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Question
Sometimes a researcher will find that the ANOVA F is not significant in regression analysis or if the F is significant, the R square is lower than desired. It is appropriate in these cases to:A) examine the data using another stat package other than SPSS.
B) change the scaling assumptions from ratio or interval to ordinal and rerun the analysis.
C) run a confidence interval around the predicted values and then make the interval narrower.
D) run a confidence interval around the predicted values and then make the interval wider.
E) run a scatter diagram, search for outliers, and remove them and rerun the regression.
Answer
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Related questions
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If we wanted to use a type of regression that first enters the variable that explains the most variance, then the variable that explains the second highest level of variance and so on, we would use ordinal regression.
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In multiple regression we make a prediction, but we cannot put confidence intervals around our prediction as we can in bivariate regression.
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When you have independent variables that are not significant in multiple regression analysis, it is appropriate to take them out and rerun the regression. The new model is referred to as a "trimmed" model.
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In multiple regression analysis, we are trying to predict an independent variable using more than two dependent variables.
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In regression, the line that runs through the points on a scatter diagram is positioned to minimize the vertical distances away from the line of the various points because of the least squares criterion.
Q:
In regression, the variable being predicted, y, is known as the dependent variable.
Q:
Which form of regression is useful when the researcher has many independent variables and wants to narrow the set down to a smaller number?
A) multiple component reduction
B) stepwise multiple regression
C) variance deflation regression
D) variance inflation regression
E) narrow regression
Q:
What is the proper SPSS command sequence to run multiple regression analysis?
A) ANALYZE; REGRESSION; MULTIPLE; GO
B) ANALYZE; REGRESSION; MULTIPLE
C) ANALYZE; REGRESSION; LINEAR
D) ANALYZE; REGRESSION; MLINEAR
E) ANALYZE; REGRESSION; MR
Q:
In multiple regression, the presence of correlations among the independent variables is termed:
A) independence assumption.
B) multicollinearity.
C) additivity.
D) regression plane.
E) multicorrelation.
Q:
A multiple regression equation is best described by which of the following forms?
A) The independent variable is predicted by the intercept plus a series of values of the slope times each dependent variable.
B) The independent variable is predicted by the slope plus a series of values of the intercept times each dependent variable.
C) The dependent variable is predicted by the intercept plus a series of values of the slope times each independent variable.
D) The dependent variable to be predicted is equal to the intercept plus a series of values of the slope times each independent variable.
E) y =a + bx
Q:
The main purpose of ANOVA in bivariate regression is to:
A) tell us if there are significant differences between three or more means.
B) tell us if ANOVA is an issue.
C) tell us if the straight-line model fits the data we are analyzing.
D) provide a frequency table for further analysis.
E) None of the above; ANOVA is not used in regression.
Q:
Which of the following residuals shows an exact prediction?
A) 0
B) +1.0
C) -25
D) +25
E) 100.0
Q:
Which of the following is NOT true of prediction?
A) It is a statement of what is believed will happen in the future.
B) It may be based on prior observation.
C) We are seldom confronted with the need to make predictions.
D) It may be based on past experience.
E) Marketing managers are constantly faced with the need to make predictions.
Q:
Michelle Steward is a marketing professor at Wake Forest University. Michelle had been asked by the administration to study a sample of classes at Wake to help the university understand the student population better particularly in terms of factors that differentiate students with high versus low GPAs. One of the questions asked was, "What score did you earn (0 to 100) on the last test that you took?" and another question in the study asked, "How much time, estimated in numbers of minutes, did you study for the last test you took?" Michelle decided to run a Pearson product moment correlation analysis on these two questions. When she did, SPSS generated the following output: Pearson Correlation .98; Sig. (2 tailed) .0001. Michelle knew that this meant:
A) there was a significant, nonmonotonic association between the two variables.
B) there was the presence of an association because the probability of supporting the alternative hypothesis is very low, less than 1 percent.
C) there was the presence of a negative association; the probability of supporting the null hypothesis that there is no association is only .01 percent.
D) there was the presence (aka "significant") of a positive, "very strong" association between the variables.
E) None of the above; Michelle should not have run a Pearson product moment correlation because the two variables are both categorical (aka nominal).
Q:
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If we determine a precise linear relationship between two variables, then by knowing the value of one variable we should be able to predict the other variable.
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Let's assume we find in a study that the correlation coefficient between number of years of education and cigarette smoking is -.89. This means that as education level increases:
A) smoking tends to increase.
B) smoking tends to decrease.
C) smoking changes 89 percent.
D) smoking is nonexistent.
E) only 89 out of every 100 people in the study would not smoke.
Q:
Assume that a researcher and client determine that a p value of .05 or less determines significance. Listed below are several correlation coefficients and their respective significance levels. Which correlation coefficient demonstrates an association not likely due to chance; that is, is it significant?
A) .22, .06
B) .75, .05
C) .32, .15
D) .76, .95
E) .05, 1.00
Q:
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A) incomplete response
B) a middle-of-the-road pattern
C) nay-saying pattern
D) nonresponse to specific questions
E) a yea-saying pattern
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Which of the following is a phrase used to identify the percentage of the sample that did not answer a particular question?
A) validation check
B) reversals of scale end-points
C) item omission
D) break-off
E) role-playing
Q:
Which of the following is most likely why prompters are often used during long questionnaires?
A) to avoid misunderstandings
B) to facilitate proper training
C) to control attention loss or fatigue
D) to make sure there is no interviewer cheating
E) to avoid distractions
Q:
________ occurs when the respondent is assured that his or her name will not be associated with his or her answers.
A) Confidentiality
B) Supervision
C) Anonymity
D) Role-playing
E) Validation check
Q:
While taking a survey, Ginny is constantly disturbed by her 10-year-old son, as a result of which she loses track and gives quick responses to all the questions. Which form of unintentional respondent error is evident here?
A) cheating
B) distraction
C) attention loss
D) misunderstanding
E) nonresponse