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AQA A Level Psychology > 3.2.3.2 Data handling and analysis > Flashcards

3.2.3.2 Data handling and analysis Flashcards

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1
Q

What is quantitative data?

A

Information that can be measured and written down with numbers

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2
Q

Name cons of quantitative data

A
  • Lacks details
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3
Q

Name pros of quantitative data

A
  • Quick and easy to analyse
  • Easy to compare
  • Immediately quantifiable
  • Measured objectively
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4
Q

What is qualitative data?

A

Descriptive information that is expressed in words

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5
Q

Name cons of qualitative data

A
  • Time consuming/difficult to analyse (lots of detail)
  • Hard to make comparisons
  • Based on subjective interpretation of language
  • Not immediately quantifiable, data has to be transformed and only quantifiable if data is put into categories and frequency is counted
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6
Q

Name pros of qualitative data

A
  • Lots of detail given
    • Allows more depth of analysis
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7
Q

What is primary data?

A

Information that a researcher has collected him/herself for a specific purpose

e.g. data from an experiment or observation

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8
Q

Name pros of primary data

A
  • More relevant to topic of research = degree of accuracy is high
  • Greater validity ∵ study is designed and carried out for main purpose of research (collected objectively)
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9
Q

Name cons of primary data

A
  • Expensive to obtain
  • Limited to time, place and no. of participants
    • Secondary data can come from different sources & give more range and detail
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10
Q

What is secondary data?

A

Information that someone else has collected

e.g. the work of other psychologists or government statistics

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11
Q

Name pros of secondary data

A
  • Easy and quick to collect
  • Large variety of it
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12
Q

Name cons of secondary data

A
  • Data may be unreliable
  • May be out of date
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13
Q

What is meta-analysis?

A
  • A technique where researchers examine results of several studies
  • Rather than conducting new research with participants
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14
Q

Name pro of meta-analysis

A

Reduce problem of sample size

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15
Q

Name con of meta-analysis

A

Lots of conflicting results

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16
Q

What do descriptive statistics help to do?

A

Help simplify large amounts of data

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17
Q

Name 2 types of descriptive statistics

A
  • Measures of Central Tendency
  • Measures of Dispersion
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18
Q

Name pro of mean

A
  • Most sensitive ∵ includes all values in data set within calculation
    • More representative of data as whole
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19
Q

Name con of mean

A
  • Easily distorted by extreme values
    • = mean doesn’t represent the average of data set as a whole
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20
Q

Name pro of median

A
  • Not affected by extreme scores
    • More representative of overall data set
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21
Q

Name con of median

A
  • Less sensitive then mean
    • Not as representative as mean
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22
Q

Name pro of mode

A

For data that appears in categories = only method you can use

e.g. favourite desserts

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23
Q

Name con of mode

A

Basic - Doesn’t repent data set as a whole

24
Q

Name pro of range

A

Easy to calculate

25
Q

Name con of range

A
  • Only takes account 2 most extreme values
    • Unrepresentative of data set as whole
26
Q

What does standard deviation tell us?

A

Tells us how far scores deviate from mean

27
Q

What does a large SD tell us?

A
  • Lots of spread within data set
    • e.g. not all participants were affected by IV in same way
  • May be few anomalous/extreme values
28
Q

What does a small SD tell us?

A
  • Data tightly clustered around mean
    • Suggests participants respond in fair similar way to IV
29
Q

Name a pro of standard deviation ​

A

Very precise (more than range), includes all values in data set

30
Q

Name a con of standard deviation ​

A

SD can be distorted by extreme values

31
Q

Why do we use graphs and tables?

A

Allows us to ‘eyeball’ data and see findings at a glance

32
Q

Name 4 presentations/displays of quantitative data

A
  • Bar Chart
  • Histogram
  • Line Graph
  • Scatter Graph
33
Q

Draw a normal distribution. Label the mode, median, mean on it.

A
34
Q

Draw a negatively skewed distribution. Label the mode, median, mean on it.

A
35
Q

Draw a postively skewed distribution. Label the mode, median, mean on it.

A
36
Q

Describe the long tail in a postive skew

A

Long tail is on positive side of peak

37
Q

Describe the long tail in a negative skew

A

Long tail is negative side of peak

38
Q

What does statistical testing tell us?

A

Tell us whether difference/relationship between variables are statistically significant or if they’re occurred by chance

39
Q

What are inference tests?

A

Statistical tests that allow us to infer things about what data means

40
Q

State the difference between descriptive and inferential statistics

A
  • Descriptive statistics
    • Describe summary of data
  • Inferential statistics
    • Allows us to make conclusion
    • Make an inference about data
41
Q

Statistical Testing

State significance/probability

A
  • Accepted level of probability = 5%
  • p < 0.05
    • Result occurred by chance is equal or less than 5%
42
Q

Name 3 factors to determine which inferential test should be used

A
  1. Research design
  2. Research aim
  3. Type of data (level of measurement)
43
Q

Factors to determine which inferential test should be used…

Describe research design

A

Data can be related or unrelated

  • Related data is produced from repeated measures and matched pair designs
  • Unrelated data is produced from independent group designs
44
Q

Factors to determine which inferential test should be used…

Describe research aim

A

Looking for a difference/relationship?

45
Q

Name 3 types of data

A
  • Nominal
  • Ordinal
  • Interval/ratio data
46
Q

Describe nominal data

A

Distinct category

47
Q

Describe ordinal data

A

List of data that can be ranked in order

e. g. subjective rating of happiness from a questionnaire
(i. e. happiness rating of 10 is higher than 5, but 2x as happy as 5)

48
Q

Describe interval/ratio data

A
  • Measured on a scale in which each interval is exactly same size
    • e.g. time, 10s 2x as long as 5s
  • Continuous
49
Q

Describe when you used use the Sign Test (i.e. the 3 conditions)

A
  • Looks for a difference
  • Used for repeated measures designs
  • Data is nominal
50
Q

The Sign Test

Describe Step 1

A
  1. Participant value in ‘experiment’ column − participant value in ‘control’ column
  2. Record its sign (+,-,0)
51
Q

The Sign Test

Describe Step 2

A
  1. Count no. of times the LESS FREQUENT sign occurs
  2. This gives us S
52
Q

The Sign Test

Describe Step 3

A
  1. Count total number of pluses and minuses
  2. This gives us N
53
Q

The Sign Test

Describe Step 4

A

Decide if hypothesis was directional or non-directional

(directional = one-tailed, non-directional = two-tailed)

54
Q

The Sign Test

Describe Step 5

A

Reading Critical Tables

  1. Use critical table to find N and 0.05
  2. & then determine if results are significant
55
Q

The Sign Test

Describe Step 6

A

State the conclusion

  • If result significant = accept experimental hypothesis
  • If result insignificant = accept null hypothesis
56
Q

Hypothesis: the recall of word lists will be greater in the silent condition compared to the noise condition

State whether the results are significant & the conclusion. Show all your working.

A

Results are significant. so we accept the experimental hypothesis

AQA A Level Psychology (10 decks)

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