Model Score Pixel DensitBattery ScoFingerprintAndroid Samsung Galaxy S7 90 577 80 1 Samsung Galaxy S6 85 577 61 1 HTC 10 79 564 66 1 Samsung Galaxy S7 Edge 100 534 98 1 LG G4 80 534 42 0 Samsung Galaxy Note Edge 53 524 56 0 Moto X Style 78 520 51 0 Microsoft Lumia 950 XL 69 518 62 0 Galaxy S6 Edge+ 63 518 71 1 Oppo R7 67 445 51 0 HTC One M8 82 441 65 0 HTC One M9 72 441 50 0 Nokia Lumia 930 60 441 22 0 Google Nexus 5X 71 432 48 1 Sony Xperia Z5 78 424 73 1 Sony Xperia Z3 73 424 73 0 Apple iPhone 6S+ 63 401 73 1 Huawei Mate 8 86 368 103 1 Apple iPhone 6S 86 326 50 1 Apple iPhone 6 71 326 37 1 Nokia Lumia 735 47 312 35 0 Microsoft Lumia 650 69 297 55 0 Sony Xperia M4 Aqua 67 294 69 0 Nokia Lumia 830 56 294 44 0 Xiaomi Mi Note 66 267 31 0 Nokia Lumia 1320 51 245 51 0 Motorola Moto E 68 245 70 0 Microsoft Lumia 532 63 233 43 0 Vodafone Smart 4 Mini 40 233 16 0 1 1 1 1 1 1 1 0 1 1 1 1 0 1 1 1 0 1 0 0 0 0 1 0 1 0 1 0 1 Windows iOS 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 1 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 Cover sheet for submission of work for assessment School: Economics, Finance and Marketing Program Name Course/unit name Business Statistics 1 Due Date 16 October 2016 Program Code Course/unit code ECON1030 Name of Lecturer Tutor's Name Tutorial Day/Time STUDENT/S Family name Given name Student number (1) (2) (3) DECLARATION AND STATEMENT OF AUTHORSHIP 1. 2. 3. 4. 5. 6. I/we hold a copy of this work which can be produced if the original is lost/damaged. This work is my/our original work and no part of it has been copied from any other student's work or from any other source except where due acknowledgement is made. No part of this work has been written for me/us by any other person except where such collaboration has been authorized by the lecturer/teacher concerned. I/we have not previously submitted this work for this or any other course/unit. I/we give permission for this work to be reproduced, communicated, compared and archived for the purpose of detecting plagiarism. I/we give permission for a copy of my/our marked work to be retained by the school for review and comparison, including review by external examiners. I/we understand that: 7. 8. Plagiarism is the presentation of the work, idea or creation of another person as though it is my/our own. It is a form of cheating and is a very serious academic offence that may lead to exclusion from the University. Plagiarised material can be drawn from, and presented in, written, graphic and visual form, including electronic data and oral presentations. Plagiarism occurs when the origin of the material used is not appropriately cited. Plagiarism includes the act of assisting or allowing another person to plagiarise or to copy my/our work. Student signature/s I/we declare that I/we have read and understood the declaration and statement of authorship. (1) (2) (3) Further information relating to the penalties for plagiarism, which range from a notation on your student file to expulsion from the University, is contained in Regulation 6.1.1 Student Discipline and the Plagiarism Policy which are available on the Policies and Procedures website at www.rmit.edu.au/policies. ECON 1030 - BUSINESS STATISTICS 1 PROJECT (TUESDAY) Due: 16 October at 23:59 Instructions: This is a project where you can work alone or with two other students (a maximum group size of three). All group members will receive the same marks for the assignment. All group members must be enrolled in the same tutorial. The assignment must be provided in the form of a (brief) business report approximately 8-14 pages. 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. 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 advertising campaigns. A review site reviewed 29 recent models of mobile phones and gave a score out of 100 points. Several characteristics of the phone including pixel density, battery life, whether the phone had a fingerprint scanner along with the operating system were included in the table. You will use descriptive statistics, inferential statistics and your knowledge of multiple linear regression to complete this task. Score (Dependent Variable) and several characteristics (Independent Variables) are given in the Excel file: Tuesday.xlsx. Here is a table describing the variables in the data set: Variable Score Pixel Density (ppi) Battery Scores Fingerprint Android Windows iOS Definition Review of phone in points between 0 and 100 Number of pixels per square inch in the screen The number of hours that the phone lasts based on several real-world scenarios including video-use, web browsing and phone calls. A dummy variable to indicate if the phone has a fingerprint scanner Dummy variable to indicate that the phone uses a version of Android Dummy variable to indicate that the phone uses a mobile version of Windows Dummy variable to indicate that the phone uses iOS Required: A. 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) B. Draw a graph that displays the distribution of review scores. Be sure to comment on the distribution. (1 Mark) C. 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) D. 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) E. Estimate the 90% confidence interval for the population mean review score of phones. (1 Mark) F. 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) G. Run a multiple linear regression using the data and show the output from Excel. Exclude the dummy variable \"iOS\" from the regression results. (1 Mark) H. 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) I. Interpret the remaining slope coefficient estimates. Discuss whether the signs are what you are expecting and explain your reasoning. (2 Marks) J. Interpret the value of the Adjusted R 2. Is there a large difference between the R 2 and the Adjusted R2? If so, what may explain the reasoning for this? (1/2 Mark) K. Is the overall model statistically significant at the 5% level of significance? Use the p-value approach. (1/2 Mark) L. 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) M. 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) N. Do the results suggest that the data satisfy the assumptions of a linear regression: Linearity, Normality of the Errors, and Homoscedasticity of Errors? Show using scatter diagrams, normal probability plots and/or histograms and Explain. (2 Marks) O. 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 to survey users. (1 Mark) Allocation of Marks: Professional Business Report Part A Part B Part C Part D Part E Part F Part G Part H Part I Part J Part K Part L Part M Part N Part O Total: 2 Marks 1 Mark 1 Mark 1 Mark 2 Marks 1 Mark 1 Mark 1 Mark 2 Marks 2 Marks 1/2 Mark 1/2 Mark 1 Mark 1 Mark 2 Marks 1 Mark 20 Marks