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statistics

Questions and Answers of Statistics

Determine the equation of the least squares regression line to predict y from the following data.a. Construct a 95% confidence interval to estimate the mean y value for x = 60.b. Construct a 95%
Determine the equation of the trend line through the following cost data. Use the equation of the line to forecast cost for year 7.Year ... Cost ($ millions)1 ..... 562 ..... 543 ..... 494 ..... 465
A manager of a car dealership believes there is a relationship between the number of salespeople on duty and the number of cars sold. Suppose the following sample is used to develop a simple
The American Research Group, Inc. conducted a telephone survey of a random sample of 1, 100 U.S. adults in a recent year and determined that the average amount of planned spending on gifts for the
It seems logical that restaurant chains with more units (restaurants) would have greater sales. This assumption is mitigated, however, by several possibilities: some units may be more profitable than
Shown here are the labor force figures (in millions) published by Index Mundi for the country of Bangladesh over a 10-year period. Develop the equation of a trend line through these data and use the
How strong is the correlation between the inflation rate and 30-year treasury yields? The following data published by Fuji Securities are given as pairs of inflation rates and treasury yields for
Shown below are data on the total sales generated by the seafood industry and the corresponding jobs supported by the seafood industry in the top 15 states by seafood sales. The data are published by
People in the aerospace industry believe the cost of a space project is a function of the weight of the major object being sent into space. Use the following data to develop a regression model to
The following data represent a breakdown of state banks and all savings organizations in the United States every 5 years over a 60-year span, according to the Federal Reserve System.Develop a
Is the amount of money spent by companies on advertising a function of the total revenue of the company? Shown are revenue and advertising cost data for nine companies published by Advertising
Can the consumption of water in a city be predicted by air temperature? The following data represent a sample of a day’s water consumption and the high temperature for that day.Water
Study the following Minitab output from a regression analysis to predict y from x.a. What is the equation of the regression model?b. What is the meaning of the coefficient of x?c. What is the result
Study the following Excel regression output for an analysis attempting to predict the number of union members in the United States by the size of the labor force for selected years over a 30-year
Compute r2 for Problem 12.24 (Problem 12.6). Discuss the value of r2 obtained.
Compute r2 for Problem 12.25 (Problem 12.7). Discuss the value of r2 obtained.
Compute r2 for Problem 12.26 (Problem 12.8). Discuss the value of r2 obtained.
Compute r2 for Problem 12.27 (Problem 12.9). Discuss the value of r2 obtained.
In Problem 12.10, you were asked to develop the equation of a regression model to predict the number of business bankruptcies by the number of firm births. For this regression model, solve for the
Study the following Minitab residual diagnostic graphs. Comment on any possible violations of regressionassumptions.
The Delta Wire Corporation was founded in 1978 in Clarksdale, Mississippi. The company manufactures high-carbon specialty steel wire for global markets and at present employs about 100 people. For
Use a computer to develop the equation of the regression model for the following data. Comment on the regression coefficients. Determine the predicted value of y for x1 = 200 and x2 =7.
Use a computer to develop the equation of the regression model for the following data. Comment on the regression coefficients. Determine the predicted value of y for x1 = 33, x2 = 29, and x3 =13.
Examine the Minitab output shown here for a multiple regression analysis. How many predictors were there in this model? Comment on the overall significance of the regression model. Discuss the t
Using the data from Problem 13.6, develop a multiple regression model to predict insider ownership from debt ratio and dividend payout. Comment on the strength of the model and the predictors by
Study the Minitab output shown in Problem 13.7.Comment on the overall strength of the regression model in light of S, R2, and adjustedR2.
Study the Minitab output shown in Problem 13.8.Comment on the overall strength of the regression model in light of S, R2, and adjustedR2.
Using the regression output obtained by working Problem 13.11, comment on the overall strength of the regression model using S, R2, and adjustedR2.
Study the Minitab residual diagnostic output that follows. Discuss any potential problems with meeting the regression assumptions for this regression analysis based on the residual graphics.
Using the following data determine the equation of the regression model. How many independent variables are there? Comment on the meaning of these regression coefficients.Predictor
Use the following data to determine the equation of the multiple regression model. Comment on the regression coefficients.Predictor .. CoefficientConstant .... 31,409.5x1 ...... .08425x2 ......
Is there a particular product that is an indicator of per capita personal consumption for countries around the world? Shown on the next page are data on per capita personal consumption, paper
Jensen, Solberg, and Zorn investigated the relationship of insider ownership, debt, and dividend policies in companies. One of their findings was that firms with high insider ownership choose lower
Displayed here is the Minitab output for a multiple regression analysis. Study the ANOVA table and the t ratios and use these to discuss the strengths of the regression model and the predictors. Does
Using the data in Problem 13.5, develop a multiple regression model to predict per capita personal consumption by the consumption of paper, fish, and gasoline. Discuss the output and pay particular
Develop a multiple regression model to predict y from x1, x2, and x3 using the following data. Discuss the values of F andt.
