4.2.3.2 Data handling and analysis Flashcards Preview

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Flashcards in 4.2.3.2 Data handling and analysis Deck (56)
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1

What is quantitative data?

Information that can be measured and written down with numbers

2

Name cons of quantitative data

  • Lacks details

3

Name pros of quantitative data

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

4

What is qualitative data?

Descriptive information that is expressed in words

5

Name cons of qualitative data

  • 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

6

Name pros of qualitative data

  • Lots of detail given 
    • Allows more depth of analysis

7

What is primary data?

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

e.g. data from an experiment or observation

8

Name pros of primary data

  • 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)

9

Name cons of primary data

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

10

What is secondary data?

Information that someone else has collected

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

11

Name pros of secondary data

  • Easy and quick to collect 
  • Large variety of it 

12

Name cons of secondary data

  • Data may be unreliable 
  • May be out of date 

13

What is meta-analysis?

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

14

Name pro of meta-analysis

Reduce problem of sample size

15

Name con of meta-analysis

Lots of conflicting results 

16

What do descriptive statistics help to do?

Help simplify large amounts of data

17

Name 2 types of descriptive statistics

  • Measures of Central Tendency
  • Measures of Dispersion

18

Name pro of mean

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

19

Name con of mean

  • Easily distorted by extreme values
    • = mean doesn't represent the average of data set as a whole

20

Name pro of median

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

21

Name con of median

  • Less sensitive then mean 
    • Not as representative as mean

22

Name pro of mode

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

e.g. favourite desserts 

23

Name con of mode

Basic - Doesn't repent data set as a whole

24

Name pro of range

Easy to calculate 

25

Name con of range

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

26

What does standard deviation tell us?

Tells us how far scores deviate from mean

27

What does a large SD tell us?

  • 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

What does a small SD tell us?

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

29

Name a pro of standard deviation ​

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

30

Name a con of standard deviation ​

SD can be distorted by extreme values