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business analytics data

Questions and Answers of Business Analytics Data

Explain systematic, stratified, and cluster sampling, and sampling from a continuous process.
Explain the importance of unbiased estimators.
Describe the difference between sampling error and nonsampling error.
Explain how the average, standard deviation, and distribution of means of samples changes as the sample size increases.
Define the sampling distribution of the mean.
Calculate the standard error of the mean.
Explain the practical importance of the central limit theorem.
Use the standard error in probability calculations.
Explain how an interval estimate differs from a point estimate.
Define and give examples of confidence intervals.
Calculate confidence intervals for population means and proportions using the formulas in the chapter and the appropriate Excel functions.
Explain how confidence intervals change as the level of confidence increases or decreases.
Describe the difference between the t-distribution and the normal distribution.
Use confidence intervals to draw conclusions about population parameters.
Compute a prediction interval and explain how it differs from a confidence interval.
Compute sample sizes needed to ensure a confidence interval for means and proportions with a specified margin of error.
Uncle’s Pizza is doing good business in Delhi due to its prompt home delivery system. It guarantees that the pizza will be delivered within 30 minutes from the time order was placed or the order is
A soft drink bottle filling machine is known to have a mean of 200 ml and a standard variation of 10 ml.The quality control manager took a random sample of the filled bottles and found the sample
Find the standard deviation of the total assets held by the bank in the Excel file Credit Risk Data.a. Treating the records in the database as a population, use your sample in Problem 2 and compute
The monthly sales of a mobile phone shop have been distributed with a standard deviation of $900. A statistical study of sales in the last nine months has found a confidence interval for the mean of
A random sample of 100 teenagers was surveyed, and the mean number of songs that they had downloaded from the iTunes store in the past month was 9.4 with the results considered accurate is within 1.4
A study of nonfatal occupational injuries in the United States found that about 31% of all injuries in the service sector involved the back. The National Institute for Occupational Safety and
After regular complaints of tire blowouts on the Yamuna Expressway, in an automotive test conducted by the authorities, the average tire pressure in a sample of 62 tires was found to be 24 pounds per
A music company wants to know how the illegal downloading of music online affects CD sales. 600 families are randomly chosen from various parts of a particular country and the number of songs that
What proportion of customers rate the company with“top box” survey responses (which is defined as scale levels 4 and 5) on quality, ease of use, price, and service in the 2012 Customer Survey
What estimates, with reasonable assurance, can PLE give customers for response times to customer service calls?
Engineering has collected data on alternative process costs for building transmissions in the worksheet Transmission Costs. Can you determine whether one of the proposed processes is better than the
What would be a confidence interval for an additional sample of mower test performance as in the worksheet Mower Test?
For the data in the worksheet Blade Weight, what is the sampling distribution of the mean, the overall mean, and the standard error of the mean? Is a normal distribution an appropriate assumption for
How many blade weights must be measured to find a 95% confidence interval for the mean blade weight with a sampling error of at most 0.2? What if the sampling error is specified as 0.1?
Explain the difference between the null and alternative hypotheses.
List the steps in the hypothesis-testing procedure.
State the proper forms of hypotheses for one-sample hypothesis tests.
Correctly formulate hypotheses.
List the four possible outcome results from a hypothesis test.
Explain the difference between Type I and Type II errors.
State how to increase the power of a test.
Choose the proper test statistic for hypothesis tests involving means and proportions.
Explain how to draw a conclusion for one- and twotailed hypothesis tests.
Use p-values to draw conclusions about hypothesis tests.
State the proper forms of hypotheses for two-sample hypothesis tests.
Select and use Excel Analysis Toolpak procedures for two-sample hypothesis tests.
Explain the purpose of analysis of variance.
Use the Excel ANOVA tool to conduct an analysis of variance test.
List the assumptions of ANOVA.
Conduct and interpret the results of a chi-square test for independence.
A company is considering two different campaigns, A and B, for the promotion of their product. Two tests are conducted in two market areas with identical consumer characteristics, and in a random
A management institute checked the past records of applicants and the mean score calculated was 350. The administration is interested to know whether the quality of new applicants has changed or not.
Metropolitan Press hypothesizes that the average life of its largest Web press is 14,500 hours. They know that the standard deviation of press life is 2,100 hours. From a sample of 25 presses, the
Ice Cream Manufacture is to produce a new ice cream flavor. The company‘s marketing research department surveyed 6,000 families and 335 of them showed interest in purchasing the new flavor. A
The manager of a store claims that 60% of the shoppers entering the store leave without making a purchase. Out of a sample of 50, it is found that 35 shoppers left without buying. Is the result
