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### Question Description

Required:

• Calculate the descriptive statistics from the data and display in a table. Be sure to comment on the central tendency, variability and shape for Score, Pixel Density and Battery Score. How would you interpret the mean of dummy variables such as Fingerprint or Android? (1 Mark)
• Draw a graph that displays the distribution of review scores. Be sure to comment on the distribution.
• Create a box-and-whisker plot for the distribution of Battery Scores and describe the shape. Is there evidence of outliers in the data? (1 Mark)
• What is the likelihood that a phone will receive a rating higher than a 70 if the battery score measure is greater than a 70? Is the phone rating statistically independent of the battery score? Use a Contingency Table. (2 Marks)
• Estimate the 90% confidence interval for the population mean review score of phones. (1 Mark)
• Your supervisor recently stated that older mobiles typically had a battery score of around 50, but have recently been improving. Test his claim at the 5% level of significance. (1 Mark)
• Run a multiple linear regression using the data and show the output from Excel. Note: exclude the dummy variable “iOS” when running the multiple regression. Also, remember to tick all the graph options which may help you answer Part N. (1 Mark)
• Is the coefficient estimate for the Battery Score statistically different than zero at the 5% level of significance? Set-up the correct hypothesis test using the results found in the table in Part (G) using both the critical value and p-value approach. Interpret the coefficient estimate of the slope. (2 Marks)
• Interpret the remaining slope coefficient estimates. Discuss whether the signs are what you are expecting and explain your reasoning. (2 Marks)
• Interpret the value of the Adjusted R2. Is there a large difference between the R2 and the Adjusted R2? If so, what may explain the reasoning for this? (1/2 Mark)
• Is the overall model statistically significant at the 5% level of significance? Use the p-value approach.
• Based on the results of the regressions, what other factors would have influenced the review score? Provide a couple possible examples and indicate their predicted relationship with the review score if they were included. (1 Mark)
• Predict the average review score of a phone with a pixel density of 400 ppi, a battery score of 90 that has a fingerprint scanner and uses Windows if it is appropriate to do so. Show the predicted regression equation. (1 Mark)
• Do the results suggest that the data satisfy the assumptions of a linear regression (that is, Linearity, Normality of the Errors, and Homoscedasticity of Errors)? Show using residual plots, normal probability plots and/or histograms and Explain. (2 Marks)
• Would these results tell us anything about the average satisfaction that users have with the features of their phones? If not, describe a scenario in how you would construct a sample that reflects users’ satisfaction.

(1 Mark)

(1/2 Mark)

(1 Mark)

John_Best
School: UCLA

corrected. check attached file

ECON 1035 – BUSINESS STATISTICS 1
PROJECT
Due: 31 March 2017 at 7 pm (Singapore Time)

Instructions:
This is a group assignment with a minimum group size of two and a maximum group size of four. All group
members will receive marks according to the percentage of contribution mutually agreed by all group
members. All group members must be enrolled in the same lecture class.
The assignment must be provided in the form of a (brief) business report approximately 8-10 pages (including
the cover page). The structure of your (brief) business report must include 1] A Title, 2] An Executive
Summary, 3] An Introduction, and 4] Conclusions.
You must submit an electronic copy of your assignment in Blackboard. Hard copies will not be accepted. SHOW
YOUR WORK for calculation based questions.
This assignment requires the use of Microsoft Excel. If you have Windows, you will also need to use the Data
Analysis ToolPak. If you have a Mac with Excel 2011, you will need to use StatPlus:MAC LE.

Group Members
First name

Last name

Student ID

% of contribution

Note: If all contributed equally, please indicate % of contribution for each group member as 100%.
Otherwise indicate correct % of contribution made by each group member.
Lecturer
Lecture day and time

Problem Description:
Worldwide sales of mobile phones are a multi-billion dollar business. There is severe competition among the
major manufacturers to attract higher sales and greater market shares. To achieve this, companies compete with
each other on prices. However, for many customers, price may not be as important as the perceived quality of the
phone, especially as many phones are offered at “zero price” under various plans and contracts from service
providers.
Decision makers and markets at mobile-phone manufacturers would like to know what features of a mobile phone
are important to consumers. This would be especially important in helping to design effective marketing and

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Anonymous
awesome work thanks

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