9a) data handling

Question 1

What is qualitative data?

Answer 1

-not numerical
-in words describing thoughts, feelings and opinions
-rich in detail
-might include a reason as to why the behaviour occurred
-acknowledges it is subjective

Question 2

What are the pros of qualitative data?

Answer 2

-provides rich insight and understanding of the issue
-can help explain the why of a phenomenon
-less reductionist than quantitive data

Question 3

What are the cons of qualitative data?

Answer 3

-more open to researcher bias
-harder to analyse

Question 4

What quantitive data?

Answer 4

-numerical data that can be statistically analysed
-does not include a reason or explanation
(E.g. numerical data collected in experiments / observations / correlations)

Question 5

What are the pros of quantitive data?

Answer 5

-allows for easier analysis / comparison
-objective and scientific
-less chance of researcher bias

Question 6

What are the cons of quantitive data?

Answer 6

-the “why” often cannot be answered
-can be viewed as reductionist
-> because complex ideas are reduced to numbers

Question 7

Are qualitative and quantitive data mutually exclusive?

Answer 7

-no many studies collect both types of data
-e.g. in Milgram = 65% fully obedient, but he also reported the comments of observations and interviews the participants afterwards
-they can be complementary

Question 8

What is primary data?

Answer 8

-is any data that has been collected by the psychologist for the purpose of their own research or investigation
-it is direct relevance to their research aim and hypothesis
-> answers from a questionnaire
-> notes from an observation
-> results from an experiment

Question 9

What are the pros of primary data?

Answer 9

-gathered for the aim of the study
-replicable
-taken directly from the population

Question 10

What are the cons of primary data?

Answer 10

-researcher bias
-time and effort
-needs a large sample to make it generalisable

Question 11

What is secondary data?

Answer 11

-any data that already exists and was collected for another purpose
-> government statistics
-> newspapers
-> websites

Question 12

What are the pros of secondary data?

Answer 12

-easier to access than primary
-large sample may exist
(E.g. government data)

Question 13

What are the cons of secondary data?

Answer 13

-data may not fit what the researcher wants to find out
-may be of poor quality

Question 14

How can we remember levels of data?

Answer 14

N-O-I-R

Question 15

What is nominal data?

Answer 15

-named variables
-> most appropriate measurement is the mode
Categories that can’t be logically ordered

Question 16

What is an example of nominal data?

Answer 16

Blood types
(They can be put into categories, but not ordered)

Question 17

What is ordinal data?

Answer 17

-named and ordered variables
-> presented in a ranked order
-> like nominal but with a meaningful order or rank to the categories

Question 18

What is an example of ordinal data?

Answer 18

Education level
(nursery, primary, secondary)

Question 19

What is interval data?

Answer 19

-named, ordered and proportionate variables
-> fixed units with equal gaps between
-> numerical distances between values, but there is no zero

Question 20

What is an example of interval data?

Answer 20

The difference between the values of temperature in Celsius and Fahrenheit
(10 degrees and 20 degrees have the same gap as 20 degree and 30 degrees)

Question 21

What is ratio data?

Answer 21

-named, ordered, proportionate interval between variables and can accommodate absolute zero

Question 22

What is an example of ratio data?

Answer 22

Height or weight in cm and kg

Question 23

Can you convert data into other levels?

Answer 23

-yes it is possible to convert data into another level
-may be needed for statistical tests
(E.g. calorie scale into a health scale)