Use the following data to develop a regression model to predict y from x1 and x2. Comment on the output. Develop a regression model to predict y from x1 only. Compare the results of this model with
Study the following Excel multiple regression output. How many predictors are in this model? How many observations? What is the equation of the regression line? Discuss the strength of the model in
Using the regression output obtained by working Problem 13.5, comment on the overall strength of the regression model using S, R2, and adjusted R2. Discuss.
Using the regression output obtained by working Problem 13.12, comment on the overall strength of the regression model using S, R2, and adjusted R2. Discuss.
Study the Minitab regression output that follows. How many predictors are there? What is the equation of the regression model? Using the key statistics discussed in this chapter, discuss the strength
Study the Excel regression output that follows. How many predictors are there? What is the equation of the regression model? Using the key statistics discussed in this chapter, discuss the strength
Use the following data to develop a multiple regression model to predict y from x1 and x2. Discuss the output, including comments about the overall strength of the model, the significance of the
Given here are the data for a dependent variable, y, and independent variables. Use these data to develop a regression model to predict y. Discuss theoutput.
The U.S. Bureau of Mines produces data on the price of minerals. Shown here are the average prices per year for several minerals over a decade. Use these data and multiple regressions to produce a
The Shipbuilders Council of America in Washington, D.C., publishes data about private shipyards. Among the variables reported by this organization are the employment figures (per 1000), the number of
The U.S. Bureau of Labor Statistics produces consumer price indexes for several different categories. Shown here are the percentage changes in consumer price indexes over a period of 20 years for
The U.S. Department of Agriculture publishes data annually on various selected farm products. Shown here are the unit production figures (in millions of bushels) for three farm products for 10 years
The American Chamber of Commerce Researchers Association compiles cost-of-living indexes for selected metropolitan areas. Shown here are cost-of-living indexes for 25 different cities on five
Shown here are the data for y and three predictors, x1, x2, and x3.A multiple regression analysis has been done on these data; the Minitab results are given. Comment on the outcome of the analysis in
Minitab residual diagnostic output from the multiple regression analysis for the data given in Problem 13.30 follows. Discuss any potential problems with meeting the regression assumptions for this
Starbucks is a resounding restaurant success story. Beginning with its first coffee house in 1971, Starbucks has grown to more than 11,000 U.S. locations. Opening up its first international outlet in
Use the following data to develop a quadratic model to predict y from x. Develop a simple regression model from the data and compare the results of the two models. Does the quadratic model seem to
Develop a multiple regression model of the formUsing the following data to predict y from x. From a scatter plot and Tukey€™s ladder of transformation, explore ways to recode the data and
The Publishers Information Bureau in New York City released magazine advertising expenditure data compiled by leading national advertisers. The data were organized by product type over several years.
Dun & Bradstreet reports, among other things, information about new business incorporations and number of business failures over several years. Shown here are data on business failures and current
Use the following data to develop a curvilinear model to predict y. Include both x1 and x2 in the model in addition to x21 and x22, and the interaction term x1x2. Comment on the overall strength of
What follows is Excel output from a regression model to predict y using x1, x2, x21, x22, and the interaction term, x1x2. Comment on the overall strength of the model and the significance of each
Analyze the following data by using a multiple regression computer software package to predict y using x1 and x2. x2 is a dummy variable. Discuss the output from the regression analysis; in
Given here are the data from a dependent variable and two independent variables. The second independent variable is an indicator variable with several categories. Hence, this variable is represented
Given here is Excel output for a multiple regression model that was developed to predict y from two independent variables, x1 and x2.Variablex2is a dummy variable. Discuss the strength of the
Falvey, Fried, and Richards developed a multiple regression model to predict the average price of a meal at New Orleans restaurants. The variables explored included such indicator variables as the
Use a stepwise regression procedure and the following data to develop a multiple regression model to predict y. Discuss the variables that enter at each step, commenting on their t values and on the
Given here are data for a dependent variable and four potential predictors. Use these data and a stepwise regression procedure to develop a multiple regression model to predict y. Examine the values
The computer output given here is the result of a stepwise multiple regression analysis to predict a dependent variable by using six predictor variables. The numbers of observations were 108. Study
Study the output given here from a stepwise multiple regression analysis to predict y from four variables. Comment on the output at eachstep.
The National Underwriter Company in Cincinnati, Ohio, publishes property and casualty insurance data. Given here is a portion of the data published. These data include information from the U.S.
Develop a correlation matrix for the independent variables in Problem 14.13. Study the matrix and make a judgment as to whether substantial multicollinearity is present among the predictors. Why or
Construct a correlation matrix for the four independent variables for Problem 14.14 and search for possible multi-co-linearity. What did you find, and why?
