24309 Marketing Research
Review Lecture
2023
Question 1.i
The ANPM bookstore has recorded the amount spent by each member on its online gift-shop over the past few years. The bookstore has figures for each individual member for their individual spending amounts from last year compared to this year.
Q1. Part i.) What is the null and alternative hypothesis to test whether the average amount spent by a member last year is significantly less than the average amount spent by a member this year?
As a result, which is the correct null or alternative hypothesis from the following listed:
(a) Ho: (mu2022 – mu2023) <=0
(b) Ho: (mu2022 – mu2023) <0
(c) Ha: (mu2022 – mu2023) <=0
(d) Ha: (mu2022 – mu2023) <0
Question 1.ii
The ANPM bookstore has recorded the amount spent by each member on its online gift-shop over the past few years. The bookstore has figures for each individual member for their individual spending amounts from last year compared to this year.
Q1.Part ii) What would be the most appropriate way to conduct this test?
(a) ANOVA
(b) Independentsamples t-test
(c) Paired samples t-test
(d) Regression analysis
Question 2:
• A review is made in relation to waiting time for public hospitals. The following results were reported to compare waiting times across the four states
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ANOVA
|
|
Source of Variation
|
SS
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df
|
MS
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F
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P-value
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F crit
|
|
Between Groups
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18924.72
|
3
|
6308.241
|
7.20537
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9.32E-05
|
2.619655
|
|
Within Groups
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528796.9
|
604
|
875.4916
|
|
|
|
|
Total
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547721.6
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607
|
|
|
|
|
What can you conclude based on the Analysis of Variance output (with α=.05):
a) The states are significantly different in terms of the amount of variability in waiting times
b) The states are not significantly different in terms of the amount of variability in waiting time
c) The states are significantly different in terms of mean waiting times
d) The states are not significantly different in terms of mean waiting times
Question 3:
You have been asked to assess whether the claim amount (in dollars) made by an insurance client can be predicted on the basis of the clients age (in years) and their gender (dummy coded). You look at the table of coefficients to see whether these relationships hold, but see your regression output has produced the following table:
|
ANOVA
|
|
|
|
|
|
|
|
df
|
SS
|
MS
|
F
|
Significance F
|
|
Regression
|
4
|
28189329349
|
7047332337
|
863.6142
|
0
|
|
Residual
|
1480
|
12077212655
|
8160278.821
|
|
|
|
Total
|
1484
|
40266542003
|
|
|
|
Which is correct?
(a) The ANOVA confirms that age and gender both are significant predictors of claim amounts
(b) The ANOVA suggests that age and gender both are not significant predictors of claim amounts
(c) The ANOVA suggests that either age or gender or both variables are significant predictors of claim amounts
(d) The ANOVA suggests that only age is a significant predictor of claim amounts
Question 4:
|
Coefficients
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tandard Err
|
t Stat
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P-value
|
|
Intercept
|
104572
|
357.7437
|
292.3099
|
0
|
|
Advertising Spend
|
1.954033
|
0.063322
|
30.85887
|
7.3E-162
|
|
Our Price
|
-2.92143
|
0.063665
|
-45.8875
|
1.1E-286
|
|
Competitors Price
|
1.10515
|
0.06307
|
17.52258
|
1.29E-62
|
|
Interest Rates
|
37.5435
|
259.5
|
0.144676
|
0.884986
|
• Assume that sales is the dependent variable in the above regression output, a one unit increase in advertising spend will:
(a) Decrease sales by 1.95 units, a significant impact
(b) Decrease sales by 1.95 units, but this is not a significant impact
(c) Increase sales by 1.95 units, a significant impact
(d) Increase sales by 1.95 units, but this is not a significant impact
Question 5:
Data was collected on a person’s age and their drink preferences and this “observed” data is in the table below.
|
|
|
Coffee/tea
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Soft drink
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Other (milk etc.)
|
Total
|
|
Age
Groups
|
21-34
|
26
|
95
|
18
|
139
|
|
35-55
|
41
|
40
|
20
|
101
|
|
>55
|
24
|
13
|
32
|
69
|
|
|
Total
|
91
|
148
|
70
|
309
|
5a). What is the probability a person will drink soft drink, given they are more than 55 years of age?
(a) 4.2%
(b) 8.8%
(c) 13.0%
(d) 18.8%
Question 5:
Data was collected on a person’s age and their drink preferences and this
“observed” data is in the table below.
|
|
|
Coffee/tea
|
Soft drink
|
Other (milk etc.)
|
Total
|
|
Age
Groups
|
21-34
|
26
|
95
|
18
|
139
|
|
35-55
|
41
|
40
|
20
|
101
|
|
>55
|
24
|
13
|
32
|
69
|
|
|
Total
|
91
|
148
|
70
|
309
|
5b) If the events of age and drinking preference were independent events, what
would be the expected number of a person’s you would observe who drink soft drink and are more than 55 years of age?
(a) 13
(b) 18
(c) 33
(d) Unsure
Question 5:
Data was collected on a person’s age and their drink preferences and this “observed” data is in the first table below.
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• When you are asked about which market research technique to use, you
can simply provide a one to three word answer. There is no need to provide any further information or justification of your choice.
• For example, the following techniques could be a suitable response: Independent samples t-test
ANOVA
Paired samples t-test
Linear regression
Logistic regression
Multinomial regression Contingency analysis
Levene’s test of equal variances
Question 6. Part I:
Data was collected on a person’s age and their drink preferences. The
following conditional probabilities and marginal probabilities were formulated from the “observed” data: