Assignment 5

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Feb 20, 2024

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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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