SHOW YOUR WORK IN THE SPACES PROVIDED BELOW FOR FULL CREDIT. a. Based on a sample of 1535 Internet users, a University of Southern California sponsored study reported Internet users followed an average of 9.9 companies on social network sites such as LinkedIn. State the population for this survey, the statistics, and some likely values from the population distribution.
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SHOW YOUR WORK IN THE SPACES PROVIDED BELOW FOR FULL CREDIT.
a. Based on a sample of 1535 Internet users, a University of Southern California sponsored study reported Internet users followed an average of 9.9 companies on social network sites such as LinkedIn. State the population for this survey, the statistics, and some likely values from the population distribution.
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- Consider again the example introduced in Section 7.5 of a credit card company that has a database of information provided by its customers when they apply for credit cards. An analyst has created a multiple regression model for which the dependent variable in the model is credit card charges accrued by a customer in the data set over the past year (y), and the independent variables are the customers annual household income (x1), number of members of the household (x2), and number of years of post-high school education (x3). Figure 7.23 provides Excel output for a multiple regression model estimated using a data set the company created. a. Estimate the corresponding simple linear regression with the customers annual household income as the independent variable and credit card charges accrued by a customer over the past year as the dependent variable. Interpret the estimated relationship between the customers annual household income and credit card charges accrued over the past year. How much variation in credit card charges accrued by a customer over the past year is explained by this simple linear regression model? b. Estimate the corresponding simple linear regression with the number of members in the customers household as the independent variable and credit card charges accrued by a customer over the past year as the dependent variable. Interpret the estimated relationship between the number of members in the customers household and credit card charges accrued over the past year. How much variation in credit card charges accrued by a customer over the past year is explained by this simple linear regression model? c. Estimate the corresponding simple linear regression with the customers number of years of posthigh school education as the independent variable and credit card charges accrued by a customer over the past year as the dependent variable. Interpret the estimated relationship between the customers number of years of posthigh school education and credit card charges accrued over the past year. How much variation in credit card charges accrued by a customer over the past year is explained by this simple linear regression model? d. Recall the multiple regression in Figure 7.23 with credit card charges accrued by a customer over the past year as the dependent variable and customers annual household income (x1), number of members of the household (x2), and number of years of post-high school education (x3) as the independent variables. Do the estimated slopes differ substantially from the corresponding slopes that were estimated using simple linear regression in parts (a), (b), and (c)? What does this tell you about multicollinearity in the multiple regression model in Figure 7.23? e. Add the coefficients of determination for the simple linear regression in parts (a), (b), and (c), and compare the result to the coefficient of determination for the multiple regression model in Figure 7.23. What does this tell you about multicollinearity in the multiple regression model in Figure 7.23? f. Add age, a dummy variable for sex, and a dummy variable for whether a customer has exceeded his or her credit limit in the past 12 months as independent variables to the multiple regression model in Figure 7.23. Code the dummy variable for sex as 1 if the customer is female and 0 if male, and code the dummy variable for whether a customer has exceeded his or her credit limit in the past 12 months as 1 if the customer has exceeded his or her credit limit in the past 12 months and 0 otherwise. Do these variables substantially improve the fit of your model?The Pew Research Center Internet Project conducted a survey of 857 Internet users. This survey provided a variety of statistics on them. The sample survey showed that 90% of respondents said the Internet has been a good thing for them personally. Develop a 95% confidence interval for the proportion of respondents who say the Internet has been a good thing for them personally. The sample survey showed that 67% of Internet users said the Internet has generally strengthened their relationship with family and friends. Develop a 95% confidence interval for the proportion of respondents who say the Internet has strengthened their relationship with family and friends. Fifty-six percent of Internet users have seen an online group come together to help a person or community solve a problem, whereas only 25% have left an online group because of unpleasant interaction. Develop a 95% confidence interval for the proportion of Internet users who say online groups have helped solve a problem. Compare the margin of error for the interval estimates in parts (a), (b), and (c). How is the margin of error related to the sample proportion?A marketing professor at Givens College is interested in the relationship between hours spent studying and total points earned in a course. Data collected on 156 students who took the course last semester are provided in the tile MktHrsPts. Develop a scatter chart for these data. What does the scatter chart indicate about the relationship between total points earned and hours spent studying? Develop an estimated regression equation showing how total points earned is related to hours spent studying. What is the estimated regression model? Test whether each of the regression parameters β0 and β1 is equal to zero at a 0.01 level of significance. What are the correct interpretations of the estimated regression parameters? Are these interpretations reasonable? How much of the variation in the sample values of total point earned does the model you estimated in part (b) explain? Mark Sweeney spent 95 hours studying. Use the regression model you estimated in part (b) to predict the total points Mark earned.