In Problem 14.17, you were asked to use stepwise regression to predict premiums earned by net income, dividends, and underwriting gain or loss. Study the stepwise results, including the regression
Study the three predictor variables in Problem 14.18 and attempt to determine whether substantial multicollinearity is present among the predictor variables. If there is a problem of
The Hospital database associated with this text and found in Wiley PLUS contains a dichotomous variable, Service, that represents two types of hospitals, general medical and psychiatric. In the
Another database associated with this text and found in Wiley PLUS is the Consumer Food database. There is a dichotomous variable in this database, and that is whether a family lives in a metro area
The Manufacturing database associated with this text and found in Wiley PLUS has a variable, Value of Industrial Shipments that is coded 0 if the value is small and 1 if the value is large. Using
Suppose logistic regression is used to develop a second model from the Manufacturing database discussed in problem 14.25 to predict the value of industrial shipments by two variables, Number of
Given here are the data for a dependent variable, y, and independent variables. Use these data to develop a regression model to predict y. Discuss the output. Which variable is an indicator variable?
Use the following data and a stepwise regression analysis to predict y. In addition to the two independent variables given here, include three other predictors in your analysis: the square of each x
Use the x1 values and the log of the x1values given here to predict the y values by using a stepwise regression procedure. Discuss the output. Was either or both of the predictorssignificant?
The U.S. Commodities Futures Trading Commission reports on the volume of trading in the U.S. commodity futures exchanges. Shown here are the figures for grain, oilseeds, and livestock products over a
The U.S. Bureau of Mines produces data on the price of minerals. Shown here are the average prices per year for several minerals over a decade. Use these data and a stepwise regression procedure to
The Shipbuilders Council of America in Washington, D.C., publishes data about private shipyards. Among the variables reported by this organization are the employment figures (per 1000), the number of
The U.S. Bureau of Labor Statistics produces consumer price indexes for several different categories. Shown here are the percentage changes in consumer price indexes over a period of 20 years for
The U.S. Department of Agriculture publishes data annually on various selected farm products. Shown here are the unit production figures for three farm products for 10 years during a 20-year period.
The American Chamber of Commerce Researchers Association compiles cost-of-living indexes for selected metropolitan areas. Shown here are cost-of-living indexes for 25 different cities on five
A stepwise regression procedure was used to analyze a set of 20 observations taken on four predictor variables to predict a dependent variable. The results of this procedure are given next. Discuss
Shown here are the data for y and three predictors, x1, x2, and x3.A stepwise regression procedure has been done on these data; the results are also given. Comment on the outcome of the stepwise
Shown below is output from two Excel regression analyses on the same problem. The first output was done on a €œfull€ model. In the second output, the variable with the smallest
Shown below is Minitab output from a logistic regression analysis to develop a model to predict whether a shopper in a mall store will purchase something by the number of miles the shopper drives to
The Minitab output displayed here is the result of a multiple regression analysis with three independent variables. Variable x1 is a dummy variable. Discuss the computer output and the role x1 plays
The U.S. Energy Information Administration releases figures in their publication, Monthly Energy Review, about the cost of various fuels and electricity. Shown here are the figures for four different
Virginia Semiconductor is a leading manufacturer of prime silicon substrates. The company, situated in Fredericksburg, Virginia, was founded in 1978 by Dr. Thomas G. Digges and his brother, Robert.
Use the forecast errors given here to compute MAD and MSE. Discuss the information yielded by each type of error measurement.Period .... e1 ...... 2.32 ...... 1.63 ..... -1.44 ..... 1.15
Determine the error for each of the following forecasts. Compute MAD andMSE.
Using the following data determine the values of MAD and MSE. Which of these measurements of error seems to yield the best information about the forecasts?Why?
Figures for acres of tomatoes harvested in the United States from an 11-year period follow. The data are published by the U.S. Department of Agriculture. With these data, forecasts have been made by
Use the following time-series data to answer the given questions.a. Develop forecasts for periods 5 through 10 using 4-month moving averages.b. Develop forecasts for periods 5 through 10 using
Following are time-series data for eight different periods. Use exponential smoothing to forecast the values for periods 3 through 8.Use the value for the first period as the forecast for the second
Following are time-series data for nine time periods. Use exponential smoothing with constants of .3 and .7 to forecast time periods 3 through 9.Let the value for time period 1 is the forecast for
The U.S. Census Bureau publishes data on factory orders for all manufacturing, durable goods, and nondurable goods industries. Shown here are factory orders in the United States over a 13-year period
The following data show the number of issues from initial public offerings (IPOs) for a 13-year period released by the Securities Data Company. Use these data to develop forecasts for the years 3

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