MGT 3604 Exam 2 Adaptive Test Prep Questions
21. The following regression model has been proposed to predict sales at a gas station where x1 = their previous day's sales (in $1,000's), x2 = population within 5 miles (in 1,000's), x3 = 1 if any form of advertising was used, 0 if otherwise, and sales (in $1,000's). Predict sales (in dollars) for a store with competitor's previous day's sale of $3,000, a population of 10,000 within 5 miles, and twenty radio advertisements. A) $86,000 B) $98,000 C) $104,000 D) $158,000
A) $86,000 (y= 10-4(3)+7(10)+18(1)))
44. The tests of significance in regression analysis are based on assumptions about the error term ε. One such assumption is that the error term ε is a random variable with a mean or expected value of A) 0. B) 1. C) y D) X-bar
A) 0.
11. Consider the following hypothesis test: A manufacturer takes a sample of 125 consumers. They suspect that over 75% of consumers will buy their brand of product. State an appropriate null and alternative hypothesis. A) H0: p ≤. 0.75, Ha: p >0.75 B) H0: p ≤. 0.75, Ha: p < 0.75 C) H0: p ≥. 0.75, Ha: p >0.75 D) H0: p ≥. 0.75, Ha: p < 0.75
A) H0: p ≤. 0.75, Ha: p >0.75
8. Several new fuel injection units will be manufactured, installed in test automobiles, and subjected to research-controlled driving conditions. The sample mean miles per gallon for these automobiles will be computed and used in a hypothesis test to determine if it can be concluded that the new system provides more than 24 miles per gallon. State the hypotheses. A) H0: μ ≤ 24, Ha: μ > 24 B) H0: μ < 24, Ha: μ ≥ 24 C) H0: μ ≥ 24, Ha: μ < 24 D) H0: μ = 24, Ha: μ ≠ 24
A) H0: μ ≤ 24, Ha: μ > 24
80. Consider the following time series data. Construct a time series plot. What type of pattern exists in the data? A) Horizontal B) Linear trend C) Nonlinear trend D) Cyclical
A) Horizontal
85. The monthly market shares of an electric company for 12 consecutive months follow. Construct a time series plot. What type of pattern exists in the data? A) Horizontal B) Linear trend C) Nonlinear trend D) Cyclical
A) Horizontal
26. _____ refers to the use of sample data to calculate a range of values that is believed to include the unknown value of a population parameter. A) Interval estimation B) Hypothesis testing C) Statistical inference D) Point estimation
A) Interval estimation
74. Based on the errors produced by the different models for the data, you could ultimately pick the model that minimizes some forecast error measure. Which of the following options is NOT a way to measure forecast errors? A) MAE B) MSE C) MAPE D) SST
A) MAE
75. South Shore Construction builds permanent docks and seawalls along the southern shore of Long Island, New York. Although the firm has been in business only five years, revenue has increased from $359,000 in the first year of operation to $1,343,000 in the most recent year. The following data show the quarterly sales revenue in thousands of dollars. Compute estimates of quarterly sales for Year 6. A) Qtr1 = 105, Qtr2 = 209, Qtr3 = 377, Qtr4 = 94 B) Qtr1 = 100, Qtr2 = 209, Qtr3 = 377, Qtr4 = 94 C) Qtr1 = 85, Qtr2 = 189, Qtr3 = 327, Qtr4 = 78 D) Cannot be determined with the information provided.
A) Qtr1 = 105, Qtr2 = 209, Qtr3 = 377, Qtr4 = 94--> Add 5 quarters/5
76. South Shore Construction builds permanent docks and seawalls along the southern shore of Long Island, New York. Although the firm has been in business only five years, revenue has increased from $359,000 in the first year of operation to $1,343,000 in the most recent year. The following data show the quarterly sales revenue in thousands of dollars. Based upon seasonal effects in the data and linear trend, compute estimates of quarterly sales for Year 6. A) Qtr1 = 280.2, Qtr2 = 383.8, Qtr3 = 546.6, Qtr4 = 245.6 B) Qtr1 = 221, Qtr2 = 523, Qtr3 = 325, Qtr4 = 84 C) Qtr1 = 72, Qtr2 = 211, Qtr3 = 156, Qtr4 = 168 D) Cannot be determined with the information provided.
