Aims & Hypotheses (College Board AP® Psychology): Study Guide

Aims

• The aim of a study is a general statement describing what the researcher intends to investigate

  • It identifies the purpose of the research

  • It outlines the topic, theory, or concept being studied

  • It is written in broad terms

• Examples:

  • To investigate the effect of caffeine on memory

  • To examine whether sleep affects reaction time

  • To explore the relationship between stress and exam performance

• An aim tells us what the study is about, but it does not provide a precise prediction - that is the role of the hypothesis

Hypotheses

• A hypothesis is a specific, testable prediction about the outcome of a study. It must:

  • clearly state the relationship between variables

  • be measurable and falsifiable

• In experimental research, a hypothesis identifies:

  • The independent variable (IV) and the dependent variable (DV)

• A strong hypothesis:

  • is clear and unambiguous

  • states how variables are defined and measured (operational definitions)

  • can be supported or refuted by data

Operational definitions

• For a hypothesis to be testable, variables must be operationally defined

  • An operational definition explains exactly how a variable is manipulated or measured so that the study can be replicated

Example

• Aim:

  • To investigate the effect of caffeine on memory

• Operationalised IV:

  • 200 ml of caffeinated drink vs. 200 ml of water

• Operationalised DV:

  • Number of correctly recalled words out of 15

• Clear operational definitions:

  • Make the study measurable

  • Allow other researchers to replicate the procedure

  • Ensure the hypothesis can be tested and falsified

• If variables are vague (e.g., “participants drank caffeine” or “memory improved”), the study cannot be reliably replicated

Types of hypotheses

Alternative hypothesis

• The alternative hypothesis predicts that the IV will affect the DV (or that a relationship exists between variables)

  • It includes clearly defined variables and measurable outcomes

• There are two types: directional and non-directional

Directional (one-tailed)

• A directional hypothesis predicts the direction of the effect or relationship

• For example:

  • Participants who drink 200 ml of caffeine before a memory test will correctly recall more words out of 15 than participants who drink 200 ml of water

• Researchers use directional hypotheses when prior research suggests a specific expected outcome

Non-directional (two-tailed)

• A non-directional hypothesis predicts that a difference or relationship exists but does not state the direction

• For example:

  • There will be a difference in the number of correctly recalled words out of 15 between participants who drink 200 ml of caffeine and those who drink 200 ml of water before a memory test

• Researchers use this when evidence is limited or mixed

Null hypothesis

• The null hypothesis states that there is no effect or no relationship

• For example:

  • There will be no difference in the number of correctly recalled words out of 15 between participants who drink 200 ml of caffeine and those who drink 200 ml of water before a memory test

• In statistical testing, researchers analyze data to determine whether they can reject the null hypothesis

  • If the results are:

    • statistically significant, the null hypothesis is rejected

    • not statistically significant, the null hypothesis is not rejected

Correlational hypotheses

• In correlational research:

  • No variable is manipulated

  • There is no IV or DV

  • The hypothesis predicts a relationship, not a difference

• A non-directional correlational hypothesis predicts a relationship but does not state the direction:

  • There will be a relationship between the number of cups of caffeine consumed per day and hours of sleep per night

• A directional correlational hypothesis predicts both a relationships and its direction

  • There will be a negative relationship between the number of cups of caffeine consumed per day and hours of sleep per night

• A null hypothesis states no relationship exists

  • There will be no relationship between the number of cups of caffeine consumed per day and hours of sleep per night

Falsifiability

• A hypothesis must be falsifiable.

• This means that:

  • it must be possible for evidence to show that the hypothesis is wrong

  • the prediction must be measurable

  • the variables must be clearly defined

• A falsifiable hypothesis can be tested and potentially disproven:

  • Participants who sleep 8 hours will score higher on a 20-question memory test than participants who sleep 4 hours

• A hypothesis that is too vague cannot be directly tested:

  • Sleep improves memory because the brain “recharges”