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QMB 3200 Exam 3 WITH COMPLETE QUESTIONS AND ANSWERS
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QMB 3200 Exam 3 WITH COMPLETE QUESTIONS AND ANSWERSQMB 3200 Exam 3 WITH COMPLETE QUESTIONS AND ANSWERSQMB 3200 Exam 3 WITH COMPLETE QUESTIONS AND ANSWERSA graph of the standardized residuals plotted against values of the normal scores that helps to determine whether the assumption that the error te...

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  • November 5, 2024
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  • 2024/2025
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  • qmb 3200 exam 3
  • qmb 3200 exam 3 with complete questions and answer
  • a graph of the standardized residuals plotted agai

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QMB 3200 Exam 3 WITH COMPLETE
QUESTIONS AND ANSWERS
A graph of the standardized residuals plotted against values of the normal scores that
helps to determine whether the assumption that the error term has a normal probability
distribution appears to be valid is called a: - ANSWER-normal probability plot

The tests of significance in regression analysis are based on assumptions about the
error term ɛ . One such assumption is that the variance of ɛ, denoted by 𝝈2, is: -
ANSWER-the same for all values of x

identify independent and dependent variables between advertising and sales -
ANSWER-The independent variable is the advertising expenses, and the dependent
variable is sales.

In regression analysis, the variable that is being predicted is the: - ANSWER-dependent
variable

The tests of significance in regression analysis are based on assumptions about the
error term ɛ. One such assumption is that the error term follows ɛ a(n) _____ distribution
for all values of x - ANSWER-normal

Influential observations always: - ANSWER-none of the above

When studying the relationship between two quantitative variables, an interval estimate
of the mean value of y for a given value of x is called a(n): - ANSWER-confidence
interval

When constructing a confidence or a prediction interval to quantify the relationship
between two quantitative variables, the appropriate degrees of freedom are: -
ANSWER-n-2

The value of the coefficient of correlation (r): - ANSWER-can be equal to the value of
the coefficient of determination (r2).

An F test, based on the F probability distribution, can be used to test for: - ANSWER-
significance in regression

The coefficient of determination: - ANSWER-cannot be negative

The mathematical equation relating the independent variable to the expected value of
the dependent variable, , is known as the: - ANSWER-regression equation

, Suppose a residual plot of x verses the residuals, y - ŷ, shows a non-constant variance.
In particular, as the values of x increase, suppose that the values of the residuals also
increase. This means that: - ANSWER-as the values of x get larger, the ability to predict
y becomes less accurate.

An observation that has a strong influence or effect on the regression results is called
a(n): - ANSWER-influential observation

The tests of significance in regression analysis are based on assumptions about the
error term ɛ. One such assumption is that the error term follows ɛ a(n) _____ distribution
for all values of x. - ANSWER-normal

Larger values of r2 imply that the observations are more closely grouped about the: -
ANSWER-least squares line

If a significant relationship exists between x and y and the coefficient of determination
shows that the fit is good, the estimated regression equation should be useful for: -
ANSWER-estimation and prediction

The tests of significance in regression analysis are based on assumptions about the
error term ɛ. One such assumption is that the error term ɛ is a random variable with a
mean or expected value of: - ANSWER-0

In a regression analysis, the error term ε is a random variable with a mean or expected
value of - ANSWER-zero.

The tests of significance in regression analysis are based on several assumptions about
the error term ɛ. Additionally, we make an assumption about the form of the relationship
between x and y. We assume that the relationship between x and y is: - ANSWER-
linear

If a residual plot of x versus the residuals, y - ŷ, shows a non-linear pattern, then we
should conclude that: - ANSWER-the regression model is not an adequate
representation of the relationship between the variables.

The difference between the observed value of the dependent variable and the value
predicted using the estimated regression equation is called a(n): - ANSWER-residual

the value of sb1 - ANSWER-std deviation, temp

if x and y are linearly related, - ANSWER-B1 ≠ 0

coefficient of determination - ANSWER-r2 = SSR/(SSE + SSR)

The model developed from sample data that has the form is known as the: - ANSWER-
estimated regression equation

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