A) Qtr1 = 280.2, Qtr2 = 383.8, Qtr3 = 546.6, Qtr4 = 245.6
58. __________ is a statistical procedure used to develop an equation showing how two variables are related. A) Regression analysis B) Data mining C) Time series analysis D) Factor analysis
A) Regression analysis
41. Suppose an estimated regression equation has a coefficient of determination (r2) of 0.866. Interpret this value. A) The estimated regression equation explains approximately 86.6% of the variation in the dependent variable. B) The estimated regression equation explains approximately 75.0% of the variation in the dependent variable. C) The estimated regression equation explains approximately 93.1% of the variation in the dependent variable. D) The estimated regression equation explains approximately 13.4% of the variation in the dependent variable.
A) The estimated regression equation explains approximately 86.6% of the variation in the dependent variable.
22. Interpret the coefficient of determination for this regression model. A) This regression model explains approximately 95.5% of the variation in cars sold for our sample data. B) This regression model explains approximately 97.7% of the variation in cars sold for our sample data. C) This regression model explains approximately 95.5% of the variation in months employed for our sample data. D) This regression model explains approximately 97.7% of the variation in months employed for our sample data.
A) This regression model explains approximately 95.5% of the variation in cars sold for our sample data.
13. The population parameter and the point estimate differ in that point estimate is obtained by collecting a sample, which is used to estimate the entire population. A) True B) False
A) True
3. A potential investor is interested in knowing whether a particular fast food drive-thru's mean service time is smaller than the competitor's service time of 2 minutes. If the investor concluded the restaurant's mean service is less than 2 minutes when it is not, it would be a _________ error. A) Type I B) Type II C) No error was made. D) Cannot be determined based upon the information provided.
A) Type I
50. Suppose a residual plot of x versus the residuals, , shows a nonconstant variance. In particular, as the values of x increase, suppose that the value of the residuals also increase. This means that A) as the values of x get larger, the ability to predict y becomes less accurate. B) as the values of x get larger, the error term, , becomes smaller. C) as the values of x get larger, the values of y become larger. D) as the values of x get larger, the standard deviation of the residuals becomes smaller.
A) as the values of x get larger, the ability to predict y becomes less accurate.
49. When we use the estimated regression equation to develop an interval that can be used to predict the mean for ALL units that meet a particular set of given criteria, that interval is called a A) confidence interval. B) prediction interval. C) estimation interval. D) population interval.
A) confidence interval.
97. We can model a time series with a seasonal pattern by treating the season as a A) dummy variable. B) smoothing constant. C) lagged variable. D) trend component.
A) dummy variable.
38. The term in the multiple regression model that accounts for the variability in y that cannot be explained by the linear effect of the q independent variables is the A) error term, E B) the leading coefficient, B0 C) the coefficient of determination, r^2 D) the response variable, y
A) error term, E
60. Simple linear regression refers to the type of regression analysis for which the relationship between the independent variable and dependent variable are approximated by a(n) A) exponential curve. B) straight line. C) normal curve. D) piecewise function.
A) exponential curve.
84. What forecasting method uses a weighted average of past time series values as the forecast; it is a special case of the weighted moving averages method in which we select only one weight—the weight for the most recent observation? A) exponential smoothing B) moving averages C) weighted moving averages D) time series decomposition
A) exponential smoothing
88. The difference between the actual time series value and the forecast is the A) forecast error. B) absolute forecast error. C) percent error. D) lagged error.
A) forecast error.
67. A prediction of future values of a time series is called a(n) A) forecast. B) lagged value. C) least squares trend line. D) adjusted model.
A) forecast.
17. Two variables have a positive linear correlation. As the dependent variable increases, the independent variable will A) increase. B) decrease. C) remain constant. D) vary normally about its mean.
A) increase.
71. Consider the following data and Excel output for a simple linear regression model. Interpret the slope of the equation. As the ________ by 1 unit, the _____________ by 0.750. A) independent variable increases, dependent variable will increase B) dependent variable increases, independent variable will increase C) independent variable decreases, dependent variable will increase D) dependent variable decreases, independent variable will increase
A) independent variable increases, dependent variable will increase
48. The tests of significance in regression analysis are based on assumptions about the error term ε. One such assumption is that the values of ε are A) independent. B) categorical. C) uniformly distributed. D) limited.
A) independent.
93. The value of an independent variable from the prior period is referred to as a A) lagged variable B) prior component C) trend component D) dummy variable
A) lagged variable
7. A finite population correction factor is needed in computing the standard deviation of the sampling distribution of sample means whenever the sample size is ________________ of the population size. A) more than 5% B) less than 10% C) more than 90% D) less than 20%
A) more than 5%
4. A parameter is a numerical measure from a population, such as a ___________. A) population mean. B) sample mean. C) sample proportion. D) standard error.
