introduction

Question 1

2 types of statistics

Answer 1

descriptive
inferential

Question 2

descriptive stats

Answer 2

describe study of population

Question 3

inferential stats

Answer 3

using what we know from data we’ve collected to make inferences about what we don’t

Question 4

cycle of experimental research design

Answer 4

current state of knowledge
construct hypothesis to test
design experiment
execute experiment
carryout stats analysis
interpret and report

Question 5

what’s a research design

Answer 5

framework / blueprint for conducting research project. details procedures to obtain correct info needed to solve research problem

Question 6

importance of research design

Answer 6

provides smooth operation
makes research efficient
blue print for advanced planning
precautions to reduce errors
reliability depends on design

Question 7

what makes a good research design

Answer 7

specifies sources and info needed
strategic roadmap for collecting and analysing data
defines timelines and cost
include statement of problem, procedures and techniques, range of processes and analysis

Question 8

criteria of research design

Answer 8

reliability
replication
validity

Question 9

types of validity

Answer 9

measurement
internal
external
ecological

Question 10

what are variables

Answer 10

main focus of research

Question 11

characteristics of variables

Answer 11

continuous (measure in a specific way and even intervals)
discrete (specific items)
categorical (eg mode of transport)
dichotomising continuous and discrete (convert with to categorical)

Question 12

4 levels of measurement

Answer 12

interval scale
ratio scale
nominal scale
ordinal scale

Question 13

interval scale

Answer 13

scores in order of magnitude with equal intervals

Question 14

ratio scale

Answer 14

same as interval but has absolute zero point

Question 15

nominal scale

Answer 15

attributes are only named

Question 16

ordinal scale

Answer 16

attributes are only ordered

Question 17

extraneous variables

Answer 17

might impact on variables we are interested in but failed to take into account

Question 18

confounding variables

Answer 18

types of extraneous variable related to both main variable and one we are interested in

Question 19

research designs - experimental

Answer 19

correlational
experimental
quasi

Question 20

research designs - cross sectional

Answer 20

longitudinal
case study

Question 21

correlational design

Answer 21

relationship / association between variables

Question 22

stats techniques used for correlational design

Answer 22

Pearson product of moment correlation
spearman’s rho
simple linear regression
multiple linear regression
chi squared analysis

Question 23

issues with correlational design

Answer 23

not causation (only observing and recording changes)

Question 24

experimental research design

Answer 24

experimenter manipulates the IV and see an effect on the DV (differences between conditions)

Question 25

features of experimental research

Answer 25

has a hypothesis
random allocation

Question 26

quasi research design

Answer 26

seeing if there are differences on the DV between conditions of the IV (pre existing difference)
no random allocation

Question 27

quasi stats techniques

Answer 27

t test
mann whitney
wilcoxon
analysis of variance

Question 28

structure of experimental design

Answer 28

has a time line:
obs = observation in relation to DV (pre and post test)
exp = experimental treatment
no exp = control
t = timing of obs

Question 29

within participant design

Answer 29

repeated measure / related
same ppt in every condition

Question 30

between participant design

Answer 30

independent / unrelated
different groups of ppts

Question 31

+ve of within participant design

Answer 31

control individual confounding variables
fewer ppts = low cost

Question 32

-ve of within participant design

Answer 32

order effects - practice, boredom, fatigue
counterbalancing
demand characteristics

Question 33

+ve of between participant design

Answer 33

less likely to get bored or tired = less order effects and demand characteristics

Question 34

-ve pf between participant design

Answer 34

more ppts
lose some control over confounding variables
individual differences

Question 35

cross sectional design

Answer 35

collection of data on more than one case at a single point in time with 2 or more variables
interested in variation and relationship between variables

Question 36

structure of cross sectional design

Answer 36

collection of data on a series of variables at a single point in time
creates a rectangle of data

Question 37

features of a questionnaire

Answer 37

reduced bias (presented to everyone the same way)
open and closed questions
descriptive research
large samples
self administered or by researcher
less intrusive
postal versions
easy to do and analyse

Question 38

pre coding questionnaire

Answer 38

set format closed responses
can be scanned into SPSS data sheet

Question 39

designing a self completion questionnaire

Answer 39

easy to follow
don’t cramp
identify response sets in a likert scale
clear instructions how to respond
keep questions and answers together
well worded questions
easily understood
happy to share info
start and end with ‘friendly’ questions
avoid 2 in 1
use simple language
avoid leading
don’t presuppose
ensure produce variablilty
test in person with trial
vary format to reduce boredom
include response id on every page

Question 40

+ve of self completion questionnaire

Answer 40

cheaper
quicker
no interviewer effects
no interviewer variability
convenience for respondents

Question 41

-ve of self completion

Answer 41

cannot prompt
cant ask too many
difficult to ask other kinds of questions
can be read as a whole
cant collect additional data
can report desirable answers not real
may not take seriously
not appropriate for all
risk of missing data
low response rate

Question 42

how to improve response rate

Answer 42

good covering letter
return S.A.E with clear instructions
follow up for no responses
questionnaire correct length
capture interest
limit open ended questions
provide incentive eg voucher

Question 43

what does a cover letter include

Answer 43

friendly
short
describe what’s being done
tailor to audience
incentives
s.a.e
use deadline
describe confidentiality
name and phone number

Question 44

features of follow ups

Answer 44

include 2nd copy of questionnaire
cant guarantee anonymity only confidentially
sounds surprised at non response

Question 45

how can bias occur with random allocation

Answer 45

due to missing data

Question 46

not randomly missing data

Answer 46

fails to reply to question because they don’t want to answer

Question 47

pilot study

Answer 47

tests measures too are going to use on a very small sample and helps identify the feasibility

Question 48

guidelines for creating data for analysis

Answer 48

decide variable and document them
design data set with one subject per line
variable with proper designated name
descriptive labels for each variable
select type for each variable
additional tips for categorical variables
define missing values codes
consider need for grouping variables

Question 49

variable with proper designated name

Answer 49

begin with letter
short
no blanks or special characters
unique and no duplicates
case doesn’t matter

Question 50

descriptive labels for each variable

Answer 50

eg Age: Age on 1st Jan 2022
Gender: male or female

Question 51

select type for each variable

Answer 51

numeric (quantitative)
character (categorical)

Question 52

additional tips for categorial variables

Answer 52

case consistent
avoid long data codes
consider binary coding

Question 53

what not to do with missing data

Answer 53

don’t fill with 0 eg use ‘’’

Question 54

data screening

Answer 54

check errors (scores out of range)
find error in data file
correcting the error in data file