Types of Data (RM P2)

Question 1

What is Qualitative Data?

Answer 1

Non-numerical data expressed in words (e.g diary extracts)

Question 2

Pros and cons of qualitative data

Answer 2

+ rich in detail (more meaningful)
- difficult to analyse

Question 3

What is Quantitive Data?

Answer 3

Numerical data (e.g reaction time in milliseconds)

Question 4

Pros and cons of quantitative data

Answer 4

+ easier to analyse and identify data
- less detail

Question 5

What is primary data?

Answer 5

‘First hand’ data collected for the purpose of the investigation

Question 6

Pros and cons of Primary Data

Answer 6

+ Directly relevant data, more valid
- Requires more time and effort. Ethical considerations need to be taken into account

Question 7

What is Secondary Data?

Answer 7

Collected by someone other than the person conducting the research e.g the work of other psychologists or government statistic

Question 8

Pros and cons of Secondary Data

Answer 8

+ Minimal effort, therefore inexpensive and less time consuming
- Unknown quality or relevance, less valid

Question 9

What is Nominal Data?

Answer 9

Qualitative values, usually tallied, frequencies (not able to rank)

Question 10

e.g Nominal Data

Answer 10

• Gender
• Weather
• Ethnicity
• Marital status

Question 11

What is Ordinal Data?

Answer 11

Scaled or ranked data (ordered), will be subjective ratings, often seen as a score

Question 12

e.g Ordinal Data

Answer 12

1-5 on Likert Scale (can’t do division/multiplication

Question 13

What is Interval Data?

Answer 13

Ranked with equal measurement intervals/standardised measurements and units, objective with arbitrary zero (uses pre-existing measurement scales)

Question 14

e.g Interval Data

Answer 14

• Time
• Temperature
• Bank balance
  (Increments are an equal distance apart)

Question 15

What is Ratio Data?

Answer 15

Same as Interval, but includes an absolute zero

Question 16

e.g Ratio Data

Answer 16

• Cash
• Distance
• Weight

Question 17

adv and disadv mean

Answer 17

+ Takes account of all values to calculate the average
- Very small or very large values can affect the mean

Question 18

adv and disadv mode

Answer 18

+ only average that can be used if the data set is not in numbers (e.g colours of cars in a car park)
- Can be more than one mode: not always representative of the data

Question 19

adv and disadv median

Answer 19

+ Not affected by very large or very small values
- Median value may not actually be a number in the original data set

Question 20

adv and disadv range

Answer 20

+ Simple and easy to understand way to assess the spread of data
- Can be sensitive to extreme values and may not be a robust measure in the presence of outliers

Question 21

adv and disadv standard deviation

Answer 21

+ Based on all observations and is amenable for further mathematical treatment
- Cannot be exactly calculated for distribution with open-ended classes (e.g >100)

Question 22

What is a measure of Central Tendency?

Answer 22

• Measure of the central point in a set of values
• Most common measure of central tendency are:
  mean —> interval
  median —> ordinal
  mode —> nominal

Question 23

What is a measure of Dispersion?

Answer 23

• Describes the spread of data
• Most common measures of dispersion are:
  range, standard deviation (average spread of values around the mean)

Question 24

What is a bar chart used for?

Answer 24

• Nominal data only (separated bars)
• Height of bars represent frequencies

Question 25

What is a histogram used for?

Answer 25

• Continuous data: ordinal, interval, ratio (no gaps between bars)
• Shows frequency of data in successive numerical intervals
• IV plotted along x-axis, DV plotted along y-axis

Question 26

What is a contingency table used for?

Answer 26

• Raw scores displayed in columns and rows
• Often asks you to draw conclusions from the data

Question 27

What is a scatter graph/scattergram used for?

Answer 27

• Gives good visual picture of relationship between 2 varliables
• Aids interpretation of correlation coefficient

Question 28

Negatively skewed distribution

Answer 28

• Mean: pulled towards lower end (left) due to extreme low scores
• Median: middle value when all scores are arranged in order, falls between mode and mean
• Mode: highest point (most frequent) located to the right
• Mean<median<mode

Question 29

Positively skewed distribution

Answer 29

• Mean: pulled towards higher end (right) due to extreme high scores in the tail
• Median: middle value when scores are ordered, falls between mode and mean
• Mode: highest point of the distribution (most frequent), located to the left
• Mode< median< mean