A) population mean.
6. The conclusion that the alternative hypothesis, as a research hypothesis, is true can be made if the sample data provide sufficient evidence to show that the null hypothesis can be A) rejected. B) accepted. C) true. D) false.
A) rejected.
70. An annual time series cannot exhibit a A) seasonal component B) trend component C) forecast D) random component
A) seasonal component
43. In the simple linear regression equation, the parameter B1 is the _______ of the true regression line. A) slope B) x-intercept C) y-intercept D) end-point
A) slope
73. The time-series component that implies a long-term upward or downward pattern is called A) the trend component B) the time component C) the exponential component D) the seasonal component
A) the trend component
98. A set of observations on a variable measured at successive points in time or over successive periods of time is referred to as a(n) A) time series. B) forecast. C) least squares trend line. D) adjusted model.
A) time series.
95. In regression analysis, when using large data sets, splitting data into ____ will be useful in determining which model to use. A) training and validation sets B) sets with similar patterns and trends C) linear or nonlinear sets D) seasonal and non-seasonal sets
A) training and validation sets
66. Which of the following exponential smoothing constant values puts the same weight on the most recent time series value as does a 5-period moving average? A) α = 0.2 B) α = 0.25 C) α = 0.75 D) α = 0.8
A) α = 0.2
53. In a regression analysis if SSE = 200 and SSR = 300, then the coefficient of determination is A) 0.67. B) 0.6. C) 0.4. D) 1.5.
B) 0.6 --> 300/(200+300)
30. Consider the Excel output for a simple linear regression model. What is the regression model? A) 0.121+ 0.0019655x B) 2.64 + 0.016x C) 21.83 + 8.187x D) 0.016 + 2.64x
B) 2.64 + 0.016x
90. Consider the following data that was fitted using a Linear Trend for the past 12 months: 21.51, 22.43, 23.02, 23.03, 22.1, 23.37, 23.21, 24.6, 23.31, 23.94, 26.05, 26.65. The intercept of the trend line is 21.231, and the slope is 0.365. What is the forecast for period 13? A) 27.6368 B) 25.976 C) 23.602 D) 21.231
B) 25.976--> 21.231+0.365(13)
91. Consider the following data that was fitted using a Linear Trend for the past 12 months: 31.51, 33.43, 36.05, 33.03, 43.5, 33.37, 35.43, 34.6, 37.63, 33.94, 36.05, 36.65. The intercept of the trend line is 33.985, and the slope is 0.223. What is the forecast for period 13? A) 33.985 B) 36.884 C) 35.4325 D) 26.5
B) 36.884--> 33.985+-.223(13)
94. Demand for a product and the forecasting department's forecast (naïve model) for a product are shown below. Compute the mean squared error. A) 3.33 B) 4.67 C) 5.33 D) 6.67
B) 4.67--> (15-12)^2+(14-15)^2+(18-16)^2/3
9. A new cellular provider claims that using their network you can get download speeds of 40.0 Mbps per second. You want to investigate if the download speed is really slower than advertised. State the hypotheses. Explain your reasoning. A) H0: μ ≤ 24, Ha: μ > 24 B) H0: μ ≥ 40, Ha: μ < 40 C) H0: μ < 40, Ha: μ ≥ 40 D) H0: μ = 40, Ha: μ ≠ 40
B) H0: μ ≥ 40, Ha: μ < 40
68. Consider the following time series data. Construct a time series plot. What type of pattern exists in the data? A) Horizontal B) Linear trend C) Nonlinear trend D) Cyclical
B) Linear trend
25. Which of the following gives the correct quadratic regression model? A) Sales = 10.57 + 6.92(Months Employed) + 0.97(Months Employed)^2 B) Sales = 21.92 - 24.55(Months Employed) + 8.06(Months Employed)^2 C) Sales = 2 + 27(Months Employed) + 29(Months Employed)^2 D) Sales = 2.07 - 3.55(Months Employed) + 8.33(Months Employed)^2
B) Sales = 21.92 - 24.55(Months Employed) + 8.06(Months Employed)^2
16. A potential investor is interested in knowing whether a particular fast food drive-thru's mean service time is smaller than the competitor's service time of 2 minutes. If the investor would conclude the restaurant's mean service is not less than 2 minutes when it is, this would be a _________ error. A) Type I B) Type II C) No error was made. D) Cannot be determined with the information provided.
