Research Methods Continued

Question 1

What is reliability?

Answer 1

Reliability is the measure of consistency - getting the same results each time

Question 2

What is test-retest reliability?

Answer 2

Test-retest reliability is the same person/group undertaking the research measure - potential demand characteristics- time has to be taken into account between testing

Question 3

Understanding test-retest results

Answer 3

Test-retest results-> scores correlated after measure has been taken on two occasions - significant = high reliability (+0.8-1)

Question 4

Inter-observer reliability

Answer 4

Inter-observer reliability = extent to which two observers are observing and recording behaviours in a consistent way -> useful in ensuring reliability

Question 5

Inter-observer reliability and behavioural categories

Answer 5

Inter-observer reliability - used in measuring behavioural categories - inter-observer reliability ensures categories correct - as psychologist observe same situation together or seperately -scores are then correlated

Question 6

Improving reliability and questionnaires

Answer 6

Can identify questions that has the biggest impact on reliability

Question 7

Improving reliability and interviews

Answer 7

Adjusting interviews:
-same interviewer (creates researcher bias)
-training interviewers - eg the way questions are asked, how open they are

Question 8

Improving reliability and experiments

Answer 8

Experiments:
-level of control researcher has over variables
-lab = high reliability = control over IV - standardised procedures
-control over extraneous variables

Question 9

Improving reliability and observations

Answer 9

Observations:
Can look objectively- relies on observer interpretation
Operationalise behavioural categories (clear and specific)

Question 10

Difference between related and unrelated designs in psychology

Answer 10

Related designs = designs such as repeated measures and matched pairs where there are connections
Unrelated designs = designs such as independant groups where there is no connection between people in each group

Question 11

What are the 3 levels of data?

Answer 11

The three levels of data are norminal, odinal and interval

Question 12

What is meant by nominal data?

Answer 12

Norminal data refers to categorical data -> numbers referring to people in categories -> discrete data as each part appears in only one category
+ = Easily generated from closed questions
- = lacks depth

Question 13

What is meant by ordinal data?

Answer 13

Data ordered in some way - used to rank data on a numerical scale from high to low
+ = More detail than nominal
- = intervals not equal value so cannot use a mean

Question 14

What is meant by interval data?

Answer 14

Interval data: data on a numerical scale with units of equal size eg temp, objective
->Ratio data = type of interval data = fixed 0 = cannot have negative - eg weight and height
+ = more informative and reliable
- = can be arbitrary

Question 15

Considerations that researchers have to take into account when deciding on an appropiate statistical test

Answer 15

Considerations that researchers have to take into account when deciding on an appropriate statistical test:
-Wether you are investigating a difference (one control and one experimental condition) or a relationship (of two co-variables)
-Experimental design (when looking for a difference

Question 16

Statistical tests used for nominal data (for related or unrelated)

Answer 16

Nominal data:
Test of difference for related designs = Simon Sign Test
Test of difference for unrelated designs = Cowell Chi-Squared

Question 17

Stastical tests used for ordinal data (for related or unrelated

Answer 17

Ordinal data:
Test of difference for related designs = Wilcoxon (Wants)
Test of difference for unrelated designs = More Mann-Whitney Test
Test of association for ordinal data = Singers Spearman Rho

Question 18

Stastical tests for interval data

Answer 18

Interval data:
-Test of difference for related designs = Related T-test (parametric, receiving)
-Test of difference for unrelated designs = Unrelated T-test (parametric, unanimous)
-Test of association = Pearson’s R (parametric, praise)

Question 19

3 Parametric assumptions that have to be applied to use statistical tests

Answer 19

3 Parametric assumptions that have to be applied to use statistical tests:
-Data should be interval
-Data should be drawn from normally distributed population (inverted U)
-Should be homogeneity of variance between conditions (the deviation of scores is similar between conditions)

Question 20

What is the sign test?

Answer 20

The sign test is used when looking for a difference between paired data ie repeated measures or matched pairs - generates nominal data

Question 21

How to carry out the sign test

Answer 21

How to carry out the sign test:
-Each pair of data scored with either + or - (if there is no difference = 0)m
-Value of S is calculated (adding total + and - and selecting smallest value)
-Calculate N value (total - nil scores)
-Use against critical value to determine significance (equal or less to be significant)

Question 22

Chi-squared test

Answer 22

Chi-squared test = Test of either difference or association - used on nominal, unrelated data

Question 23

How to carry out the chi-squared test

Answer 23

Chi-squared test:
-Frequencies recorded and put into contingency table
-Degrees of freedom calculatred before determining significance of data ( df = ((rows-1))x((columns-1)) )
-To be significant = results equal or more than critical

Question 24

Calculating degree of freedom for chi-squared test

Answer 24

Calculating degree of freedom for chi-squared test:
df = (rows-1) x (columns-1)

Question 26

What three things should science have?

Answer 26

Science should have:
-Assumptions (paradigm - shared set of collective assumptions
-Scientific methods (empiricism)
-Terminology

Question 27

What was peppers idea on science?

Answer 27

Peppers idea = falsification - if it is false, then this can be shown by observation or experiment - cant be fully proven right but can be proven wrong - no theory in science final

Question 28

What is predictive power?

Answer 28

Predictive power is theories should take nomothetic approach (general laws should be applied)

Question 29

What is empiricism?

Answer 29

Empiricism - Locke - gathering information through observation/experiments rather than reasoned argument/opinion

Question 30

Types of internal validity?

Answer 30

Types of internal data:
Face validity - does it look like what is should be measuring
Concurrent validity - comparing to established test
Construct - using specific group with predictable results
Predictive - can performance be used to predict future behaviour

Question 31

Types of external validity

Answer 31

Types of external validity:
Ecological - reflective of everyday behaviour
Temporal - reflective of time periods
Population - reflective of target populations

Question 32

What is standard deviation?

Answer 32

Standard deviation is a measure to show to what extent the values in data deviate around the mean

Question 33

What is counterbalancing?

Answer 33

Counterbalancing is a technique used to deal with order effects when using a repeated mesures design - splitting up sample

Question 34

Designing experiments in psychology

Answer 34

Designing experiments in psychology:
-Self-report methods (interviews, questionnaires) (open/closed)
-Experimental design (RM, IM, MP)
-Procedure (sample size, type of sampling)
-Consent from participants