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Unformatted text preview: predicted values of the dependent variable 40. In regression analysis, the standard error (s) is _________ greater than the standard
deviation of y (the dependent variable).
A. Always
B. Sometimes
C. Never 41. In a multiple regression analysis, if the normal probability plot ____________, then it can
be concluded that the assumption of normality is not violated.
A. Is a straight line
B. Has the shape of a symmetric bell shaped curve
C. Is greatly curved
D. Is left skewed
E. Has the shape of a parabola that opens upward 42. Which one of the following tools is not used to check the normality of residuals
assumption for a multiple regression model?
A. Histogram
B. Stemandleaf display
C. Scatter diagram
D. Normal plot 43. If we are testing the significance of the independent variable X1 and we reject the null
hypothesis H0: β1 = 0, we conclude that:
A. X1 is significantly related to y.
B. X1 is not significantly related to y.
C. X1 is an unimportant independent variable.
D. β1 is significantly related to the dependent variable y. 11310 Chapter 01  An Introduction to Business Statistics 44. In using the multiple regression method, we can model the effects of the different levels of
a qualitative independent variable by using a(n):
A. Interaction variable
B. Crossproduct term
C. Quadratic term
D. Dummy (indicator) variable
E. Variance equalizing transformation 45. A particular multiple regression model has 3 independent variables, the sum of the
squared error is 7680, and the total number of observations is 34. What is the value of the
standard error of estimate?
A. 256
B. 232.72
C. 225.89
D. 16
E. 15.03 46. The multiple _________ measures the proportion of the variation in y (response variable)
explained by the multiple regression model or the set of independent variables included in the
multiple regression equation.
A. Correlation coefficient
B. Coefficient of determination
C. Total variation
D. Standard error
E. F test 47. _____ variation is the sum of explained variation plus the sum of unexplained variation.
A. Explained
B. Unexplained
C. Error
D. Total 11311 Chapter 01  An Introduction to Business Statistics 48. Dummy or indicator variables typically are values of zero or one, and are used to model
the effects of different levels of _____ variables.
A. Qualitative
B. Quantitative
C. Ratio
D. Measured 49. The _____ term describes the effects on y of all factors other than the independent
variables in a multiple regression model.
A. Dependent
B. ttest
C. Error
D. Dummy 50. The y intercept (β0) in a multiple regression model represents the estimated value of the
________ variable, when the value of all independent variables is/are _______.
A. Response, one
B. Dummy, zero
C. Response, zero
D. Dummy, one 51. The difference between the observed values of y and the predicted value of y is referred to
as a/an _____.
A. Dependent variable
B. Predicted value
C. Residual
D. Explained variation 52. The effects of different levels of qualitative independent variables are described using
_____ variables.
A. Dependent
B. Response
C. Dummy
D. Quantitative 11312 Chapter 01  An Introduction to Business Statistics 53. The range of the previously observed combinations of values of the independent variables
is referred to as the _____.
A. Area under the normal curve
B. Residual
C. Experimental region
D. Correlation coefficient 54. Dummy variables take on the values of ______ and are used to model the effects of
different levels of qualitative variables.
A. 1 or 1
B. 1 or 2
C. 0 or 2
D. 0 or 1 55. Consider the following partial computer output for a multiple regression model. The calculated value of the t statistic for X1 is ________.
A. 2.325
B. 2.325
C. 0.4301
D. 0.4301 56. In a multiple regression model, the explained sum of squares divided by the total sum of
squares yields the ___________.
A. F model
B. t statistic
C. R
D. R2 11313 Chapter 01  An Introduction to Business Statistics 57. In a multiple regression model, a point estimate of σ2 is called the ________________
error.
A. standard
B. regression
C. mean square
D. multiple regression 58. In a multiple regression analysis, if the normal probability plot is a ____________, then it
can be concluded that the assumption of normality is not violated.
A. Normal curve
B. Straight line
C. Parabola
D. Curved line 59. Plotting the residuals in a timeordered sequence will reveal possible violations of the
__________ of error terms assumption.
A. Normality
B. Independence
C. Constant variation
D. Residual sum 60. In a multiple regression model the residuals were plotted against the values of one of the
independent variables. The plot exhibited a funneling out pattern of residuals. This means that
as the value of the independent variable increases, the error terms tend to ________ and the
model assumption of ________ is violated.
A. increase, constant variance
B. increase, independence
C. decrease, constant variance
D. decrease, normality 11314 Chapter 01  An Introduction to Business S...
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 Winter '14

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