L3 Quantitative Research

Question 1

What is Quantitative Research

Answer 1

Confirmatory

• reality is objective and identifiable (behavioral psychology, economics, statistics)
• surveys, experiments, conjoint

Question 2

Conjoint analysis

Answer 2

is a survey-based statistical technique used in market research that helps determine how people value different attributes (feature, function, benefits) that make up an individual product or service.

Question 3

example descriptive questions:

Answer 3

e.g.: - consumer characteristics: what percentage of consumers are in their 30s?

Question 4

What is a good descriptive research?

Answer 4

minimizes the error in representing reality

Question 5

What types of error do we have?

Answer 5

Total survey error = Random error + Systematic error (bias)

Question 6

random error

Answer 6

difference btw. the sample value and the true value of the population mean (no direct control over this, results form chance variation)

Question 7

systematic error

Answer 7

• problems in the very research design (measurement error )

- problems in the sampling process (sample design error)

Question 8

two types of systematic error

Answer 8

measurement error and sample design error

Question 9

scales

Answer 9

sets of symbols or numbers so constructed that the symbols or numbers can be assigned by a rule to the individuals (or their behaviors or attitudes) to whom the scale is applied
- this is about how you can treat your data (not objective)

Question 10

interval

Answer 10

no true zero

mode, median, mean

Question 11

ordinal

Answer 11

(mode, median) relative preferences (objects are greater or smaller)

Question 12

ratio

Answer 12

there now is a real zero

Question 13

How to assign numbers or symbols?

Answer 13

• In a way that the latent construct can be observed,

- information reflects what is needed

Question 14

Most popular scaling techniques

Answer 14

comparative scaling

and non-comparative scaling

Question 15

comparative scaling (most popular techniques)

Answer 15

• paired comparison scaling
• rank order scaling
• constant sum scale

Question 16

non-comparative scaling (most popular techniques)

Answer 16

• likert scale

- semantic differential scale

Question 17

Issues with non-comparative scales

Answer 17

• how many points on the scale? (Richness: not too few vs. discriminability: not too many=
• balanced or unbalanced (more options for left side or right side? vs. see options on both sides): use balanced, unless distribution is very skewed
• odd- or even-numbering scales (do you want to force preference?)
• force choice..

Question 18

reliability

Answer 18

degree to which measures are free from random error and, therefore, provide consistent data. The extent to which the survey responses are internally consistent

Question 19

How to test for reliability?

Answer 19

• test and retest
• equivalent form (do highly similar tools produce the same result?)
• internal consistency (do different parts of the tool produce the same results?) (Cronbach’s alpha)

Question 20

reliability vs. validity

Answer 20

Validity= are the measures appropriate and meaningful?
Reliability= Possible to repeat or corroborate the findings?

Question 21

corroborate

Answer 21

confirm or give support to

Question 22

how is zero interpreted

Answer 22

absence of success

Question 23

-5 interpreted

Answer 23

presence of failure

Question 24

Sampling methods

Answer 24

probability sampling

non-probability sampling

Question 25

probability sampling

Answer 25

systematic, stratified, cluster, simple random

Question 26

non probability sampling

Answer 26

convenience, snowball, judgment, quota