposure to the sun – the assumed cause . The dependent variable is the level of happiness – the assumed effect .

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Step 1. ask a question.

Writing a hypothesis begins with a research question that you want to answer. The question should be focused, specific, and researchable within the constraints of your project.

Step 2. Do some preliminary research

Your initial answer to the question should be based on what is already known about the topic. Look for theories and previous studies to help you form educated assumptions about what your research will find.

At this stage, you might construct a conceptual framework to ensure that you’re embarking on a relevant topic . This can also help you identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalize more complex constructs.

Step 3. Formulate your hypothesis

Now you should have some idea of what you expect to find. Write your initial answer to the question in a clear, concise sentence.

4. Refine your hypothesis

You need to make sure your hypothesis is specific and testable. There are various ways of phrasing a hypothesis, but all the terms you use should have clear definitions, and the hypothesis should contain:

• The relevant variables
• The specific group being studied
• The predicted outcome of the experiment or analysis

5. Phrase your hypothesis in three ways

To identify the variables, you can write a simple prediction in  if…then form. The first part of the sentence states the independent variable and the second part states the dependent variable.

In academic research, hypotheses are more commonly phrased in terms of correlations or effects, where you directly state the predicted relationship between variables.

If you are comparing two groups, the hypothesis can state what difference you expect to find between them.

6. Write a null hypothesis

If your research involves statistical hypothesis testing , you will also have to write a null hypothesis . The null hypothesis is the default position that there is no association between the variables. The null hypothesis is written as H 0 , while the alternative hypothesis is H 1 or H a .

• H 0 : The number of lectures attended by first-year students has no effect on their final exam scores.
• H 1 : The number of lectures attended by first-year students has a positive effect on their final exam scores.

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

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A hypothesis is not just a guess — it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Null and alternative hypotheses are used in statistical hypothesis testing . The null hypothesis of a test always predicts no effect or no relationship between variables, while the alternative hypothesis states your research prediction of an effect or relationship.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

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McCombes, S. (2023, November 20). How to Write a Strong Hypothesis | Steps & Examples. Scribbr. Retrieved September 13, 2024, from https://www.scribbr.com/methodology/hypothesis/

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