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Psychology > Stats Booklet 3 > Flashcards

Stats Booklet 3 Flashcards

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1
Q

Data types

A

-quantitative
-qualitative
-primary
-secondary

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2
Q

Quantitative

A

Numeric form(1) Can be collected from individual scores in and the number of words and uses closed questions

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3
Q

Qualitative

A

1)descriptive 2)written form written such as from notes within an interview , diary entry from open questions

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4
Q

S/W of quantitative data

A

Quantitative is more simple analyse which allows comparison drawn between groups ,

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5
Q

S/w qualitative data

A
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6
Q

Types of data- NOMINAL DATA
Identify)justify)contex

A

1)categorical data
2)
3)hair categ

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7
Q

Types of data ordinal

A

1)ranked - ordered
2)not in fixedbintervals/ subjective
3)1-10 memory test/ iq test

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8
Q

Interval data

A

1)continuos data
2)standard/universal/official measurement
3)numerical scales

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9
Q

Primary data - define
S/W

A

1) data collected first hand from ppts specific to aim of study
2)E.g questionnaire exp, interviews
3) S- first hand data specific for aim of research which allows to target info ij a way to suit their aim(CONTEXTofaim) increasint IV
4) W-time and effort to obtain data and analyse findings, whereas secondary data is easily accessed (less eff+ time)

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10
Q

Secondary data - define
S/W
Link to IV

A

1)previously collected by a third party not specifically for aim of study and used by researcher
2)gov stats
3)S-easily accessed and min effort , info trying to collect already exists vs primary conducted by researcher themselves
4)W- may be poor quality data /inaccurate. Could be outdated and incomplete and not meet aim of study(C)

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11
Q

Meta analysis define(2)

A

1)reseArch that uses secondary data to gain data from many studies, which investigated same questions and methods of research
2)combines info from all studies to reach conclusions about behaviour

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12
Q

Meta analysis S/W

A

1)gather data from a range of studies, allow to view data with more confidence and increases generalisability of the finding across larger pop. Incresing EV
2)W- prone to publication bias, as reaearcher may not select all studies, choosing to leave out studies with -ve results. Thus biased data and may represent only some of the relevant data. Decres IV

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13
Q

Qualitative data- DEFINE CONTENT ANALYSIS (2)

A

1)a method of analysing qualitative data by converting large amount of qualitative data into quant.
2)identifying meaningful codes that can be counted, enabling us to present data in a graph

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14
Q

1)Why is appropriate to use a CONTENT ANALYSIS?
2) what is coding?

A

1)the data being analysed is qualitative data
2)coding is the initial process of CA where qual is converted into meaningful categories

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15
Q

How is a content analysis carried out(4)

A

1)read transcript or watch video of context
2)identify coding categories (C)
3)re read the diaries/questionnaire or relisten to recordings and tally everytime a code appears
4) present quant data in a graph

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16
Q

Define thematic analysis (2)

A

1)analysing qual data by identifying themes allowing to present data in quantitative form
2) interview recordings radio

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17
Q

Thematic analysis carried out(4)

A

1)if data is not in scenario read the transcript/ watch recordings (aggressive behaviour interview)
2)read and re read transcript
3)identify coding categories (shouting)
4)combine these codes to reduce number if codes into 4 themes that are linked(theme of aggression)
5)present data in qualitative format

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18
Q

Thematic analysis S/W

A

S- it is easy to assess the reliability of the findings and conclusions cause other researchers can access materials and use the coding systems to ensure findings are consistent
W- researchers bias,
-content confirms researchers hypothesis is more likely to be identify and compared to content that contradicts their aim (C).
-reducing IV

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19
Q

Assessing reliability of CAnalysis . Test retest

A

1) researchers creates coding categories (C) and tally eveytime it occurs within qual data
2)same researcher repeats the content analysis on same qualitative data, interview, tallying each time the coding category occurs
3)compare results from each CA and correlate results using stats test
4)strong +0.8 correlation shows high rel

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20
Q

Assessing reliability of CAnalysis. Inter rater reliability.(4)

A

1)the two raters would resd through the qual data separately but create coding categories together
2)two raters read the same content (aggressive behav) but record tally separately
3)compare tallies from both raters and correlate using stats test
4)strong +0.8

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21
Q

Assessing the validity of content analysis face va concurrent.

