research methods- statistics

Question 1

quantitative data

Answer 1

data expressed nnumerically. this data can be gained from individual scores in experiements

Question 2

evaluation of quantitative data

Answer 2

+ simple to analyze
- lacks depth and meaning

Question 3

qualitative data

Answer 3

data expressed in words or descriptive data. in form of written description of thought, feelingsand opinions

Question 4

qualitative data evaluation

Answer 4

+ rich detail and depth
- harder to analyse

Question 5

descrete data

Answer 5

info that can be categorised into groups, the data can only appear in one category. cant be sub-divided

Question 6

continuous data

Answer 6

data that can be measured using scientific tools

Question 7

nominal

Answer 7

data in the form of categories
something you can count
subjective at time

Question 8

ordinal

Answer 8

data in order/ ranked
doesnt have equal intervals
based on subjective opinions
doesnt use raw data so isnt very precise

Question 9

interval

Answer 9

data that is a standard/universal/offical measurement
based on objective meaures
interval is based on numerical scales that include units of equal precisely defined size

Question 10

primary data

Answer 10

data gathered first hand/ directly from participants. specific to the aims of the study.

Question 11

primary data evaluation

Answer 11

+ specifically for the aim
- involves time and effort to obtain the data as well as analyse the findings

Question 12

secondary data

Answer 12

has previously been collected by a third party, no specific to the aims of the study.

Question 13

secondary data evaluation

Answer 13

+ requires minimal effort
- may be poor quality or have inaccuracy or out of date information

Question 14

meta analysis

Answer 14

a form of research methods that use secondary data as it gains data from a large number of studies, which hae been investigted the same research questions and methods of research. then it combies the information to make conclusions

Question 15

meta analysis evaluations

Answer 15

+ increases generalisablitity
- prone to publication bias

Question 16

content analysis

Answer 16

method of analysing qualitative data by changing large amounts of qualitative data into quantitative data. this si doen by codes that can be counted so that we can make a graph

Question 17

when is it appropriate to use content analysis

Answer 17

the data () being analysed is qualitative

Question 18

what is meant by coding

Answer 18

coding is the initial process of a content analysis where qualitative data is placed into meaningful categories

Question 19

how is content analysis carried out

Answer 19

: read/ view video or trandscript
: create codes (give example)
: re-read and tally everytime each code appears
: present the quantitative data in graph/ table

Question 20

thematic analysis

Answer 20

method of analysing qualitative data by identifying emergent themes enabling us to present the data in qualitative format

Question 21

how is thematic analysis carried out

Question 22

thematic analysis evaluation

Answer 22

+ easy to assess the reliability of findings because others can access the material and use codes
- research bais

Question 23

ways to assess reliability of content analysis

Answer 23

: test re-test
: inter-rater reliability

Question 24

test re-test

Answer 24

: does content analysis
: same researcher repeats the content analysis on the same data
: compare results
:correlate using stats test
: strong posistive of 0.8+ shows high reliability

Question 25

inter-rater reliability

Answer 25

: two rates read through data seperately : create codes together : both read the exact same content but record sperately : compare tallies : correlate using appropriate stats test : strong positive correlation shs high reliability

Question 26

ways to improve reliability of content analysis

Answer 26

: operationalise

Question 27

operationalise

Answer 27

means t be speific and clear when defining coding categories to make the codes more measurable

Question 28

why is it important to operationalise

Answer 28

if coding categories are vague then it wouldnt be possible to repeat the research to check for consistent results increases reliability, other researchers can repeat and check for consistent results

Question 29

face validity

Answer 29

psychologist in the same field seeing if a coding category looks like it measures what it claims to measure at firs sight/ face value. if they say yes the content analysis is valid

Question 30

concurrent validity

Answer 30

comparing the results of a new content analysis with results from another similar pre-existing content analysis which has already been astablished for its validity. if the results from both are similar we can assume the test is valid. correlation of coding recordings gained from an appropriate stats test should be more that 0.8

Question 31

ways to improve the validity of content analysis

Answer 31

operationalise categories train researchers in how to use the coding categories

Question 32

what is meant by measures of central tendency and eg.'s

Answer 32

the general term for any measure of average value in a set of data mode,median, mean

Question 33

mode and what data it is used with

Answer 33

most common or popular number in set of scores and there can be more than one mode in data set used with nominal data

Question 34

mode evaluations

Answer 34

+ easy to calculate + less prone to distortion by extreme values - doesnt take into account all data so may be less accurate

Question 35

median and the date used with

Answer 35

middle score in a list of ranked-ordered scores. used with ordinal data

Question 36

median evaluation

Answer 36

+ easy to calculate + not efffected by extreme values - not as sensitive as mean as doesnt use all data

Question 37

mean and the data it is used with

Answer 37

all scores added up and divided by the total number of scores used with interval data

Question 38

evaluation of mean

Answer 38

+ most accurate and sensitive measure - affected by extreme scores

Question 39

measures of dispersion

Answer 39

this is based on the spread of scores, how far scores vary from the mean or average eg. range, standard deviation,

Question 40

range and the data used with it

Answer 40

the spread of data from the smallest to largest calculated by substracting the lowest value from the highest value and adding 1 used for ordinal data

Question 41

range evaluations

Answer 41

+ easy and quick to calculate - can be distorted by extreme

Question 42

standard deviation and the data used with it

Answer 42

measure of spread around mean higher the SD the more the spread larger the number the less consisten and more individual differences used with interval data

Question 43

standard deviation

Answer 43

+ most precise/ sensitive measure + less easily distorted by extreme value - more complicated and time consuming

Question 44

writing frame for interpretating the mean

Answer 44

the mean for condition ------- is ------ which is (higher/ lower) than the mean for condition ------ which is ------ therefore----- (effective or not) for standard deviation change effective to consistent

Question 45

normal distribution

Answer 45

curve is symmetrical extends outward but never touches 0 mean, median mode is around the same

Question 46

skewed distribution

Answer 46

not symmetrical- data clusered at one end positive skew: most of data towards the left negative skew: most of data is concentrated on the right

Question 47

bar charts

Answer 47

: display discrete data : used when data is divided into categories- they will be words : frequency as y axis : used to compare conditions bars dont touch

Question 48

histograms

Answer 48

: display continuous data or data where each participant has an individual score : represent frequences : scores with equal intervals on x-axis : frequency on y-axis : bars should always touch each other

Question 49

scattergram/ scattergraph

Answer 49

used to display a relationship between wo co-variables represent corelation each plot on the graph represents 1 ppt but 2 scores

Question 50

a statistical test tells us which hypothesis is most likely to be true or most probable

Answer 50

accepted significance level in psychology is less than 5%. this means there is less than 5% probability that the results occurred by chance/ extraneous variables so more than 95% was because of the iv

Question 51

statistical testing or inferential testing

Answer 51

when we carry out these tests it gives us a score which is a value for the research. this is called the calculated or observed value you then compare the calculated value to a critical value. the critical value decides whether or not the calculated value is significant if the calculated value is signifacant we can accept our alternative hypothesis