A sample of 400 athletes is found to have mean height of 171.38 cm. Can we call it a sample from a large population of mean height 171.17 and standard deviation of 3.30 cm?
A sample size of 22 with a mean of 8 and a standard deviation of 12.5 test the hypothesis that the value of the population mean is 70 against the assumption that it is more than 70. Use the 0.025
A car manufacturing firm is bringing out a new model. To figure out its advertising campaign, they want to determine whether the model appeal will be dependent on a particular age group. A sample of
A survey of college students determined the preference for cell phone providers. The following data were obtained:Provider Gender T-Mobile AT&T Verizon Other Male 12 39 27 16 Female 8 22 24 12 Can we
Are there significant differences in ratings of specific product/service attributes in the 2014 Customer Survey worksheet?
In the worksheet On-Time Delivery, has the proportion of on-time deliveries in 2014 significantly improved since 2010?
Have the data in the worksheet Defects After Delivery changed significantly over the past 5 years?
Although engineering has collected data on alternative process costs for building transmissions in the worksheet Transmission Costs, why didn’t they reach a conclusion as to whether one of the
Are there differences in employee retention due to gender, college graduation status, or whether the employee is from the local area in the data in the worksheet Employee Retention?
Explain the purpose of regression analysis and provide examples in business.
Use a scatter chart to identify the type of relationship between two variables.
List the common types of mathematical functions used in predictive modeling.
Use the Excel Trendline tool to fit models to data.
Explain how least-squares regression finds the bestfitting regression model.
Use Excel functions to find least-squares regression coefficients.
Use the Excel Regression tool for both single and multiple linear regressions.
Interpret the regression statistics of the Excel Regression tool.
Interpret significance of regression from the Excel Regression tool output.
Draw conclusions for tests of hypotheses about regression coefficients.
Interpret confidence intervals for regression coefficients
Calculate standard residuals.
List the assumptions of regression analysis and describe methods to verify them.
Explain the differences in the Excel Regression tool output for simple and multiple linear regression models.
Apply a systematic approach to build good regression models.
Explain the importance of understanding multicollinearity in regression models.
Build regression models for categorical data using dummy variables.
Test for interactions in regression models with categorical variables.
Identify when curvilinear regression models are more appropriate than linear models.
Each worksheet in the Excel file LineFit Data contains a set of data that describes a functional relationship between the dependent variable y and the independent variable x. Construct a line chart
A consumer products company has collected some data relating to the advertising expenditure and sales of one of its products:Advertising cost Sales$300 â•‡ $7000$350 â•‡ $9000$400
Using the data in Excel file Loans, construct a scatter chart for monthly income versus loan amount and add a linear trendline. What is the regression model?If an individual has 7336 as monthly
Using the results of fitting the Home Market Value regression line in Example 8.4, compute the errors associated with each observation using formula (8.3)and construct a histogram.
Set up an Excel worksheet to apply formulas (8.5)and (8.6) to compute the values of b0 and b1 for the data in the Excel file Home Market Value and verify that you obtain the same values as in
The managing director of a consulting group has the following monthly data on total overhead costs and professional labor hours to bill to clients:4 Overhead Costs Billable Hours$365,000
Using the data in Excel file Crime, apply the Excel regression tool using crime rate (CRIM) as the dependent variable and pupil-teacher ratio (PTRATIO)in the region as the independent variable.a.
Using the data in the Excel file Credit Card Spending, develop a multiple linear regression model for estimating the average credit card expenditure as a function of both the income and family size.
For the Car Sales data described in Problem 25, develop a regression model for selling price as a function of horsepower and manufacture year, incorporating an interaction term. What would be the
Cost functions are often nonlinear with volume because production facilities are often able to produce larger quantities at lower rates than smaller quantities.5 Using the following data, apply
A product manufacturer wishes to determine the relationship between the shelf space of the product and its sales. Past data indicates the following sales and shelf space in its stores.Sales Shelf
Use XLMiner and best subsets with stepwise selection to find the best model points per game for the National Football League data (see Problem 23).
In reviewing the PLE data, Elizabeth Burke noticed that defects received from suppliers have decreased (worksheet Defects After Delivery). Upon investigation, she learned that in 2010, PLE
Define business analytics. Appendix
Explain why analytics is important in today’s business environment. Appendix
State some typical examples of business applications in which analytics would be beneficial. Appendix
Summarize the evolution of business analytics and explain the concepts of business intelligence, operations research and management science, and decision support systems. Appendix
Explain and provide examples of descriptive, predictive, and prescriptive analytics. Appendix
State examples of how data are used in business. Appendix
Explain the difference between a data set and a database. Appendix
Define a metric and explain the concepts of measurement and measures. Appendix

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