A

1)superficial method of analysing validity. And independent psychologist from the same field will check the coding category to see if researcher is measuring what they intend to measure at first sight. If they say yes CA is valid
2)comparing the results of a new CA with a CA results whose validity has already been established . If the results from both are similar is valid. A stats test

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22
Q

Improving validity of Content Analysis.(2)

A

1)ensure coding categories are operationalised
2)researcher are trained on how to use coding categories

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23
Q

Measures of central tendency VS measure of dispersion

A

TENDENCY - MMM
DISPERSION - SD / RANGE

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24
Q

Define measures of central tendency.(2)

A

1)average value in a set of data, e.g
2) mean, mode median

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25
Q

Describe MODE, DATA, S/W

A

1) most common number in set of scores, and there can be more than one
2)NOMINAL DATA
3) S— easy to calculate, less prone to to distortion bu extreme values as it does not take in account all data. UNLIKE mean which is highly influenced by extreme values
W— may be inaccurate as it does not take into account all the number of scores in the data, unlike mean
Moreove many modes may ⬇️ usefulness

26
Q

Describe MEDIAN, data, s/w

A

1)median is the middle score in a list of ordered data / 2 more middle values add together and /2
2)ordinal
3) S-easy to calculate and not affected by extreme values unlike mean which is influenced by extreme value
W- not as accurate as mean / not representative as it does not take into account all set of score

27
Q

Describe MEAN, DATA, S/W

A

1)all scores added together / the total number of scores
2) INTERVAL(continuous data)
3) S- more sensitive and accurate as it takes into account all set of data UNLIKE
W- more likely to be affected by extreme value as it takes into account all set of data, leading to misreading the info

28
Q

Define measure of dispersion.(2)

A

Spread of scores(1) how far score vary from the mean or range
2) SD or range

29
Q

Describe RANGE,DATA, S/W

A

1)range is the spread of data from smallest to biggest
2)calculated by subtracting the lowest value from largest and adding 1
3)ORDINAL DATA
4) S- easy and quick to calculate as it uses only 2 pieces of information unlike SD which is more complex and time consuming
W- can be distorted by extreme values as it does not take into account all values just highest and lowest . Inaccurate range could be calculated

30
Q

DESCRIBE SD, DATA, S/W

A

1)spread of data around the mean , the larger the SD the more spread the SD is
2) larger SD, larger spread around the mean, less consistency and more individual differences.
3) INTERVAL
4) S- more precise as it takes into account al data and not just 2 values
W- more time consuming to calculate

31
Q

Interpreting TABLES, interpreting STANDARD DEVIATION.(3) model

A

1) The SD for condition A is 7 which is lower than the SD for condition B , 9
2) the smaller SD the less the data is spread around the mean
3)more consistency and individual difference between X and Y

32
Q

Interpreting TABLES, interpreting MEAN.(3)
(Higher mean better) lower speed better

A

1) the mean for A is 98 which is higher than mean for B is 78
2) higher mean a higher score so condition A is more effective than B

33
Q

Normal distribution features.

A

1)curve is symmetrical
2) extends outward never touches 0
3) the MMM all occupy around the same midpoint

34
Q

Positive skew distribuition features vs negative skew

A

Positive : most of the data is conc on the right hand side of the peak of database
Negative: maj of data is conc on the left side of the peak of data

35
Q

Drawing a distribuition and explaining.(3)-ve

A

1)negative skew suggesting that the test is easier as ppl get a higher score
2) to get normal distribution make test more difficult
3)to balance scores

36
Q

Graphs plotting (5)

A

1) identify graph
2) plot data
3)title
4)label axis
5)scales on y axis
—bar chart |no touching
—histogram |bars touching
—scatter|plot each score

37
Q

Graphs > Bar Charts > … data >

A

1) categorical data
2) divided into categories, appear as words
3)category on x axis and y axis frequency
4)never touch!!

38
Q

Graphs > Histograms > … data

A

1)continuous data
2) represents frequecies
3) X= scores are in equal intervals- equal widths of bars
4) freq on y axis
5) bars touching!!!

