Quiz (Chapter 16)

Bivariate, Multiple, and Logistic Regression


  1. (T/F) Though regression is related to correlation, the former has a different purpose than the latter.
  2. In some studies, regression is used to "predict"; in other studies, regression is used to "_____."
  3. What are 3 synonyms for "dependent variable"? What are 2 synonyms for "independent variable"?
  4. Excerpt 16.6 has how many predictor variables? How many criterion variables?
  5. Which kind of analysis allows for more inferential tests, a correlational analysis or a regression analysis?

Bivariate Regression
  1. (T/F) Bivariate regression is used more often to "predict" than to "explain."
  2. If a scatter diagram were to be created for Excerpt 16.3, which variable's name would be used to label the ordinate?
  3. If bivariate regression is used to predict, predictions are made of the ____ (independent/dependent) variable.
  4. In bivariate regression, the "regression line" and the "line of best fit" ___ (do/don't) refer to the same line.
  5. In a regression equation, the regression coefficient is represented by the letter __.
  6. Using the regression equation on page 374, what would Sam's predicted "down time" be if his age was 32?
  7. In Excerpt 16.4, what is the criterion variable?
  8. (T/F) In standardized regression equations, the beta weight is very similar to a regression coefficient.
  9. In a regression equation, the term "a" indicates the regression line's _____ while "b" indicates its _____.
  10. A regression equation's ability to predict well is given by r, for it equals the correlation between Y ' and __.
  11. r2 indicates the proportion of variability in the ______ that's "explained" by variability in the ______.
  12. (T/F) In most regression analyses, a, b, and r are viewed as sample statistics, not population parameters.
  13. (T/F) If, in Excerpt 16.8, the inferential test had focused on r (rather than b), the outcome would have been the same.
  14. If, in Excerpt 16.7, r had been equal to .80 (rather than .93), the predictor would have explained __% of the variance in running performance.

Multiple Regression
  1. In multiple regression, how many independent variables will there be? How many dependent variables?
  2. In Excerpt 16.9, what is/are the numerical value(s) of the regression coefficient(s)?
  3. Excerpt 16.11 shows that beta weights ____ (can/cannot) be compared.
  4. A standardized regression equation has _____ rather than regression coefficients, each symbolized as ___.
  5. If used as an independent variable, _____ would be a dummy variable?
    1. height
    2. gender
    3. income
  6. What 3 terms are used to distinguish the 3 main types of multiple regression from one another?
  7. Does a researcher determine the "entry order" of independent variables in stepwise multiple regression?
  8. How does a researcher represent the multiple correlation coefficient? Is it usually squared or left as is?
  9. Is it possible to compute DR2 for a simultaneous multiple regression? For a hierarchical multiple regression?
  10. Adjusted R2 will be _____ (smaller/larger) than R2 because of anticipated ______.
  11. In Excerpt 16.16, what was the value of R2 at the end of Step 2?
  12. In Excerpt 16.18, how many models were there in the hierarchical multiple regression?

Logistic Regression
  1. (T/F) Logistic regression is used exclusively within the fields of medicine, health, and epidemiology.
  2. A subset of the independent variables, each called a ______, is typically included for "______" purposes.
  3. (T/F) Logistic regression is like bivariate or multiple regression in that there is only 1 dependent variable.
  4. Would "mother's age" (measured in years), "length of labor" (measured in hours), or "baby's sex" (male or female) be the dependent variable in a logistic regression?
  5. What are the odds against getting two heads if you flip a fair coin twice?
  6. (T/F) The concept of an "odds ratio" is involved in logistic regression but not in multiple regression.
  7. If the number 200 in Figure 16.3 had been 400 instead, the OR for females watching Program B would be __.
  8. (T/F) The lowest possible OR is 1.00.
  9. If a logistic regression involves 4 independent variables, how many odds ratios will there be?
  10. If an odds ratio is computed for a particular independent variable, and if that particular OR takes into consideration the other independent variables, then it is called an "_____" OR.
  11. In Excerpt 16.25, stroke severity was a significant predictor because the OR of 1.24 was quite far away, statisticall speaking, from the null hypothesis number that was equal to ___ .
    1. 0
    2. .01
    3. 1.0
    4. 10
  12. In logistic regression, the main tests of significance focus on _____.
    1. individual ORs
    2. the full regression equation
    3. the slope of the regression line
  13. An OR equal to __ (what number?) would mean that membership in the two categories of the dependent variable is unrelated to the independent variable under consideration.
  14. What is the name of the test procedure that determines whether a particular OR is statistically significant?

Final Comments
  1. The issue of "multicollinearity" arises when ___ (low/high) correlations exist among independent variables.
  2. (T/F) In hierarchical multiple regression and logistic regression, efforts at "control" don't work perfectly.
  3. (T/F) If important variables are overlooked in a regression analysis, or if irrelevant variables are included, the regression model is said to be "imploded."

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