ShopEasy Inc. is a specialty e-tailer that operates 87 catalogue websites on the Internet. Larson Brown, Sales Director, feels that thestyle (colour scheme, graphics, fonts, etc.) of a website may affect its sales. He chooses three levels of design style (neon, old world andsophisticated) and randomly assigns six catalogue websites to each design style. Analysis of Larson's data yielded the followingANOVA table:Source of VariationBetween GroupsWithin GroupsTotalSS19.432.85O 3.68O 19.45O 3.57df68102.33 2 34051.17Using a = 0.05, the critical F value isMS29177.67 15 1945.17897280 17F

The level of significance is .The ANOVA table is shown below:Source of VariationSSdfMSBetween…

Answered: ShopEasy Inc. is a specialty e-tailer…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The data below contains mileage, age, and selling price for a sample of 33 sedans. Price Mileage Age 16,998 35,000 17,599 16,000 15,998 42,000 15,998 62,000 14,998 60,000 11,599 88,000 12,599 11,599 102,000 12,998 109,000 4 58,000 14,998 27,000 3 15,998 32,000 3 3 4 7 5 9 8 6 3 Mileage Age 11,599 95,000 11,499 123,000 Price 14,599 54,000 10,599 16,998 40,000 20,998 11,599 9,599 7,000 12,599 70,000 68,000 12 80,000 13,599 86,000 11,599 92,000 120,000 . 8 8 5 4 0 9 6 5 7 10 Price Mileage Age 18,998 12,599 12,599 10,998 11,998 11,998 17,599 20,000 63,000 70,000 86,000 60,000 88,000 10 45,000 9,998 60,000 2 16,998 36,000 7 17,599 45,000 6 6 9,998 95,000 11 6 2 11 2 2 (a) Develop an estimated regression equation that predicts the selling price of a used Honda Accord given the mileage and age of the car. (Round your numerical values to two decimal places. Let x₁ represent mileage, x₂ represent age, and y represent the selling price.) y=20087.1 -0.04x₁ - 642.15x2 (b) Is multicollinearity an…
Students in a statistics class were asked, “About how many minutes do you typically exercise in aweek?” Responses from the men in the class were “180, 300, 60, 480, 0, 90, 300, 14, 600, 360, 120, 0,240”(a) Create a five-number summary of the men’s responses.(b) Identify any potential outliers.
The following data show the rankings of 11 states based on expenditure per student (ranked 1 highest to 11 lowest) and student-teacher ratio (ranked 1 lowest to 11 highest). State Expenditureper Student Student-TeacherRatio Arizona 9 10 Colorado 5 8 Florida 4 6 Idaho 2 11 Iowa 6 4 Louisiana 11 3 Massachusetts 1 1 Nebraska 7 2 North Dakota 8 7 South Dakota 10 5 Washington 3 9 (a) What is the rank correlation between expenditure per student and student-teacher ratio? (Round your answer to three decimal places.) rs = At the ? = 0.05 level, does there appear to be a relationship between expenditure per student and student-teacher ratio? State the null and alternative hypotheses. H0: ρs ≥ 0Ha: ρs < 0H0: ρs ≠ 0Ha: ρs = 0 H0: ρs = 0Ha: ρs ≠ 0H0: ρs ≤ 0Ha: ρs > 0H0: ρs > 0Ha: ρs = 0 Find the value of the test statistic. (Round your answer to two decimal places.) Find the p-value. (Round your answer to four decimal places.) p-value…
Online Sales Inc. has outsourced their customer service and wants to construct a control chart for determining whether the 10 customer service employees in the company they’ve hired are under control regarding the number of unsatisfied customers. Online Sales Inc. has sampled 100 service calls from last year for each customer service employee, with the following results: Customer Service Employee Unsatisfied customers 1 20 2 33 3 15 4 28 5 17 6 25 7 18 8 26 9 16 10 28 Analyze the data using a p-chart that would provide a 97% confidence interval, identifying the control limits and customer service employees, if any, that are outside the control limits. (use excel to show formulas used)
A real estate agency, located in a metropolitan area in the northeastern U.S., kept data on the various types of properties purchased in the area. Historically, 15% of purchases were for condominiums, 30% were for townhouses, 40% for single family homes, 10% for commercial properties and 5% for land. With changing demographics, the agency wondered if the current distribution matches the historical distribution. Recent data showed the following: Type of Property Condos Townhouses Homes Commercial Land Frequency 89 121 78 25 12 Based on the historical distribution, we would expect how many homes to be purchased? Question content area bottom Part 1 A. 130 B. 121 C. 129.95 D. 122.54 E. 100
