PRM Logistic Regression

25 Questions

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PRM Logistic Regression


Questions and Answers
  • 1. 
    Logistic Regression (LR) is very similar to ___ except the predictors do not need to be ____.
    • A. 

      MANOVA, normally distributed

    • B. 

      DFA, normally distributed

    • C. 

      ANOVA, normally distributed

    • D. 

      Factor Analysis, normally distributed

    • E. 

      DFA, linear

  • 2. 
    In LR, the DV is a ___ variable, even though it represents a ___ probabilistic occurence of an event occurring.
    • A. 

      Categorical, continuous

    • B. 

      Continuous, categorical

    • C. 

      Dichotomous, categorical

    • D. 

      Interval, continuous

    • E. 

      None of the above

  • 3. 
    The 5 assumptions are (1) independence (2) linearity (3) normality (4) homogeneity of variance & (5) non-multicollinearity. LR does not require:
    • A. 

      1,2,3

    • B. 

      2,3,4

    • C. 

      3,4,5,

    • D. 

      Is flexible with all 5

    • E. 

      Is strict with all 5

  • 4. 
    Which one of the following is TRUE?
    • A. 

      In MANOVA, the dv has to be categorical but an underlying continuous distribution

    • B. 

      In DFA, the dv has to be categorical but an underlying continuous distribution

    • C. 

      In LR, the dv has to be categorical but an underlying continuous distribution

    • D. 

      Standard, statistical & heirarchical regression are all variable selection methods of LR.

    • E. 

      C and d

  • 5. 
    The reduction in uncertainty or the degree of variance we have to explain is represented by: multiple regression uses ____, MANOVA  and ANOVA use ____, and LR uses ____.
    • A. 

      R squared, ss, -2LL

    • B. 

      Ss, ss squared, -2LL

    • C. 

      Ss, r squared, -2LL

    • D. 

      -2LL, ss, r squared

    • E. 

      -2LL, ss squared, r squared

  • 6. 
    Is the following True or False: In research, the significance of a finding is very dependent on sample size, but not effect size. Effect size will stay reliable always.
    • A. 

      True

    • B. 

      False

  • 7. 
    The nagelkerke R squared  is a recommended effect size estimate to use in which statistical modelling?
    • A. 

      MANOVA

    • B. 

      ANOVA

    • C. 

      DFA

    • D. 

      LR

    • E. 

      MR

  • 8. 
    In LR, the exponent of B, EB, tells us that something is NOT a significant predictor, if the EB is ___. In other words, it is equally probable that the skier fell or did not fall.
    • A. 

      1

    • B. 

      Higher than 1

    • C. 

      Lower than 1

    • D. 

      Close to 1

    • E. 

      A fraction of 1

  • 9. 
    In the textbook example: In LR, if the EB is ____ then it is ____ that the skier will fall.
    • A. 

      Below 1, less likely

    • B. 

      Below 1, more likely

    • C. 

      Close to 1, less likely

    • D. 

      Close to 1, more likely

  • 10. 
    The use of EB is particularly pertinent in ___, whereby you are 4.3 times as likely or half as likely to do something.
    • A. 

      Marketing

    • B. 

      Environmental research

    • C. 

      Health research

    • D. 

      Tourism

    • E. 

      Hospitality

  • 11. 
    Nagelkerke's statistic is the ____ which can achieve a value of 1.
    • A. 

      Proportion of variation in the response variable explained by the specific model

    • B. 

      Proportion of variation in the explanatory variable explained by the specific model

    • C. 

      It is used as a measure of effect size

    • D. 

      B and c

    • E. 

      None of the above

  • 12. 
    If in LR you are predicting gender & are using dummy variables 0 and 1 for female and male respectively, the EB understood as a poor predictors will have an EB of ____.
    • A. 

      Close to 1

    • B. 

      Of 1

    • C. 

      Higher than 1

    • D. 

      Less than 1

    • E. 

      None of the above

  • 13. 
    With reference to ques 12, an EB of .9 on 'information' is interpreted as:
    • A. 

      You are less likely to have a high information score if you are male.

    • B. 

      You are less likely to have a high information score if you are female.

    • C. 

      You are equally likely either way.

    • D. 

      The highest reading before 1.

  • 14. 
    In LR it is important to keep an eye on which dummy value is 0 and which is 1. This is:
    • A. 

      True

    • B. 

      False

  • 15. 
    LECTURE 4: MULTIPLE REGRESSION Predicting some dichotomous outcome with variables that are either continuous or dichotomous is:
    • A. 

      MANOVA

    • B. 

      ANOVA

    • C. 

      DFA

    • D. 

      LR

    • E. 

      MR

  • 16. 
    The use of multiple variables to predict 1 variable and the variable being predicted or the DV is a continuous scale variable is:
    • A. 

      ANOVA

    • B. 

      MANOVA

    • C. 

      DFA

    • D. 

      LR

    • E. 

      MR

  • 17. 
    The predictors (IV's) in MR can be:
    • A. 

      Continuous

    • B. 

      Dichotomous

    • C. 

      A and b

    • D. 

      Categorical

    • E. 

      Whatever you like

  • 18. 
    The number of predictors do matter in terms of bringing up the R squared and bringing down the F value in MR is:
    • A. 

      False

    • B. 

      True

  • 19. 
    The usefulness of any single predictor will be gauged by its semi-partial correlation (SR). Is this true or false?
    • A. 

      False

    • B. 

      True

  • 20. 
    The general linear model, is:
    • A. 

      The observed data times what you can model plus eror

    • B. 

      Quite simply, the observed data is the result of what you can model plus error

    • C. 

      Error plus any data and model varianace

    • D. 

      Is an interplay between variance and error variance

    • E. 

      None of the above

  • 21. 
    The difference between an ANOVA and a correlational design is that the ANOVA is ____ and ____ whilst the correlational design is  ____.
    • A. 

      Structured, involved, relative.

    • B. 

      Experimental, looking for an effect, trying to prove relationships.

    • C. 

      Experimental, looking for an effect, not looking for an effect.

    • D. 

      Non-experimental, causal, not looking for an effect.

    • E. 

      Non-experimental, looking for an effect, trying to prove relationships.

  • 22. 
    Standard MR uses ____ predictors, statistical regression uses ____, whilst hierarchical regression uses ____.
    • A. 

      All, some, few.

    • B. 

      All, minimum, subset.

    • C. 

      All, some, subset.

    • D. 

      All, best, subset.

    • E. 

      They all use the same number of IV's.

  • 23. 
    Efficiency of predictors is a pretty important consideration when using MR. This is predominantly because of its placement in the numerator.This is:
    • A. 

      True

    • B. 

      False

  • 24. 
    In MR, what order do we check out (1) descriptive stats (2) inferential stats of predictors & (3) inferential statistics of equation?
    • A. 

      3,2,1

    • B. 

      1,2,3

    • C. 

      2,1,3

    • D. 

      3,1,2

    • E. 

      1,3,2

  • 25. 
    LECT 4: Unique contributions of particular predictors (ie X1 alone & X2 alone) are ___ and joint contributions ___ assigned to any particular predictor.
    • A. 

      Semi-partial correlation, are not

    • B. 

      Partial correlation, are not

    • C. 

      Semi-partial correlation, are

    • D. 

      Partial-correlation, are