B) Type II
24. The mathematical equation relating the expected value of the dependent variable to the value of the independent variables, which has the form of y= B0+B1X1+B2X2+...+BqXq+E is called A) a simple linear regression model. B) a multiple regression model. C) an estimated multiple regression equation. D) a multiple regression equation.
B) a multiple regression model.
27. Which of the following options guarantees that the best model for a given number of variables will be found? A) backward elimination. B) best subsets regression. C) forward selection. D) stepwise regression.
B) best subsets regression.
47. Which of the following options is NOT an iterative variable selection procedure? A) backward elimination. B) best subsets regression. C) forward selection. D) stepwise regression.
B) best subsets regression.
59. In the simple linear regression model, the ________ accounts for the variability in the dependent variable that cannot be explained by the linear relationship between x and y. A) constant term B) error term C) model parameter D) residual
B) error term
34. The process of making conjecture about the value of a population parameter, collecting sample data that can be used to assess this conjecture, measuring the strength of the evidence against the conjecture that is provided by the sample, and using these results to draw a conclusion about the conjecture is known as A) postulation. B) hypothesis testing. C) statistical inference. D) empirical research.
B) hypothesis testing.
65. The coefficient of determination A) can be any positive number. B) is defined as SSR/SST. C) is used to measure the slope of the estimated regression line. D) is interpreted as the percent of the variation in the values of x that are explained by the estimated regression line.
B) is defined as SSR/SST.
87. Autoregressive models typically violate the condition necessary for inference in A) time series analysis. B) least squares regression. C) forecast modeling. D) correlation analysis.
B) least squares regression.
72. Three of the following forecasting methods are appropriate for a time series with a horizontal pattern. Which one is not appropriate for a time series with a horizontal pattern? A) exponential smoothing. B) linear trend regression. C) moving averages. D) weighted moving averages.
B) linear trend regression.
79. A measure of forecasting accuracy, the average of the squared differences between the forecast values and the actual time series values is the A) mean absolute error (MAE). B) mean squared error (MSE). C) mean absolute percentage error (MAPE). D) mean forecast error (MFE).
B) mean squared error (MSE).
82. A time-series graph shows that annual sales data have decreased gradually over the past several years. Given this, if a linear trend model is used to forecast future years' sales, the value of the regression slope coefficient will be A) positive B) negative C) approaching zero D) difficult to determine
B) negative
23. When we use the estimated regression equation to develop an interval that can be used to predict the mean for a specific unit that meets a particular set of given criteria, that interval is called a A) confidence interval. B) prediction interval. C) estimation interval. D) population interval.
B) prediction interval.
2. When a selected sample adheres to the following conditions, it is said to be a Condition (1) each element selected comes from the same population. Condition (2) each element is selected independently. A) simple random sample. B) random sample. C) sampled population. D) target population.
B) random sample.
54. A _____ is used to visualize sample data graphically and to draw preliminary conclusions about the possible relationship between the variables. A) contingency table B) scatter chart C) bar chart D) pie chart
B) scatter chart
57. When the mean value of the response variable is independent of variation in the predictor variable, the slope of the regression line is A) positive. B) zero. C) negative. D) infinite.
B) zero
36. The following regression model has been proposed to predict sales at a gas station, y=10-4x1+7x2+18x3 where x1 = their previous day's sales (in $1,000's), x2 = population within 5 miles (in 1,000's), x3 = 1 if any form of advertising was used, 0 if otherwise, and sales (in $1,000's). Predict sales (in dollars) for a store with competitor's previous day's sale of $3,000, a population of 10,000 within 5 miles, and six radio advertisements. A) $78,000 B) $82,000 C) $86,000 D) $176,000
C) $86,000 (y=10-4(3)+7(10)+18(1)))
15. Consider the following hypothesis test: A manufacturer takes a sample of 125 consumers. They suspect that over 75% of consumers will buy their brand of product. The survey results are that 92 out of 125 of the consumers indicated they will buy the product. What is the value of p? A) 0.230 B) 0.469 C) 0.736 D) 0.920
C) 0.736 (92/125)
77. South Shore Construction builds permanent docks and seawalls along the southern shore of Long Island, New York. Although the firm has been in business only five years, revenue has increased from $359,000 in the first year of operation to $1,343,000 in the most recent year. The following data show the quarterly sales revenue in thousands of dollars. Let Period 1 refer to the observation in quarter 1 of year 1; Period 2 refer to the observation in quarter 2 of year 1; . . . and Period 20 refer to the observation in quarter 4 of year 5. Using the dummy variables defined here, what values are needed to yield the first-year values for Quarter 1? A) 24, 150, 170, 16 B) 1, 2, 3, 4 C) 1, 0, 0, 0 D) Cannot be determined with the information provided.