3. Consider the following set of data, which represents a simple random sample of heights (in inches) of full-grown corn plants in Horseyetown, WI: (78.5, 88.8, 76.2, 73.0, 79.5, 66.9, 72.4, 86.6, 67.6, 73.5, 72.6, 72.6, 80.0, 69.1, 79.1, 73.9, 72.3, 83.3, 64.3, 69.1) Round your answers to 2 decimal places. A. Calculate the range. B. Calculate the sample mean. C. Calculate sample statistics to estimate the population standard deviation and variance of all full-grown corn plants in Horseyetown, WI.
In order to compare the real estate markets in Pittsburgh and Philadelphia, a realtor selected a random sample of 150 homes in the Pittsburgh area and 100 homes in the Philadelphia area. Shown below are dotplots showing the distribution of home price for the homes in these two cities.
The National Association of Home Builders provided data on the cost of the most popular home remodeling projects. Sample data on cost in thousands of dollars for two types of remodeling projects are as follows. Excel File: data 10-41.xlsx Kitchen 25.2 17.4 22.8 21.9 19.7 Master Bedroom 18.0 22.9 26.4 24.8 26.9 Kitchen 23.0 19.7 16.9 21.8 23.6 Master Bedroom 17.8 24.6 21.0 a. Develop a point estimate of the difference between the population mean remodeling costs of kitchens and master bedrooms. (Enter negative values as negative numbers. Report in thousands of dollars with no commas in your answer.) Point estimate = $ thousand b. Develop a 90% confidence interval for the difference between the two population means. (to 1 decimal and enter negative values as negative numbers) ) in thousands of dollars.
Is the mean, median, or mode most sensitive to the presence of outliers?
The dataset HollywoodMovies - 2e contains information on 970 movies that came out of Hollywood between 2007 and 2013. One of the variables is the budget (in millions of dollars) to make the movie. What would be the relevant parameter and statistic for this problem (think -- is this categorical or quantitative)? O u: The mean budget of all Hollywood Movies made between 2007 and 2013. O p: The average proportion of budgets of Hollywood Movies made between 2007 and 2013. T: The mean budget of all Hollywood Movies made between 2007 and 2013. Op: The proportion of Hollywood Movies made between 2007 and 2013.
The Wall Street Journal asked Concur Technologies, Inc., an expense management company, to examine data from 8.3 million expense reports to provide insights regarding business travel expenses. Their analysis of the data showed that New York was the most expensive city. The following table shows the average daily hotel room rate (*) and the average amount spent on entertainment (y) for a random sample of 9 of the 25 most-visited U.S. cities. These data lead to the estimated regression equation ŷ = 17.49 +1.0334x. For these data SSE = 1541.4. Click on the datafile logo to reference the data. Use Table 1 of Appendix B. DATA file City Boston Denver Nashville New Orleans Phoenix San Diego San Francisco San Jose Room Rate ($) 148 96 91 110 90 102 136 90 82 Tampa a. Predict the amount spent on entertainment for a particular city that has a daily room rate of $89 (to 2 decimals). $ Entertainment ($) 161 105 101 142 ***** b. Develop a 95% confidence interval for the mean amount spent on…
You are a manager for Company ABC and decide to compile data and analyze your employees’ level of satisifaction. You create a survey to ask each employee to rate their level of satisfaction working at Company ABC. Table 1 shows data of 15 people employees that responded to your survey. Each of the employees have the same job title: Sales Representative. The data set includes variables regarding an employee ID, gender, ethnicity, region, pay rate, employee satisfaction rating. Each employee was asked to rate their level of satisfaction working at Company ABC. A composite score from 0 (lowest) to 5 (highest) is shown as the data variable employee satisfaction. Table 1: Employee Data on 15 Sales Representatives at Company ABC

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