39
Q

Graphs > Scattergraph > … data

A

1) relationship between two co variables
2) represent correlations
3) each plot = 1 ppt = 2 scores

40
Q

Statiscal testing 3/4m

A

1) we have to see if our results are significant or non significant
2) to determine the likelihood the results/correlation/difference are due to chance OR IV/covariables
3) two types of hypothesis
4)stats test tell us which hypothesis is more probable

41
Q

P value and why 0.05 in psychology

A

1) probaility value
2) conventional value
3) not too lenient and not too stringent
4) strike balance between the risk of making type I or type II error

42
Q

Identifying a stats test (3)
D/C
ED
LM

A

1)diff or correlation
2) RM or MP and IGD
3)Ordinal interval or nominal

43
Q

No ric table

A

N O I
Difference-
RM sign test. Wilcoxon. Related
- IGD. Chi sq. mann whitney U unrelated
Link -C - chi sq x2. Spermans rho pearson’s

44
Q

Justifying stats test(3)

A

1) test of difference as it has IV , working in groups and not , DV assessment score out of 24.
2) independent group design, split into group ppts take part in 1 condition only
3) ordinal data , scores of ppts are ranked , prone to subjective measure of achievement

45
Q

Interpreting stats test. What information you need from scenario? (5)

A

1) one or two tailed hypothesis
2)N
3)p value
4)Calc value
5)critical value

46
Q

Model of interpreting a correlation stats test(4)

A

1) CRV= 0.556 due to P value being >0.05 a one tailed hypothesis where N = 21.
2) calculated value = 0.543 > CRV to be significant .
3) Cv< CRV so not significant reject alternative hypothesis and accept null
4) there is no significant relationship between X and Y

47
Q

Where do you find CV in sign test? Why

A

1( smaller number
2( less frequent

48
Q

Type I error define. 2/3M

A

1) when researcher has used a lenient P value .
2)The researcher thinks the results are significant when they are due to chance.
3)wrongly accept alt hyp and wrongly reject null hyp

49
Q

Type II error define .2-3 M

A

1) when researcher has used a stringent P value .
2)The researcher thinks the results are not significant when they are.
3)wrongly reject alt hyp and wrongly accept null hyp

50
Q

How to check for Type I error (3)

A

1) more stricter level of significance , P value and compare CV with CRV
2)if results are still significant then no error
3) e.g. researcher is confident of 98% they haven’t made type I error
4) if results are not significant made a type I error

51
Q

How to check for type II error (4)

A

1) more lenient level of significance , P value and compare CV with CRV
2)if results are still not significant then no type II error made
3) e.g. researcher is confident of 98% they haven’t made type II error/ results significant
4) if NOW results are significant made a type II error

52
Q

Reporting psych investigation.
Section 1. Abstract purpose and content.

A

1)allow a psychologist to gain an overview of the study and decide if want to read on
2) a summary of hypothesis,AMPFC, first part of psych reports , worth 150-250.

53
Q

Section 2 : Introduction
-Purpose and content

A

1)gives background on relevant therories to explain how aims and hypothesis are developed
2) describing previous research in the studied, links made with previous research and how current research will add to previous research. Ending with A+ Hyp

54
Q

Section 3: Method .
Purpose (1)

A

1) detailed description of what researcher did, enough to replicate

55
Q

SPEED

A

2)S- how many ppts,ages,gender
P-recipe with order of events and standardised instructions
E-details of apparatus + material
E- ethics+ how dealts
D-RM or covert observation, justifed choice of design

56
Q

Section 4 : Results
Purpose + content

A

1) to present summary of findings to the reader, rather than reviewing raw data
2) descriptive statistics- tables , graph, frequencies and measure of CT and D
Inferential stats- stats test, CLV, signific levels

57
Q

Section 5: discussion
Purpose + content

A

1)discuss findings and uses and future area of research
2) Summary of results-description of stats test
Compare with other results
Limitations and modifications
Implication & future research

58
Q

Reference of book and journal .(2)

A

— give details about books mentioned

1– A last name, Initials. Title.Place of public : publisher
2– author name, (date), title of article , journal title, volume,issue, page numbers.

59
Q

Peer review process (5)
-Gatekeeper to f__ f__ research

A

1– before publication, the pysch report goes through independent scrutiny, by independent psych in similar field
2-check for VAL. ORIGI.SIGNIFof research
3- methods and designs appropriateness is assessed
4- outcome: accept/reject/accept if improved
5-the editor of journal has final say whether the report should be published based on reviewers comments

60
Q

Peer review purpose (3)

A

1) whether research funding should be received
2) ensure quality and relevance of findings eg methodology, with reliabiltiy and accuracy of findings. Address weaknesses
3)allow research to be taken seriously as it has been ISCRUT

61
Q

Limitations of peer review (6)

A

1) fraud- unable to identify before publication
2) values- too difficult to separate personal values and be objective
3)BIAS- institutional- prestigious uni are favoured
Gender bias- male researchers are biased towards +ve findings
4)Anonymity - remains anonymous to give honest appraisal
BUT increases competition as researcher may criticise rival reviewers. Use Open review, reviewer name is visible

Psychology (5 decks)

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