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Question: If a data set contains 6 independent

If a data set contains 6 independent variables, the number of all possible regression models will be __________. a) 31 b) 62 c) 63 d) 64 22. The main difference between forward selection and stepwise regression is this: __________. a) Forward selection is not a step-by-step procedure b) The outcome of forward selection is never the same as that of stepwise regression c) The outcome of forward selection is always the same as that of stepwise regression d) In forward selection, once a variable is entered into the model, it is never dropped out 23. The problem of multi-collinearity in a regression analysis occurs when __________.: a) The independent variables are highly correlated with the dependent variable b) Two or more of the independent variables are highly correlated c) The regression model contains several linear fits d) Two or more of the dependent variables are highly correlated 24. If multi-collinearity exists in a multiple regression analysis, which one of the following effects will not be a concern? a) Inordinately small t values for the regression coefficients may result. b) It is difficult to interpret the estimates of the regression coefficients. c) The algebraic sign of estimated regression coefficients may be the opposite of what would be expected for a particular predictor variable. d) The standard deviations of regression coefficients are overestimated. e) The standard deviations of regression coefficients are underestimated. 25. Variance inflation factor is useful in overcoming the problem of ___________. a) Nonlinearity. b) Heteroscedasticity c) Non-normality d) Multi-collinearity 26. For a multiple linear regression model, if the t values are not significant, but the overall F value for the model is highly significant, then what might be the possible problem for this regression model? a) Estimability b) Multi-collinearity c) Extrapolation d) Non-linear problem 27. Refer to Figure 14.13 from the textbook, what is the probability that a 45-year-old auto club member will return the form? FIGURE 4.13: Tree Diagram for Cartridge Problem Probabilities
If a data set contains 6 independent variables, the number of all possible regression models will be __________.
a) 31
b) 62
c) 63
d) 64
22. The main difference between forward selection and stepwise regression is this: __________.
a) Forward selection is not a step-by-step procedure
b) The outcome of forward selection is never the same as that of stepwise regression
c) The outcome of forward selection is always the same as that of stepwise regression
d) In forward selection, once a variable is entered into the model, it is never dropped out
23. The problem of multi-collinearity in a regression analysis occurs when __________.:
a) The independent variables are highly correlated with the dependent variable
b) Two or more of the independent variables are highly correlated
c) The regression model contains several linear fits
d) Two or more of the dependent variables are highly correlated
24. If multi-collinearity exists in a multiple regression analysis, which one of the following effects will not be a concern?
a) Inordinately small t values for the regression coefficients may result.
b) It is difficult to interpret the estimates of the regression coefficients.
c) The algebraic sign of estimated regression coefficients may be the opposite of what would be expected for a particular predictor variable.
d) The standard deviations of regression coefficients are overestimated.
e) The standard deviations of regression coefficients are underestimated.
25. Variance inflation factor is useful in overcoming the problem of ___________.
a) Nonlinearity.
b) Heteroscedasticity
c) Non-normality
d) Multi-collinearity
26. For a multiple linear regression model, if the t values are not significant, but the overall F value for the model is highly significant, then what might be the possible problem for this regression model?
a) Estimability
b) Multi-collinearity
c) Extrapolation
d) Non-linear problem
27. Refer to Figure 14.13 from the textbook, what is the probability that a 45-year-old auto club member will return the form?

FIGURE 4.13: Tree Diagram for Cartridge Problem Probabilities

a) −1.2384
b) 0.2898
c) 0.8075
d) 0.2247
28. Refer to Figure 14.13 from the textbook, what are the odds that a 45-year-old auto club member will return the form?
a) 0.2898
b) 0.4259
c) 0.8075
d) 0.2247
29. The main differences between linear regression and logistic regression include which of the following?
a) The response variable for a logistic regression model is binary while the response variable for a linear regression model is continuous.
b) Logistic regression models contain indicator variables, while linear regression models do not.
c) Logistic regression models predict the probability of the independent variable being a “success” (1 value) whereas linear regression models predict the value of the independent variable.
d) Both a and c
e) All of the above
30. Which of the following are valid reasons that a multiple regression model cannot be used to predict a binary response?
a) The error terms do not follow a normal distribution.
b) The error terms are not independent.
c) There is heteroscedasticity of error variances.
d) The predicted values would not necessarily be between 0 and 1.
e) All of the above

a) −1.2384 b) 0.2898 c) 0.8075 d) 0.2247 28. Refer to Figure 14.13 from the textbook, what are the odds that a 45-year-old auto club member will return the form? a) 0.2898 b) 0.4259 c) 0.8075 d) 0.2247 29. The main differences between linear regression and logistic regression include which of the following? a) The response variable for a logistic regression model is binary while the response variable for a linear regression model is continuous. b) Logistic regression models contain indicator variables, while linear regression models do not. c) Logistic regression models predict the probability of the independent variable being a “success” (1 value) whereas linear regression models predict the value of the independent variable. d) Both a and c e) All of the above 30. Which of the following are valid reasons that a multiple regression model cannot be used to predict a binary response? a) The error terms do not follow a normal distribution. b) The error terms are not independent. c) There is heteroscedasticity of error variances. d) The predicted values would not necessarily be between 0 and 1. e) All of the above