- The Human Resources Manager for Optilytics LLC is evaluating applications for the position of Senior Data Scientist. The file OptilyticsLLC presents summary data of the applicants for the position. a. Use a PivotTable in Excel to create a joint probability table showing the probabilities associated with a randomly selected applicants sex and highest degree achieved. Use this joint probability table to answer the questions below. b. What are the marginal probabilities? What do they tell you about the probabilities associated with the sex of applicants and highest degree completed by applicants? c. If the applicant is female, what is the probability that the highest degree completed by the applicant is a PhD? d. If the highest degree completed by the applicant is a bachelors degree, what is the probability that the applicant is male? e. What is the probability that a randomly selected applicant will be a male whose highest completed degree is a PhD?In a recent report, the top five most-visited English-language web sites were google.com (GOOG), facebook.com (FB), youtube.com (YT), yahoo.com (YAH), and wikipedia.com (WIKI). The most-visited web sites for a sample of 50 Internet users are shown in the following table: a. Are these data categorical or quantitative? b. Provide frequency and percent frequency distributions. c. On the basis of the sample, which web site is most frequently the most-often-visited web site for Internet users? Which is second?assume that you are planning to purchase a new laptop for school, work, and home use. go to the website of two computer manufacturers and make a selection. complete the following items and questions. compare the following items for your selections in their financial statements. revenues for products, revenues for services, cost of goods sold, accounts receivable, inventories, accounts payable, and research ad development. what are some factors that can impact the gross profit of a merchandise company? one item that can help investors understand the relationship between net sales and net profits is the gross profit rates. find the financial information needed to calculate the gross profit rate for your two selected companies.
- Consider the following survey results regarding smartphone ownership by age: a. Construct a stacked-column chart to display the survey data on type of cell-phone ownership. Use Age Category as the variable on the horizontal axis. b. Construct a clustered column chart to display the survey data. Use Age Category as the variable on the horizontal axis. c. What can you infer about the relationship between age and smartphone ownership from the column charts in parts a and b? Which column chart (stacked or clustered) is best for interpreting this relationship? Why?As was discussed in the Analytics in Action from Chapter 2, the U.S. Census Bureau is a leading source of quantitative data related to the people and economy of the United States. The crosstabulation below represents the number of households (1,000s) and the household income by the highest level of education for the head of household (U.S. Census Bureau web site, 2013). Use this crosstabulation to answer the following questions. a. Develop a joint probability table. b. What is the probability the head of one of these households has a masters degree or higher education? c. What is the probability a household is headed by someone with a high school diploma earning 100,000 or more? d. What is the probability one of these households has an income below 25,000? e. What is the probability a household is headed by someone with a bachelors degree earning less than 25,000? f. Are household income and educational level independent?The president of the American Insurance Institute wants to compare the yearly costs of auto insurance offered by two leading companies. He selects a sample of 15 families, some with only a single insured driver, others with several teenage drivers, and pays each family a stipend to contact the two companies and ask for a price quote. To make the data comparable, certain features, such as the deductible amount and limits of liability, are standardized. The data for the sample of families and their two insurance quotes are reported in the table. Family Becker Berry Cobb Debuck Midstates Car Insurance $ 2,090 Gecko Mutual Insurance $ 1,610 1,683 1,247 1,402 2,327 1,830 1,367 DuBrul 930 1,461 Eckroate 697 1,789 German 1,741 1,621 Glasson 1,129 1,914 King 1,018 1,956 Kucic 1,881 1,772 Meredith 1,571 1,375 Obeid 874 1,527 Price 1,579 1,767 Phillips 1,577 Tresize 860 1,636 1,188 Click here for the Excel Data File At the 0.10 significance level, can we conclude that there is a difference in…
- Consumer complaints are frequently reported to the Better Business Bureau. Industries with the most complaints to the Better Business Bureau are often banks, cable and satellite television companies, collection agencies, cellular phone providers, and new car dealerships. The results for a sample of 200 complaints are in the file BBB. a. Show the frequency and percent frequency of complaints by industry. b. Which industry had the highest number of complaints? c. Comment on the percentage frequency distribution for complaints.Brian just completed a Client Needs Assessement and his client confirmed that she will requre profitability tracking, and need to create budgets and purchase orders in her accounting solution. What is the mimimum Quick Books online version suitable for Brian's client?A sociologist was hired by a large city hospital to investigate the relationship between the number of unauthorized days that employees are absent per year and the distance (miles) between home and work for the employees. A sample of 10 employees was chosen, and the following data were collected. a. Develop a scatter chart for these data. Does a linear relationship appear reasonable? Explain. b. Use the data to develop an estimated regression equation that could be used to predict the number of days absent given the distance to work. What is the estimated regression model? c. What is the 99% confidence interval for the regression parameter 1? Based on this interval, what conclusion can you make about the hypotheses that the regression parameter 1 is equal to zero? d. What is the 99% confidence interval for the regression parameter 0? Based on this interval, what conclusion can you make about the hypotheses that the regression parameter 0 is equal to zero? e. How much of the variation in the sample values of number of days absent does the model you estimated in part (b) explain?
