Quiz (Chapter 16)


Bivariate, Multiple, and Logistic Regression

Introduction
  1. Though regression is related to correlation, the former has a different purpose than the latter.
    2. True
    False
  2. In some studies, regression is used to "predict"; in other studies, regression is used to "_____."
    3. adjust
    explain
    hypothesize
    prove
  3. Which of the following is not a synonym for "dependent variable"?
    criterion variable
    outcome variable
    predictor variable
    response variable
  4. Excerpt 16.4 has __ predictor variable(s) and __ criterion variable(s).

    5. 1; 6
    6: 1

    4; 6
    6; 4
  5. Which kind of analysis allows for more inferential tests, a correlational analysis or a regression analysis?
    6. A correlational analysis
    A regression analysis
Bivariate Regression
  1. Bivariate regression is used more often to "predict" than to "explain."
    2. True
    False
  2. In a scatter diagram created for Excerpt 16.3, which variable's name would be used to label the ordinate?
    3. Antioxidant intake
    Baseline MMSE score
  3. If bivariate regression is used to predict, predictions are made of the ____ variable.
    4. dependent
    independent
  4. In bivariate regression, the "regression line" and the "line of best fit" refer to the same line.
    5. True
    False
  5. In a regression equation, the regression coefficient is represented by the letter __.
    6. a
    b
    r
    x
    y
  6. Using the regression equation on page 413, what would Sam's predicted "down time" be if his age was 32?
    7. 3.59 days
    13.69 days
    26.95 days
    37.05 days
  7. In Excerpt 16.6, what is the dependent variable?

    8. Arm span
    Height
    Age
    Gender
  8. In standardized regression equations, the beta weight is very similar to a regression coefficient.
    9. True
    False
  9. In a regression equation, the term "a" indicates the regression line's _____ while "b" indicates its _____.
    10. slope; intercept
    intercept; slope
  10. A regression equation's ability to predict well is given by r, for it equals the correlation between Y' and __.
    11. X
    Y
    Z
  11. The proportion of variability in the dependent variable that's "explained" by variability in the independent variable is equal to ___.
    12. a2
    b2
    r2
  12. In most regression analyses, a, b, and r are viewed as sample statistics, not population parameters.
    13. True
    False
  13. If, in Excerpt 16.10, the inferential test had focused on r (rather than b), the outcome would have been the same.
    14. True
    False
  14. In Excerpt 16.19, Total Perceived Support the _______ variable.
    15. independent
    dependent
Multiple Regression
  1. In a multiple regression, there will always be __ dependent variable(s) and __ independent variable(s).
    2. 1; 2 or more
    2 or more; 1
    2; 2 or more
    2 or more; 2
  2. In Excerpt 16.12, what is/are the numerical value(s) of the regression coefficient(s)?
    3. 6.34
    7.06
    4.17
    7.06 and 4.17
    6.34, 7.06, and 4.17
  3. Excerpts 16.13 and 16.14 show that it ___ possible to compare beta weights.
    4. is
    is not
  4. A standardized regression equation has _____ rather than regression coefficients, each symbolized as ___.
    5. alpha coefficients; a
    beta coefficients; b
    eta coefficients; h
    lambda coefficients; l
  5. If used as an independent variable, _____ would be a dummy variable?
    height
    gender
    income
    heart rate
  6. The 3 main types of multiple regression are called "simultaneous multiple regression," "stepwise multiple regression," and "___________ multiple regression."
    7. actuarial
    hierarchical
    splintered
    standardized
  7. Does a researcher determine the "entry order" of independent variables in stepwise multiple regression?
    8. Yes
    No
  8. The multiple correlation coefficient is symbolized by ___.
    9. r
    r2
    R
    R2
  9. The concept of DR2 does not apply to which kind of multiple regression?
    Simultaneous multiple regression
    Stepwise multiple regression
    Hierarchical multiple regression
  10. Adjusted R2 will be _____ than R2 because of anticipated ______.
    11. smaller; attrition
    larger; attrition
    smaller; shrinkage
    larger; shrinkage
  11. In Excerpt 16.22, how many of the 5 independent variables were involved in the model that produces an R2 value of .50?
    12. 2
    3
    4
    5
  12. In Excerpt 16.21, the number in step 3 for "additional variance accounted for" should have been ___, not 4%.
    13. 2%
    3%
    4%
    5%
Logistic Regression
  1. Logistic regression is used exclusively within the fields of medicine, health, and epidemiology.
    2. True
    False
  2. A subset of the independent variables, each called a ______, is typically included for "control" purposes.
    3. adjuster
    covariate
    guard
    placebo
  3. Logistic regression is like bivariate or multiple regression in that there is only 1 dependent variable.
    4. True
    False
  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. Mother's age
    Length of labor
    Baby's sex
  5. What are the odds against getting two heads if you flip a fair coin twice?
    6. 2 to 1
    3 to 1
    4 to 1
  6. The concept of an "odds ratio" is involved in logistic regression but not in multiple regression.
    7. True
    False
  7. If the number 200 in Figure 16.2 had been 400 instead, the OR for females watching Program B would be __.
    8. 2
    4
    8
    10
    12
  8. The lowest possible OR is 1.00.
    9. True
    False
  9. If a logistic regression involves 4 independent variables, how many odds ratios will there be?
    10. 1
    2
    3
    4
    5
  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 a(n) "_____" OR.
    11. adjusted
    comprehensive
    global
    neutralized
    standardized
  11. In Excerpt 16.26, the first OR turned out to be statistically significant because 0.150 was quite different, statistically speaking, from the null hypothesis number that was set equal to
    12. 0
    .01
    .85
    1
  12. In logistic regression, the main tests of significance focus on _____.
    the individual ORs
    the full regression equation
    the slope of the regression line
  13. An OR equal to __ would mean that membership in the two categories of the dependent variable is unrelated to the independent variable under consideration.
    14. -1
    0
    1
    50
    100
  14. What is the name of the test procedure that determines whether a particular OR is statistically significant?
    15. The OR test
    The LR test
    The Snyder test
    The Murphy test
    The Wald test
Final Comments
  1. The issue of "multicollinearity" arises when ___ correlations exist among independent variables.
    2. low
    high
  2. In hierarchical multiple regression and logistic regression, efforts at "control" don't work perfectly.
    3. True
    False
  3. The results shown in Excerpt 16.30 demonstrate a causal link between immigrant status and the likelihood that mothers will breastfeed their children.
    4. True
    False

 

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