C) 1, 0, 0, 0
52. The multiple regression equation based on the sample data, which has the form y=b0+b1x1+b2x2+...+bqxq is called A) a simple linear regression model. B) a multiple regression model. C) an estimated multiple regression equation. D) a multiple regression equation.
C) an estimated multiple regression equation.
33. A variable used to model the effect of categorical independent variables is called a A) explanatory variable. B) categorical variable. C) dummy variable. D) quantitative variable.
C) dummy variable.
64. The _____ is the range of values of the independent variables in the data used to estimate the regression model. A) confidence interval B) codomain C) experimental region D) validation set
C) experimental region
100. A measure of the accuracy of a forecasting method, the average of the absolute values of the errors as a percentage of the corresponding forecast values is the A) mean absolute error (MAE). B) mean squared error (MSE). C) mean absolute percentage error (MAPE). D) mean forecast error (MFE).
C) mean absolute percentage error (MAPE).
69. If the historical data on which the model is being built consist of monthly data, the forecasting period would probably be A) daily B) weekly C) monthly D) annually
C) monthly
83. The method that uses the average of the most recent k data values in the time series as the forecast for the next period is called A) exponential smoothing. B) linear trend regression. C) moving averages. D) weighted moving averages.
C) moving averages.
40. The study of how a dependent variable y is related to two or more independent variables is called A) least significant difference analysis. B) linear regression analysis. C) multiple linear regression. D) factorial design analysis.
C) multiple linear regression.
39. The tests of significance in regression analysis are based on assumptions about the error term ε. One such assumption is that the error term ε follows a ________ distribution for all values of x. A) binomial B) exponential C) normal D) uniform
C) normal
18. A(n) ________ refers to a measurable factor that defines a characteristic of a population, process, or system. A) random variable B) expectation C) parameter D) residual
C) parameter
92. Consider the following data and its associated Excel output for a simple linear regression model. How would you describe the linear relationship between x and y? A) negative linear relationship B) no linear relationship C) positive linear relationship D) Cannot be determined with the information provided.
C) positive linear relationship
51. What type of regression model should be used when there is a nonlinear relationship between the independent and dependent variables which is fit by including the independent variable and the square of the independent variable? A) simple linear regression model B) multiple variable regression model C) quadratic regression model D) exponential regression model
C) quadratic regression model
62. The difference between the observed value of the dependent variable and the value predicted using the estimated regression equation is known as the A) constant term. B) error term. C) residual. D) model parameter.
C) residual.
32. Regression analysis involving one independent variable and one dependent variable is referred to as A) factor analysis. B) time series analysis. C) simple linear regression. D) data mining.
C) simple linear regression.
86. The average of all the historical data will always provide the best results when the underlying time series is A) increasing. B) decreasing. C) stationary. D) cyclical.
C) stationary.
37. The process of making estimates and drawing conclusions about one or more characteristics of a population through analysis of sample data drawn from the population is known as A) inductive inference. B) deductive inference. C) statistical inference. D) Bayesian inference.
C) statistical inference.
46. The _____ is a measure of the error that results from using the estimated regression equation to predict the values of the dependent variable in a sample. A) sum of squares due to regression (SSR) B) error term C) sum of squares due to error (SSE) D) residual
C) sum of squares due to error (SSE)
10. For the interval estimation of μ when σ is unknown, the proper distribution to use is the A) standard normal distribution B) t distribution with n degrees of freedom C) t distribution with n − 1 degrees of freedom D) t distribution with n − 2 degrees of freedom
C) t distribution with n − 1 degrees of freedom
20. The procedure of using sample data to find the estimated regression equation is better known as A) point estimation. B) interval estimation. C) the least squares method. D) extrapolation.
C) the least squares method
29. The tests of significance in regression analysis are based on assumptions about the error term ε. One such assumption is that the variance of ε, denoted by σ 2 , is A) greater as x increases. B) less as x increases. C) the same for all values of x. D) unrelated to the value of x.
C) the same for all values of x.
5. When the expected value of a point estimator equals the population parameter, we say that the point estimator is A) the expected value. B) the standard error. C) unbiased. D) estimated.
C) unbiased.
