Accounting
Anthropology
Archaeology
Art History
Banking
Biology & Life Science
Business
Business Communication
Business Development
Business Ethics
Business Law
Chemistry
Communication
Computer Science
Counseling
Criminal Law
Curriculum & Instruction
Design
Earth Science
Economic
Education
Engineering
Finance
History & Theory
Humanities
Human Resource
International Business
Investments & Securities
Journalism
Law
Management
Marketing
Medicine
Medicine & Health Science
Nursing
Philosophy
Physic
Psychology
Real Estate
Science
Social Science
Sociology
Special Education
Speech
Visual Arts
Question
Row cell percentage is calculated by dividing a cell frequency by the cell row total.Answer
This answer is hidden. It contains 4 characters.
Related questions
Q:
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.
Q:
There is a type of multiple regression, called stepwise multiple regression, that does the trimming operation automatically.
Q:
In multiple regression we make a prediction, but we cannot put confidence intervals around our prediction as we can in bivariate regression.
Q:
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.
Q:
In multiple regression analysis, we are trying to predict an independent variable using more than two dependent variables.
Q:
The R Square value is very important because it tells us how well our regression line fits the scatter of data points. It may range from 0 to +1.00 because it is the square of the correlation coefficient, which may range from -1.00 to +1.00.
Q:
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:
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.
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:
The Pearson product moment correlation measures the linear relationship between two interval-scaled and/or ratio-scaled variables.
Q:
Covariation is defined as the amount of change in one variable systematically associated with a change in another variable.
Q:
The degrees of freedom in chi-square are calculated by multiplying the rows, minus one times the columns, minus one.
Q:
In the chi-square analysis, the greater the differences between the observed frequencies and the expected frequencies, the less likely it is that there will be a statistically significant relationship.
Q:
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.
Q:
Coffee orders at a restaurant are present at breakfast and soft drink orders are present at lunch. This is an example of a monotonic relationship.
Q:
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:
When a respondent indicates "no opinion" to most of the questions, which of the following categories does he or she fall in?
A) incomplete response
B) a middle-of-the-road pattern
C) nay-saying pattern
D) nonresponse to specific questions
E) a yea-saying pattern
Q:
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