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> Which of the following descriptive measure is not a statistic? a) Sample mean b) Population mean µ c) Sample standard deviation s d) Sample variance s2 e) Sample median 5. To study the impact of advertising on various market segments, marke

> The payoffs of a decision analysis problem are the payments to decision makers. 2. When it is uncertain which of the states of nature will occur and also the probability of each state of nature occurring is unknown, the scenario is referred to as decisio

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> What is the relative frequency of type B in the previous question? a) 0.25 b) 0.35 c) 0.5 d) 0.64 29. In sciences and technology, use of pie charts is limited compared to other types of graphs such as a histogram, because __________. a) It is difficult

> A null hypothesis must always include the equality sign. 2. If the result of a hypothesis test is statistically significant, it must be considered a substantive result. 3. The null hypothesis is rejected if the p-value (i.e., the probability of getting a

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> Binomial distribution applies only to experiments in which the trials are done with replacement or successive trials are independent. 2. A hypergeometric distribution is used in situations where the sampling is done from an infinite population and the s

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> A histogram is vertical bar chart on an X-Y plane, in which the labels along horizontal (or X) axis represent the class end points and the bars along the vertical (or Y) axis show the ____. a) Class width b) Class range c) Class frequency d) Class mid-

> An approach to decision making under uncertainty that is based on a weighted combination of the maximum and the minimum payoffs from each alternative is called the _____________. a) Maximin criterion b) Maximax criterion c) Hurwicz criterion d) Minimax r

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> Many times in the implementation of quality improvement techniques, it is useful to explore the relationship between two numerical variables (e.g., the strength of steel bars and the carbon content of steel). A graphical mechanism to explore such relatio

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> Consider the data set in the table below, use the Wilcoxon Matched-Pairs Signed-Ranks Test to calculate the test statistic, and the test statistic is __________. a) 28 b) 24 c) 4 d) −24 22. The nonparametric alternative to the one-way

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> The administrator of a large university wants to test if students elected to a large student council were randomly selected from its two campuses, east (E) and west (W). A sequence of 26 consecutive students sampled showed the following pattern: E E E E

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> A business analyst wants to use the chi-square goodness-of-fit test if a uniform distribution is a good fit for the following observed frequencies in eight categories along a single dimension. The desired level of significance is 0.05. The correct decis

> Given a small dataset: 2.3, 7.1, 6.3, 5.8, 4.2, what is the range for this data? a) 1.9 b) 2.5 c) 4.8 d) 2.3 10. A useful tool for grouping data is __________. a) A frequency distribution b) Group dynamics c) Segmentation d) Constructive statistics 11

> A firm believes that the distribution of the economic class of its customers is 25%, 50%, and 25% in the three possible categories (i.e., lower income class, middle-income class, or upper income class). To test if this belief is true, data from a random

> A regression model, Monthly Sales = 750 + 0.20 (Month), was developed to predict the monthly sales (in $1,000s) using the data from the months, 1, 2, …, 12 of the past year. The forecast using this model for the first month of the next year will be _____

> A forecasting technique that is not appropriate for forecasting time-series data that are stationary is __________. a) A naïve forecasting model b) An averaging model c) A simple linear regression model d) An exponential model 12. The techniques used for

> Data gathered on any characteristic of interest (e.g., a company’s sales) over a period of time (e.g., past five or ten years) at regular intervals (e.g., a month or a quarter) is called time-series data. Which of the following elements

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> If the scatter plot of y variable versus x variable shows a parabolic shape, which of the following steps would be appropriate to explore the relationship between the two variables? a) Add two more x variables to the regression model b) Add a log x varia

> In a regression study, a multiple regression model with two explanatory variables is developed using a data set with 23 observations. In the ANOVA table for this model, the sum of squares total (SSyy) is = 12500 and the sum of squares error (SSE) = 3000.

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> If a continuous random variable has a uniform distribution between 20 and 70, the graph of its distribution will be a rectangle with height equal to __________. a) 50 b) 1/50 c) 20 d) 70 3. The values of a random variable are uniformly distributed

> Which of the following is a characteristic of a hypergeometric distribution? a) It is a continuous distribution. b) It has undefined trials c) The outcome of each trial is a success or a failure or undefined. d) Sampling is done without replacement. e)

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> Use the following data to determine the equation of the multiple regression model. Comment on the regression coefficients. Predictor _________ Coefficient Constant …………………… 31,409.5 x1 …………………….………… .08425 x2 …………………….………… 289.62 x3 …………………….………… −.0947

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