4.2.3.2 Data handling and analysis

Question 1

What is quantitative data?

Answer 1

Information that can be measured and written down with numbers

Question 2

Name cons of quantitative data

Answer 2

• Lacks details

Question 3

Name pros of quantitative data

Answer 3

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

Question 4

What is qualitative data?

Answer 4

Descriptive information that is expressed in words

Question 5

Name cons of qualitative data

Answer 5

• 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

Question 6

Name pros of qualitative data

Answer 6

• Lots of detail given
  
  • Allows more depth of analysis

Question 7

What is primary data?

Answer 7

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

e.g. data from an experiment or observation

Question 8

Name pros of primary data

Answer 8

• 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)

Question 9

Name cons of primary data

Answer 9

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

Question 10

What is secondary data?

Answer 10

Information that someone else has collected

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

Question 11

Name pros of secondary data

Answer 11

• Easy and quick to collect
• Large variety of it

Question 12

Name cons of secondary data

Answer 12

• Data may be unreliable
• May be out of date

Question 13

What is meta-analysis?

Answer 13

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

Question 14

Name pro of meta-analysis

Answer 14

Reduce problem of sample size

Question 15

Name con of meta-analysis

Answer 15

Lots of conflicting results

Question 16

What do descriptive statistics help to do?

Answer 16

Help simplify large amounts of data

Question 17

Name 2 types of descriptive statistics

Answer 17

• Measures of Central Tendency
• Measures of Dispersion

Question 18

Name pro of mean

Answer 18

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

Question 19

Name con of mean

Answer 19

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

Question 20

Name pro of median

Answer 20

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

Question 21

Name con of median

Answer 21

• Less sensitive then mean
  
  • Not as representative as mean

Question 22

Name pro of mode

Answer 22

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

e.g. favourite desserts

Question 23

Name con of mode

Answer 23

Basic - Doesn’t repent data set as a whole

Question 24

Name pro of range

Answer 24

Easy to calculate

Question 25

Name con of range

Answer 25

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

Question 26

What does standard deviation tell us?

Answer 26

Tells us how far scores deviate from mean

Question 27

What does a large SD tell us?

Answer 27

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

Question 28

What does a small SD tell us?

Answer 28

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

Question 29

Name a pro of standard deviation ​

Answer 29

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

Question 30

Name a con of standard deviation ​

Answer 30

SD can be distorted by extreme values

Question 31

Why do we use graphs and tables?

Answer 31

Allows us to 'eyeball' data and see findings at a glance

Question 32

Name 4 presentations/displays of quantitative data

Answer 32

* Bar Chart * Histogram * Line Graph * Scatter Graph

Question 33

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

Answer 33

Question 34

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

Answer 34

Question 35

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

Answer 35

Question 36

Describe the long tail in a postive skew

Answer 36

Long tail is on positive side of peak

Question 37

Describe the long tail in a negative skew

Answer 37

Long tail is negative side of peak

Question 38

What does statistical testing tell us?

Answer 38

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

Question 39

What are inference tests?

Answer 39

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

Question 40

State the difference between descriptive and inferential statistics

Answer 40

* Descriptive statistics * Describe summary of data * Inferential statistics * Allows us to make conclusion * Make an inference about data

Question 41

Statistical Testing State significance/probability

Answer 41

* Accepted level of probability = 5% * p \< 0.05 * Result occurred by chance is equal or less than 5%

Question 42

Name 3 factors to determine which inferential test should be used

Answer 42

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

Question 43

Factors to determine which inferential test should be used... Describe research design

Answer 43

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

Question 44

Factors to determine which inferential test should be used... Describe research aim

Answer 44

Looking for a difference/relationship?

Question 45

Name 3 types of data

Answer 45

* Nominal * Ordinal * Interval/ratio data

Question 46

Describe nominal data

Answer 46

Distinct category

Question 47

Describe ordinal data

Answer 47

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)

Question 48

Describe interval/ratio data

Answer 48

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

Question 49

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

Answer 49

* Looks for a difference * Used for repeated measures designs * Data is nominal

Question 50

**The Sign Test** Describe Step 1

Answer 50

1. Participant value in 'experiment' column − participant value in 'control' column 2. Record its sign (+,-,0)

Question 51

**The Sign Test** Describe Step 2

Answer 51

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

Question 52

**The Sign Test** Describe Step 3

Answer 52

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

Question 53

**The Sign Test** Describe Step 4

Answer 53

Decide if hypothesis was directional or non-directional (directional = one-tailed, non-directional = two-tailed)

Question 54

**The Sign Test** Describe Step 5

Answer 54

Reading Critical Tables 1. Use critical table to find N and 0.05 2. & then determine if results are significant

Question 55

**The Sign Test** Describe Step 6

Answer 55

State the conclusion * If result significant = accept experimental hypothesis * If result insignificant = accept null hypothesis

Question 56

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.

Answer 56

Results are significant. so we accept the experimental hypothesis