Case uitwerking
OE106 Marketing research SPSS
- Instelling
- Hogeschool InHolland (InHolland)
Dit is het uitgewerkte tentamen van OE106 Marketing Research met de SPSS berekeningen erbij. Het vak is met een 7 afgerond.
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OE106 research skillsfor marketeers
INHOLLAND ALKMAAR
| 18-04-2022
,Foreword
In front of you is the exam for OE106 Research Skills for Marketeers. This exam was assigned by the
Hogeschool Inholland Alkmaar to be hand in on 19-04-2022 before 8:30 AM. I have put a lot of time
into this document and hope that is seen throughout. I would like to thank my teacher Hugo Booms
for his classes, assignments and extras he put on Moodle for me so that I am as best prepared as I
can. I would also like to thank my friends and family for supporting me during the time of making this
exam.
,Inhoud
Foreword................................................................................................................................................1
Introduction............................................................................................................................................3
1 Exploring the data................................................................................................................................4
Do the customers who receive a newsletter generate a higher revenue than the others, on
average?.............................................................................................................................................4
Is there a difference in average age depending on the size of the house hold a customer is part of?
............................................................................................................................................................4
Can the monthly revenue be regarded as normally distributed?.......................................................5
The average age of customers in 2018 was 44,0 years. Has this number significantly changed now?
(In what direction?)............................................................................................................................6
Do females on the whole come from larger households than males? (Disregard the persons of
undisclosed gender.)..........................................................................................................................6
Is the distribution of urbanization grades the same for all packages or are there one or several on
the whole higher or lower? (The variable ‘urbanization’ is not metric here.)....................................7
Is there a relationship between (monthly) revenue and age? What kind of relationship? How
strong is it?.........................................................................................................................................8
Is there a relationship between urbanization and age? If so, what kind of relationship, how strong
is it?....................................................................................................................................................9
Is the distribution of customers over the regions (provinces) equal to that of the general
population?........................................................................................................................................9
Part B: Logistic regression.....................................................................................................................11
1. Some variables are unusable for this purpose. Explain why. Do not use them in the rest of this
assignment.......................................................................................................................................11
2. Check the significance of the relationship of all variables (to be used) with ‘active’ on a one-to-
one basis. Consider ‘urbanization’ to be non-metric as before. ‘Household size’ is best considered
nominal here, because it has only three categories.........................................................................11
3. Devise a model, based on the variables measured here, to predict whether someone is active not
(strictly speaking: devise a model that assigns a probability of someone being active to the values of a
set a suitable variables measured for that person). Show the intermediary stages.............................24
3. Linear regression..............................................................................................................................31
4 Hierarchical cluster analysis...............................................................................................................43
2. How many cases are attributed to each of the clusters? Show the distribution of the variables
over the clusters (the variables both used in clustering and not used in clustering, but of course not
the individual data like customer number.)......................................................................................45
Characterize the clusters..................................................................................................................55
,Introduction
The exam can be split up into 4 different assignments, they are as followed:
Assignment 1 is about statistical testing, in here 10 different statistical have been solved according to
the right functions.
Assignment 2 where the focus is on binary logistical regression. In this assignment I was supposed to
recognise variables and later on use and apply them in a model.
Assignment 3 was kind of the same as assignment 2 however this time about linear regression
instead of logistical regression.
Assignment 4 was about cluster analysis, in which I had to make a Dendogram, boxplots and also
crosstabulations. After making these assignments I had to go by every variable to tell what they were
showing.
, 1 Exploring the data
Do the customers who receive a newsletter generate a higher
revenue than the others, on average?
H0: Customers that receive a newsletter generate a higher revenue than others on average.
The X variable in this case is revenue which is a numeric variable. The y variable is abou if the
customers receive a newsletter which is a binary variable because it has 2 outcomes. This is why we
use the Independence sample t test.
Out of the data above we can see that people who receive a newsletter have a higher mean of
generated revenue than people who do not receive a newsletter. Because 58,91 is higher than 51,93.
The second test that was performed showed the following: P-value= 0,367 > 0,05: equal variances
are assumed. We now use the first row. Sig = <0,01 > 0,05. This shows that the generated revenue is
significantly higher from the customers that receive a newsletters than from customers that do not.
Is there a difference in average age depending on the size of the
house hold a customer is part of?
HO: There a difference in average age depending on the size of the house hold a customer is part of.
The X variable this time is age which is numeric. The Y variable is size of household which is nominal.
For that reason the one way ANOVA will be used.
The P-value is <,001 which means that the average age of at least one size of household differs from
the average age of another size of household.
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