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Marketing Research
MAR 4613 Assignment 5
50 Total Points
Due: Sunday, November 19 @ 11:59 PM
Name(s): Gabriela Blazquez
Please read the case on the following pages and answer the corresponding questions.
In this assignment, you are going examine the factors that influence a consumer’s likelihood to
view a YouTube video by a vlogger. The data was collected from 276 American adults using an
online survey developed on Qualtrics. Participants in the survey were shown one short video by a
vlogger and were asked to respond to a few questions about the vlogger, and the content itself.
The videos seen by different participants were not necessarily the same video or by the same
vlogger.
The data collector has shared results for some of the data that was collected. There are 6 different
variables in this dataset as follows:
1.
Views – How likely the consumers are to view other videos by the vlogger
2.
ProfSetup – The extent to which the vlogger used a professional vlogging setup visible in
the video (e.g., professional cameras, microphones, background wall and props)
3.
Distinct – How different or similar did consumers find this vlogger versus others that
they know of
4.
DiverseTopic – How diverse or specialized is the content developed by the vlogger
5.
MaxLearning – The extent to which consumers think they can get maximum learning on
diverse topics from the YouTube channel of this particular vlogger only
6.
ContentQual – The extent to which consumers found the content by the vlogger of good
quality
Using the dataset and the description of the variables above, you are going to complete the
following tasks.
Section 1: In this part of the assignment, you are tasked with determining whether having a professional setup (ProfSetup) is related to views received on a video on YouTube (Views). For this, while collecting data from participants, your team show a YouTube video to participants and then asked the following questions:
“ProfSetup”
= To what extent does the YouTube video display a typical professional vlogging setup? (1 = Extremely low, 7 = Extremely high)
“Views”
= How likely are you to view other videos by this vlogger? (1 = Very unlikely,
7 = Very likely)
A.
Write down the null and alternate hypothesis for this correlation analysis
a.
Null Hypothesis: There is no correlation between the likelihood of viewers watching more videos by the vlogger (Views) and how visible the professional vlogging setup is (ProfSetup).
b.
Alternate Hypothesis : There is a significant correlation between how visible the professional vlogging setup is (ProfSetup) and the likelihood that viewers will watch other videos by the vlogger (Views).
B.
Using the variables “Views” and “ProfSetup” determine the Pearson correlation coefficient. Please provide the output from SPSS/Excel and explain what is relationship between the two variables.
View
ProfSetu
p
View
1
ProfSetu
p
-0.228138821
1
There is a weak inverse correlation between Views and ProfSetup meaning that there is a slightly
decreased likelihood that a viewer will watch other videos by the vlogger if the vlogger has had a
higher frequency of visible equipment in their videos.
Section 2
: In this section you will assess whether people are more likely to view videos from a YouTuber
who is very distinct from other YouTubers, or one that is very similar to others. In your data collection exercise, you had asked participants to indicate about the level of
similarity the vlogger in the video had compared to other vloggers participants know of.
“Distinct”
= To what extent is this vlogger similar or distinct from other vloggers on
YouTube that you follow? (1 = Extremely similar, 7 = Extremely distinct)
“Views”
= How likely are you to view other videos by this vlogger? (1 = Very unlikely, 7 = Very likely)
A.
Write down the null and alternate hypothesis for this regression analysis
a.
Null Hypothesis: There is no correlation between the likelihood of viewers watching more videos by the vlogger (Views) and how different or similar the vlogger from other vloggers they know of (Distinct).
b.
Alternate Hypothesis : There is a significant correlation between the likelihood that viewers will watch other videos by the vlogger (Views) and how they perceive the vlogger being distinct from other vloggers they know.
B.
Run a bivariate/linear regression analysis on SPSS/Excel to assess whether “Distinct”
predicts “Views”. Please provide the three output tables (Model Summary, ANOVA and
Coefficients) from SPSS/Excel in the write-up SUMMARY OUTPUT
Regression Statistics
Multiple R
0.03074
R Square
0.00094
Adjusted R Square
-0.00270
Standard Error
0.88521
Observations
276
ANOVA
df
SS
MS
F
Significance F
Regression
1
0.203
0.203
0.259
0.611
Residual
274
214.706
0.784
Total
275
214.909
Coefficients
Standard
Error
t Stat
P-value
Lower 95%
Upper 95%
Lower
95.0%
Upper
95.0%
Intercept
4.094
0.158
25.990
0.000
3.783
4.404
3.783
4.404
Distinct
-0.016
0.031
-0.509
0.611
-0.077
0.045
-0.077
0.045
C.
Using the coefficients table, interpret the results and explain what it means. In your
explanation, be very clear in the wording such that a person who has never conducted
regression analysis, is easily able to understand the results.
Hint: if you do not recall how to interpret the results, please refer to the slides on chapter
12
Summary Output
Since both multiple R and R Square values are low, that would indicate that there is a
weak relationship between the likelihood that a viewer will watch other videos by the
vlogger and how distinct that vlogger is, as well as the fact that there is a low amount of
variance in viewership vs the distinctness of the vlogger.
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