Scientific Processes

Question 1

The Scientific Process

Answer 1

1. Aims
   o A general statement of what the researcher intends to investigate (e.g., to investigate the effect of sleep on memory).
2. Hypotheses
   o Null Hypothesis: Predicts no relationship or difference between variables.
   o Alternative Hypothesis: Predicts a relationship or difference. It can be directional or non-directional.
3. Theories
   o A set of ideas intended to explain a phenomenon, which can be supported or refuted by empirical evidence.

Question 2

Variables

Answer 2

1. Independent Variable (IV)
   o The variable that is manipulated or changed by the researcher.
2. Dependent Variable (DV)
   o The variable that is measured to see the effect of the IV.
3. Operationalisation
   Clearly defining variables in terms of how they can be measured (e.g., operationalising “stress” as heart rate in beats per minute).

Question 3

Experimental Hypotheses

Answer 3

1. Directional Hypothesis (One-tailed)
   o Predicts the specific direction of the effect (e.g., “People who sleep 8 hours will score higher on memory tests than those who sleep 4 hours”).
2. Non-directional Hypothesis (Two-tailed)
   o Predicts an effect but not the direction (e.g., “There will be a difference in memory test scores between people who sleep 8 hours and those who sleep 4 hours”).

Question 4

Peer Review

Answer 4

1. Purpose
   o To validate the quality and credibility of research before publication.
2. Process
   o Experts in the field evaluate the methodology, data analysis, and conclusions of a study.
3. Functions
   o Allocating Research Funding: Ensures money is allocated to worthwhile projects.
   o Publication: Ensures only high-quality research is published.
   Assessing Research Ratings: University research is rated based on quality and originality.

Question 5

Control of Variables

Answer 5

1. Extraneous Variables (EVs)
   o Unrelated variables that can affect the DV if not controlled.
2. Confounding Variables
   o Variables that vary systematically with the IV and can obscure the true relationship.
3. Standardisation
   o Keeping conditions the same for all participants to reduce bias and increase reliability.

Question 6

Experimental Control

Answer 6

1. Randomisation
   o Using chance to reduce researcher bias (e.g., randomising the order of stimuli).
2. Counterbalancing
   o Used in repeated measures to reduce order effects by changing the order of conditions for participants.
3. Double-blind Procedure
   o Both the participants and the researchers are unaware of which condition participants are in to prevent bias.

Question 7

Sampling Techniques

Answer 7

1. Random Sampling
   o Every member of the population has an equal chance of being selected.
2. Stratified Sampling
   o Divides the population into subgroups (strata) and samples from each proportionally.
3. Opportunity Sampling
   o Using whoever is available at the time of the study.

Question 8

Reliability

Answer 8

1. Internal Reliability
   o The consistency within the test (e.g., all parts of the test should measure the same thing).
2. External Reliability
   o The consistency of the test over time (test-retest reliability).
3. Inter-Rater Reliability
   o The degree to which different observers agree in their observations or ratings.

Question 9

Validity

Answer 9

1. Internal Validity
   o Whether the results are due to the manipulation of the IV and not extraneous variables.
2. External Validity
   o The extent to which findings can be generalised to other situations, times, or populations.
   o Ecological Validity: Generalisation to real-life settings.
   o Population Validity: Generalisation to other groups of people.
3. Face Validity
   o Whether the test appears to measure what it claims to (e.g., a memory test actually tests memory).
4. Concurrent Validity
   o Comparing the test results with other measures that are already valid.

Question 10

Types of Data

Answer 10

1. Qualitative Data
   o Descriptive data, often involving thoughts, feelings, and opinions.
   o Strength: Provides rich detail and depth of understanding.
   o Limitation: Harder to analyse and make objective comparisons.
2. Quantitative Data
   o Numerical data that can be statistically analysed.
   o Strength: Easy to compare and analyse.
   o Limitation: Can oversimplify complex behaviour.

Question 11

Statistical Testing

Answer 11

1. Significance
   o Results are significant if the probability of them occurring by chance is less than 5% (p < 0.05).
2. Type I Error
   o False positive: rejecting a true null hypothesis.
3. Type II Error
   o False negative: failing to reject a false null hypothesis.

Question 12

Descriptive Statistics

Answer 12

1. Measures of Central Tendency
   o Mean: The arithmetic average.
   o Median: The middle value when data is ordered.
   o Mode: The most frequent value.
2. Measures of Dispersion
   o Range: The difference between the highest and lowest values.
   o Standard Deviation: The average amount by which scores deviate from the mean.

Question 13

Inferential Statistics

Answer 13

1. Parametric Tests
   o Used when data meets certain assumptions (e.g., normally distributed, interval data).
2. Non-Parametric Tests
   o Used when assumptions of parametric tests are not met (e.g., nominal or ordinal data).

Question 14

Correlation

Answer 14

1. Positive Correlation
   o As one variable increases, so does the other.
2. Negative Correlation
   o As one variable increases, the other decreases.
3. No Correlation
   o No relationship between the variables.
4. Correlation Coefficient
   o A statistical measure that indicates the strength and direction of the relationship (ranges from -1 to +1).