1. Which of the following symbols is used to refer to a sample statistic? A) p B) µ C) x-bar D) 𝜎
C) x-bar
61. In the simple linear regression equation, the parameter B0 represents the _____ of the true regression line. A) slope B) x-intercept C) y-intercept D) end-point
C) y-intercept
19. What would be the coefficient of determination if the total sum of squares (SST) is 30 and the sum of squares due to regression (SSR) is 27? A) 0.30 B) 0.40 C) 0.80 D) 0.90
D) 0.90
45. What would be the value of the sum of squares due to regression (SSR) if the total sum of squares (SST) is 22.21 and the sum of squares due to error (SSE) is 6.89? A) 31.89 B) 19.32 C) 18.43 D) 15.32
D) 15.32 (22.21-6.89)
81. In the table below, we see data for the number of units were sold for a 5-week period. Use a three-week moving average to estimate the number of units that will be sold during week 7. A) 6 B) 6.67 C) 7 D) 7.67
D) 7.67
31. Found below is Excel output from a quadratic regression analysis based upon the number of cars each employee sold during the most recent sales period and the number of months each salesperson has been employed by the company. Based upon the p-values for "Month" and "Month Squared", what can we conclude about the current model? A) Because both p-values are greater than 0.05, we can conclude that adding Months Squared to the model involving Months is not significant. B) Because both p-values are greater than 0.05, we can conclude that adding Months Squared to the model involving Months is significant. C) Because both p-values are substantially less than 0.05, we can conclude that adding Months Squared to the model involving Months is not significant. D) Because both p-values are substantially less than 0.05, we can conclude that adding Months Squared to the model involving Months is significant.
D) Because both p-values are substantially less than 0.05, we can conclude that adding Months Squared to the model involving Months is significant.
14. Consider the following hypothesis test: A manufacturer takes a sample of 125 consumers. They suspect that over 75% of consumers will buy their brand of product. Describe the consequences to the manufacturer of making a Type I error for this test. A) They will invest in developing a product that will meet expectations. B) They will not invest in developing a product that will not meet expectations. C) They will not invest in developing a product that will meet expectations. D) They will invest in developing a product that will not meet expectations.
D) They will invest in developing a product that will not meet expectations.
96. The component of the time series that results in periodic above-trend and below-trend behavior of the time series lasting more than one year is known as a A) seasonal pattern B) linear trend pattern C) exponential trend pattern D) cyclical pattern
D) cyclical pattern
42. Prediction of the value of the dependent variable outside the experimental region is called A) interpolation. B) forecasting. C) averaging. D) extrapolation.
D) extrapolation.
35. The graph of the simple linear regression equation is a(n) _____. A) ellipse B) hyperbola C) parabola D) line
D) line
56. When there are many independent variables to consider, special procedures are sometimes employed to select the independent variables to include in the regression model. All of the following are examples of variable selection procedures except for A) backward elimination. B) forward selection. C) best subsets. D) overfitting.
D) overfitting.
78. While virtually all time series exhibit a __________________, not all time series exhibit other components. A) seasonal component B) trend component C) forecast D) random component
D) random component
99. Which graphical display is useful in determining which forecasting model to select? A) box plot B) a normal distribution C) bar chart D) scatter chart
D) scatter chart
12. Which of the following sampling techniques exemplifies a simple random sample? A) selecting 25 men and 25 women by drawing names from a "men's" hat and a "women's" hat B) selecting the first 50 people to enter into a baseball stadium C) selecting all households within a certain community D) selecting 50 names drawn at random from a hat without replacement
D) selecting 50 names drawn at random from a hat without replacement
89. A time series whose statistical properties are independent of time is called a(n) A) forecast. B) least squares trend line. C) adjusted model. D) stationary time series.
D) stationary time series.
55. When determining the best estimated regression equation to model a set of data, the procedure that uses an iterative variable selection procedure that considers adding an independent variable and removing an independent variable at each step is called A) backward elimination. B) the best subsets procedure. C) forward selection. D) stepwise selection.
D) stepwise selection.
63. If a residual plot of x versus the residuals, y-y^ , shows a non-linear pattern then we should conclude that A) the regression model was not based upon a large enough sample size. B) the regression model describes the relationship between x and y very well. C) the regression model is useful for making predictions. D) the regression model is not an adequate representation of the relationship between the variables.
D) the regression model is not an adequate representation of the relationship between the variables.
28. If GPA and Aptitude Test Scores are linearly related, which of the following must be true? A) β = 0 B) β > 0 C) β < 0 D) β ≠ 0
D) β ≠ 0
