# Research Methods Flashcards

1
Q

correlation

A

a measure of how strongly 2 or more variables are related to each other

2
Q

is correlation more ethical

A

yes because nothing is manipulated

3
Q

positive correlation

A

as one variable increases, so does the other

4
Q

negative correlation

A

as one variable increases the other decreases

5
Q

correlation coefficient

A

measures the strength of relationship between -1 and +1

6
Q

2 types of hypothesis

A

null

alternate (one or two-tailed)

7
Q

two-tailed hypothesis

A

“there is a correlation between”

either positive or negative correlation

8
Q

one-tailed hypothesis

A

“there is a positive correlation” or “there is a negative correlation”

9
Q

null hypothesis

A

“there is no correlation between”

10
Q

nominal data

A

data put into named categories

11
Q

ordinal data

A

data put into rank order from lowest to highest

12
Q

interval data

A

data is taken using the same unit of measure throughout the range

13
Q

discrete data

A

data that can only take a certain individual value

14
Q

continuous data

A

data that can have any number value in a certain range

15
Q

assumptions of parametric tests

A

populations drawn from should be normally distributed, variances of populations should be equal, at least interval/ratio data, no extreme scores

16
Q

why non-parametric tests are used

A

when assumptions of parametric tests can’t be fulfilled, when distributions are non-normal

17
Q

independent variable

A

the factor you change

18
Q

dependent variable

A

the result when affected by the independent variable

19
Q

experiments designs

A

independent groups, repeated measures, matched groups, quasi

20
Q

independent groups

A

when there are groups of different participants being tested by the same test

21
Q

repeated measures

A

the groups of participants are the same but given different tests

22
Q

matched groups

A

the different groups are matched for intelligence/ability/skill etc.

23
Q

quasi

A

an experiment with independent variables that are not open to manipulation therefore, have naturally occurring groups

24
Q

if the standard deviation is large

A

the values are widely distributed and scores can occur a long way from the mean

25
Q

symmetrical distribution

A

mean = mode = median

26
Q

positive skew

A

histogram leans to left

mode < median < mean

27
Q

negative skew

A

histogram leans to right

mean < median < mode

28
Q

central tendency and spread most suitable for skewed distributions

A

median as mean would be affected by skewed value, IQR for spread

29
Q

central tendency and spread most suitable for symmetrical distributions

A

30
Q

most suitable graph to show how data is distributed

A

histogram

31
Q

symmetrical distributions on a boxplot

A

median in center, whiskers equal length

UQ - median = median - LQ

32
Q

negative skew on boxplot

A

median closer to UQ

UQ - median < median - LQ

33
Q

type 1 error

A

when you accept hypothesis but null hypothesis is correct

34
Q

type 2 error

A

when you accept null hypothesis when hypothesis is correct

35
Q

how to minimise type 1 and 2 errors

A

ensuring experiments are controlled, reliable and valid

36
Q

descriptive statistics

A

tables, graphs, mode/median/mean

37
Q

measures of dispersion

A

variance: average of the squared differences from the mean
standard deviation: a measure of how spread out the scores are (square root of variance)

38
Q

measures of central tendency

A

mean, mode, median

39
Q

standard deviation

A

measures the spread of the set of numbers (average of each number from mean)

40
Q

the bigger the standard deviation

A

the bigger the spread of numbers

41
Q

sample techniques

A

opportunity, random, self-select/volunteer, snowball, clinical

42
Q

purpose of binominal sign test

A

difference between 2 conditions when data falls into 2 categories

43
Q

alternate hypothesis

A

predicts there will be a relationship between the variables and the results are significant

44
Q

target population

A

the group of people the researcher is interested in and draws the sample from

45
Q

random sampling

A

each member of the target population has an equal chance of being chose so no bias and likely to be representative but no control over who is selected

46
Q

snowball sampling

A

relies on initial participants recruiting others to generate additional participants, sample is unlikely representative but easy if specific sample features required

47
Q

opportunity sampling

A

selecting people most easily available at the time of study, unlikely representative but quick and easy

48
Q

self-selected sampling

A

people asked to volunteer in the study, unlikely representative but those are usually willing and cooperative so perform best to ability

49
Q

what do you put into the abstract

A

brief statement of the topic investigated, design used, participants, stimulus materials, apparatus, brief results/analysis/conclusions

50
Q

what do you put into the introduction

A

review of background material, outline of the topics being investigated, aim and hypotheses

51
Q

what do you put into the discussion

A

interpretation and meanings of results, limitations of the study, short statement of results, account/explanation of findings, how it has benefited the community and improved understanding

52
Q

what do you put into a harvard reference

A

surname, first initials, year published, title, book, pages

53
Q

what do you put into the appendices

A

raw data, statistical calculations, stimulus material, standardised instructions, copies of questionnaires etc

54
Q

what is the purpose of a peer review

A

to validate new knowledge and ensure integrity, researchers comment on work, follow it up, produce further research