EXAM 2

Question 1

What are the different types of measures?

Answer 1

1) Nominal
2) Ordinal
3) Interval
4) Ratio

Question 2

Nominal

Answer 2

Nominal - scales label objects (responses cannot be differentiated) EX:1 Male, 2 female, 3 prefer not to say

Question 3

Ordinal

Answer 3

Ordinal - relative size differences between objects (responses ranked/scaled)
EX: How many influencers do you follow? 1= 1-10 influencers, 2=11-30 influencers, 3=31-50 influ.

Question 4

Interval

Answer 4

Interval: (no true 0 origin)
EX: 1=strongly disagree, 2= somewhat disagree, 3= neither agree/ disagree, 4= somewhat agree

Question 5

Ratio

Answer 5

Ratio: (true 0 origin)
EX: how many times have you spent $20 or more on an influencer-inspired purchase 0, 1, 2, 3, 4

Question 6

Composite Measure

Answer 6

combination of two or more surveys measuring the specific construct
- semantic differential
- Likert
EX rate agreement to the following statements

Question 7

Be able to calculate the composite measure

Answer 7

The average (add all numbers up and divide by those numbers; mean)

Question 8

What is scale reliability?

Answer 8

The degree to which an instrument consistently measures a construct across items
Indicator of a measure’s internal consistency

Question 9

Be able to interpret the internal consistency based on the Cronbach’s alpha table.

Answer 9

• Represents a measure of homogeneity/ extent to which an indicator converges on a common meaning
• Measured by correlating scopes of items making up a scale
• Cronbach’s alpha= most commonly applied estimate of multiple item’s scale reliability
  >0.9 - excellent
  >0.8 - good
  >0.7 - acceptable
  >0.6 - questionable
  >0.5 - poor

Question 10

What is descriptive analysis? What are descriptive statistics?

Answer 10

Descriptive analysis: used by marketing researchers to describe sample dataset, reveals general patterns of responses
Descriptive statistics: mean, median, mode, frequency, variability, range, standard deviation

Question 11

What is inferential analysis?

Answer 11

Use statistical procedures to generalize the results of the sample to the target population it represents

Question 12

What is a null or alternative hypothesis?

Answer 12

Hypothesizes the result of an alternative answer (Gen Z consumers will not buy a product promoted by a social media influencer.)

Question 13

What are testing differences? What is a testing relationship?

Answer 13

Testing differences: on outcome variable between two or more groups (EX: do consumers behave differently on certain outcomes between 2 or more market segments). Determines the degree to which real and generalizable differences exist in the population

Question 14

Be able to interpret t-test results.

Answer 14

• comparing the differences between 2 groups (ex. female and male) and their significant difference from 0
• Look at the MEAN when seeing which group is higher in the outcome variable
• when looking at the TWO TAILED TEST: if the p-value is less than 0.5 it means our null hypothesis is rejected

Question 15

Be able to interpret the ANOVA table,

Answer 15

• used when comparing the means of
  three or more groups
• ANOVA will “signal” when at least one pair of means has a statistically
  significant difference
• when looking at the AVERAGE you can see how much each variable differs from one another, dependent on how far apart they are spread
• when looking at P VALUE you can see if the p-value is above 0.05 then the null hypothesis is accepted

Question 16

Be able to interpret the regression statistics table, and coefficient table from the regression results.

Answer 16

Regression= look at r squared (interprets % of variance in dependent variable)

look at F and significance F = P value of F statistic and shows weather independent variable significantly predicts dependent variable

coefficients= largest amounts (- or +) are most signifiant relationships

P value= which ones are significant P> 0.05 null hypothesis

Question 17

What is a testing relationship?

Answer 17

Tests relationship between 2 or more variables, and how they’re related. Insight on multiple relationships between variables.
relationship must be meaningful and actionable

Question 18

Be able to propose null hypothesis regarding testing differences or testing relationship.

Answer 18

Testing differences: Light users, regular users, and heavy users of social media in Gen Z consumers do not differ from their purchase intention on the product promoted by a social media influencer.

Testing relationships: The expertise of a social media influencer is not related to (will not affect) Gen Z consumers’ purchase intention on the product promoted by this influencer.

Question 19

What are the steps in hypothesis testing process?

Answer 19

1) Null hypothesis related to research question
2) Select appropriate statistical test (t-test, anova, regression)
3) Specify significance level (0.05)
4) Run test and get P value
5) Interpret P value and compare to significance level (0.05)
6) P value > 0.05 null hypothesis
rejected = sig difference

Question 20

Be able to select the right statistical tests (e.g., t-test, ANOVA test, regression) given the scenario.

Answer 20

T-test = difference between two groups
ANOVA = test of variance = three or more groups
Regression = tests relationship between single dependent variable and multiple independent variables