Chapter 2 - Research Methods

Front 1

Theory

Back 1

A systematic way of organising and exploring observations.

Front 2

Hypothesis

Back 2

A belief about the relationship between two or more variables.

Front 3

Measure

Back 3

A variable which provides a concrete way of assessing it.

Front 4

Reliable

Back 4

Produces consistent results that does not show much random fluctuation.

Front 5

Valid

Back 5

If it accurately assesses the construct it is intended to measure.

Front 6

Experimental Method

Back 6

Manipulation of variables to assess cause and effect.

Front 7

Independent Variable

Back 7

The variable manipulated by researches.

Front 8

Dependent Variable

Back 8

The impact on the way participants respond.

Front 9

Experimental Conditions

Back 9

To understand cause and effect researchers change different possible variations in which they compare results.

Front 10

Experimental uses and advantages

Back 10

Demonstrates casual relationships, replicability (study can be repeated to see if same findings emerge), maximises control over relevant variables.

Front 11

Experimental Limitations

Back 11

Generalisability outside the lab, some complex phenomena can be readily tested using pure experimental methods.

Front 12

Steps of an Experiment

Back 12

Step 1: Framing a hypothesis
Step 2: Operationalising variables
Step 3: Developing a standardised procedure
Step 4: Selecting and assigning participants
Step 5: Applying statistical techniques to the data
Step 6: Drawing conclusions

Front 13

Descriptive Method (Case study, Naturalistic observation and survey research)

Back 13

Attempts to describe phenomena as the exist rather than to manipulate variables.

Front 14

Case Study Method

Back 14

In depths observations of a small number of cases.

Front 15

Case Study Uses and Advantages

Back 15

Describes psychological processes as the occur in individual cases, allows study of complex phenomena, provides data that can be useful in framing an hypothesis.

Front 16

Case Study Limitations

Back 16

Generalisability to the population, Replicability (study may not be repeatable), research bias, cannot establish caucation.

Front 17

Naturalistic Observation Method

Back 17

In depth observation of a phenomenon as it occurs in nature.

Front 18

Naturalistic Observation Uses and Advantages

Back 18

Reveals phenomena as they exist outside the lab, allows study of complex phenomena, provides data that can be useful in framing an hypothesis.

Front 19

Naturalistic Observation Limitations

Back 19

Generalisability to the population, observer effects: the presence of an observer may alter behaviour of the participants, replicability, researcher bias and can not establish caucation.

Front 20

Survey Research

Back 20

Asking people questions about their attitudes and behaviour etc.

Front 21

Survey Research Uses and Advantages

Back 21

Reveals attitudes or self reported behaviours of a large sample of individuals and allows quantification of attitudes or behaviours.

Front 22

Survey Research Limitations

Back 22

Self report bias: people may not be able to honestly or accurately and cannot establish caucation.

Front 23

Random Sample

Back 23

A sample selected from the general population that does not introduce systematic bias.

Front 24

Correlation Method

Back 24

Examines the extent to which two or more variables are related and can be used to predict one another.

Front 25

Correlation Uses and Advantages

Back 25

Reveals relationships among variables as they exist outside the lab and Allow quantification of relationships among variables.

Front 26

Correlation Limitations

Back 26

Cannot establish Caucation

Front 27

Correlation Coefficient

Back 27

Measures the extent to which two variables are related.

Front 28

Positive Correlation

Back 28

The higher participants on one variable, the higher they are likely to measure on the other side.

Front 29

Negative Correlation

Back 29

The higher participants measure on one variable, the lower they will measure on the other.

Front 30

Zero Correlation

Back 30

Unrelated variables, thus can not be used to predict one another.

Front 31

Correlation Matrix

Back 31

A table presenting the correlations among a number of variables.

Front 32

Descriptive Statistics

Back 32

Allows researchers to summarise data in a readily understandable form.

Front 33

Frequent Distribution

Back 33

Shows how frequent participants received each of many possible scores.

Front 34

Measure of Central Tendency

Back 34

Provides an index of the way a typical participant responded on a measure.

Front 35

Mean

Back 35

The average of the scores of all participants

Front 36

Mode

Back 36

The most common score

Front 37

Median

Back 37

Is the same score that falls in the middle of the distribution.

Front 38

Variability

Back 38

The extend to which participants tend to differ from one another.

Front 39

Standard Deviation

Back 39

Describes how much the average participant deviates from the mean.

Front 40

Normal Distribution

Back 40

The score of most participants fall in the middle of the bell-shaped distribution and progressively fewer participants have scores at either extremes.

Front 41

Percentile Scores

Back 41

Indicate the percentage of scores that fall below the.

Front 42

Statistical Significance

Back 42

Help determine whether the results of the study are likely to have occurred simply by chance or whether they reflect true properties of the population.

Front 43

Probability Value (p value)

Back 43

Represents the probability that any positive findings obtained were accidental or just a matter of chance. Psychologists accept p values that fall below 0.5 (less then 5%).

Front 44

Effect Size

Back 44

Indicates the magnitude of the experimental effect or the strength of a relationship.

Front 45

Chi-squared Test

Back 45

Compares the observed data with the results that would be expected by chance and test the likelihood that the difference between observed and expected are accidental.

Front 46

T Test

Back 46

A statistical procedure called analysis of variance (ANOVA), which compares the means of two or more groups. Assesses the likelihood that mean differences among groups occurred by chance.