Research Methods A.1

Question 1

What is a hypothesis?

Answer 1

A testable prediction derived from theories

Question 2

What is reactivity?

Answer 2

The adjustment of behaviour to knowledge about the study

Question 3

Examples of non-experimental methods:

Answer 3

naturalistic observations
case studies
surveys
correlational research

Question 4

Qualities of a naturalistic observation:

Answer 4

Mainly categorisiation, observer stays in the background

Question 5

Problems and solutions of naturalistic observations:

Answer 5

Problem: the reliability of categorisation
Solution: compare notes to for inter-observer reliability
Problem: Reactivity
Solution: Participant observation

Question 6

What are case studies?

Answer 6

observations of a single person, often used in clinical settings

Question 7

Problems and solution on case studies:

Answer 7

problems: lack of generalisation, lack of reproducibility, lack of cause and effect, which all means limited application

Question 8

What are examples of surveys?

Answer 8

Questionares, interviews and diary studies

Question 9

What are structured interviews?

Answer 9

a type of survey, with fixed questions in a fixed order, usually either multiple choice or ratings

Question 10

Strengths and limitations of structured interviews:

Answer 10

S: easily quantifiable, can compares answers, can ensure all topics will be covered
L: Rigid structure, not adaptable to ppts, surface info only

Question 11

Strengths and limitations of unstructured interviews:

Answer 11

S: more in depth info, relevant to each specific ppt
L: lack of generalisability, analysis is time consuming and answers are hard to compare

Question 12

Strengths and limitations of descriptive research overall:

Answer 12

S: sometimes the only practical or ethical way, real life studies have high ecological validity
L: researcher bias (it’s down to their subjective questions, observations and analysis) reactivity, lack of cause and effect

Question 13

What is correlational research?

Answer 13

A way of determining the direction and strength of a relationship between two variables without manipulating any variables

Question 14

What is an experimental method?

Answer 14

a manipulation of one or more variables, where we attempt to determine the effect of this manipulation on the other variable

Question 15

How can we deal with nuisance variables?

Answer 15

• turn it into a control variable if it varies for levels of the IV
• random allocation, or counterbalancing (ABBA) if it varies across ppts

Question 16

Strengths of experimental methods:

Answer 16

-relatively strong test of causality
-possibility of a variety of manipulative controls

Question 17

Limitations of experimental conditions?

Answer 17

-unnatural settings and tasks
- reactivity
ethical limitations (e.g. deception)
-some phenomena cannot be studied under controlled conditions (e.g. social interactions

Question 18

What is a within subjects design?

Answer 18

ppts do all conditions

Question 19

What is a between subject design?

Answer 19

ppts do different conditions (ppts differ BETWEEN conditions)

Question 20

What is a Quasi experiment?

Answer 20

one of IV’s are selected, but not manipulated. Usually a characteristic of ppts.

Question 21

Why are quasi experiments not truly experimental?

Answer 21

because we are technically not manipulating anything

Question 22

What is EEG and what are strengths and limitations?

Answer 22

-electrodes being placed on the scalp
- strengths: good temporal resolution
- limitations: poor spatial resolution (only picks up activity on the surface of the brain)

Question 23

What is an fMRI and what are the strengths and limitations?

Answer 23

-measures amount of oxygenated blood in areas of the brain
- strengths: good spatial resolution
- limitations: poor temporal resolution (5s delay)

Question 24

What are nominal levels of measurement?

Answer 24

numbers are merely labels, no relationships between size of numbers and attribute measured

Question 25

What are ordinal levels of measurement?

Answer 25

order of numbers = order of size of attribute measured. Only relative ranking… distances between scores vary e.g. IQ scores

Question 26

What are interval levels of measurement?

Answer 26

equal intervals on the scales, equal measures of magnitude e.g. Degrees Celsius. Zero isn’t relevant, and we can have minus values

Question 27

What are ratio levels of measurement?

Answer 27

All properties of interval scale, but we do have an absolute zero, which means absolute absence e.g. reaction times

Question 28

What level data can you not use the median?

Answer 28

nominal level

Question 29

What levels of data can you not use the mean?

Answer 29

Nominal and ordinal level

Question 30

What levels of data are bar graphs used for?

Answer 30

nominal and ordinal data

Question 31

What type of graphs are usually used to display correlations?

Answer 31

scatterplots

Question 32

What are the two correlation coefficients we use?

Answer 32

Pearson’s and Spearman’s (always lie between -1 and 1)

Question 33

Which coefficient is calculated directly from raw scores, and is suitable for interval or ratio level data?

Answer 33

Pearson’s

Question 34

Which coefficient is calculated from the ranking of raw scores, and is suitable for ordinal level data?

Answer 34

spearman’s

Question 35

When is it best to use density curves?

Answer 35

when we are dealing with a large sample size and are looking for an overall pattern

Question 36

In a normal distribution, what is the order of mean, median and mode?

Answer 36

all the same

Question 37

In a positively skewed density curve, what is the order of mean, median and mode?

Answer 37

mode, median, mean

Question 38

In a negatively skewed density curve, what is the order of the mean, median and mode?

Answer 38

mean, median, mode

Question 39

If we had to calculate ‘what percentage of people scored over 50?’ from a density curve, how would we do it?

Answer 39

find 50, then calculate the area of the curve from after that point, then times it by 100 to get a percentage

Question 40

What is a standard Z score and what is the formula?

Answer 40

• the number of standard deviations that a single value in the data set deviates from the mean
• formula is deviation of _ from mean divided by standard deviation

Question 41

How do you calculate degrees of freedom?

Answer 41

(no. rows - 1) x (no. columns - 1)

Question 42

what data is chi-squared usually performed on and how is the data presented?

Answer 42

usually nominal/ categorical data, data is presented in a contingency table

Question 43

In a density curve what is the value of the total area under the curve?

Answer 43

1 (100%)

Question 44

In chi-squared what are the observed frequencies and the expected frequencies?

Answer 44

the number or ppts measured in individual categories. the expected frequencies are the frequencies predicted by the null hypothesis. The bigger the gap between these values, the bigger the chi-squared value

Question 45

In what chi-squared test do we compares these observed values and expected values?

Answer 45

chi-squared test for goodness of fit

Question 46

if i had two sets of data e.g. scores in RMA exam and scores in RMB exam, and i wanted to ask the question of in which test getting a score of 50 is better, what calculation would i use?

Answer 46

calculate the Z scores: do 50- mean over SD for both groups, then whichever has the value that is closest to the mean is the one in which getting a score of 5o is better

Question 47

What is standardising?

Answer 47

adjusting values measured on a unique scale to a more common scale, usually by making the mean 0 and the standard deviation 1

Question 48

what does chi-squared test for goodness of fit tell us?

Answer 48

tells us about the PROPORTIONS of a population distribution e.g. is there gender bias in the psychology department? used to compare different variables of ONE level