Deck 20: Logistic Regression
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Deck 20: Logistic Regression
1
How would you request a logistic regression analysis in SPSS?
A) Analyze → Nonparametric → Binomial
B) Analyze → Regression → Ordinal
C) Analyze → Regression → Binary Logistic
D) Analyze → Loglinear → General
A) Analyze → Nonparametric → Binomial
B) Analyze → Regression → Ordinal
C) Analyze → Regression → Binary Logistic
D) Analyze → Loglinear → General
Analyze → Regression → Binary Logistic
2
You are proofreading a new business statistics book for a close friend. He lists the following as functions of logistic regression, but you suspect one is not accurate. Which?
A) Predict a dependent variable on the basis of several independent variables
B) Determine the variance in the dependent variable explained by the independent variables
C) Rank the relative importance of independent variables
D) Assess the impact of covariate control variables
A) Predict a dependent variable on the basis of several independent variables
B) Determine the variance in the dependent variable explained by the independent variables
C) Rank the relative importance of independent variables
D) Assess the impact of covariate control variables
Rank the relative importance of independent variables
3
To predict a person's occupation by their income, lawyers are coded as 0 and accountants as 1. If there are 100 cases and 40 are accountants, what is the mean of the variable?
A) 40
B) 0.4
C) 2.5
D) 25
A) 40
B) 0.4
C) 2.5
D) 25
0.4
4
Which of the following statements is not true about the Wald statistic?
A) The Wald statistic assesses the individual contribution of a predictor variable in a logistic regression model.
B) The Wald statistic tends to be biased when the regression coefficient is large.
C) The Wald statistic is equivalent to the t-statistic in multiple regression.
D) The Wald statistic has a t-distribution.
A) The Wald statistic assesses the individual contribution of a predictor variable in a logistic regression model.
B) The Wald statistic tends to be biased when the regression coefficient is large.
C) The Wald statistic is equivalent to the t-statistic in multiple regression.
D) The Wald statistic has a t-distribution.
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5
In the above example, the mean is also equal to?
A) The mode
B) The probability of randomly drawing an accountant
C) The median
D) The probability of drawing a lawyer
A) The mode
B) The probability of randomly drawing an accountant
C) The median
D) The probability of drawing a lawyer
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6
Very high standard errors in parameter estimates in logistic regression suggest evidence of?
A) Shrinkage
B) Multicollinearity
C) An outlier
D) A dummy variable
A) Shrinkage
B) Multicollinearity
C) An outlier
D) A dummy variable
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7
A marketing consultant would like to analyse whether an advertisement is recalled or not by a group of consumers, predicted by the number of hours of television they watch. He has received various pieces of advice from colleagues. Which should he listen to?
A) Logistic regression is not suitable with this predictor variable.
B) Logistic regression is not suitable as the dependent variable only has two categories.
C) Logistic regression is not suitable as only one predictor variable is postulated.
D) Logistic regression is perfectly acceptable for this model.
A) Logistic regression is not suitable with this predictor variable.
B) Logistic regression is not suitable as the dependent variable only has two categories.
C) Logistic regression is not suitable as only one predictor variable is postulated.
D) Logistic regression is perfectly acceptable for this model.
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8
You have a dependent variable with three categories - low, medium and high emotion advertising. What is an alternative to logistic regression in this instance?
A) Binomial regression
B) Logit regression
C) Legit regression
D) Multinomial regression
A) Binomial regression
B) Logit regression
C) Legit regression
D) Multinomial regression
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9
The same friend has produced another list. Which of the following is true about logistic regression?
A) It estimates values in the outcome variable.
B) It estimates a probability that the outcome variable assumes a certain value.
C) It estimates probabilities in the outcome variable.
D) It estimates the probabilities that the predictor variables assume certain values.
A) It estimates values in the outcome variable.
B) It estimates a probability that the outcome variable assumes a certain value.
C) It estimates probabilities in the outcome variable.
D) It estimates the probabilities that the predictor variables assume certain values.
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10
Large log-likelihood values do not show or represent?
A) The extent of the relationship between independent and dependent variables.
B) That there are a large number of unexplained observations in the data.
C) That there is a large measure of deviance.
D) That the model is a good fit.
A) The extent of the relationship between independent and dependent variables.
B) That there are a large number of unexplained observations in the data.
C) That there is a large measure of deviance.
D) That the model is a good fit.
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11
Logistic regression is used when you want to?
A) Predict a continuous variable from dichotomous ones.
B) Predict a dichotomous variable from continuous or dichotomous variables.
C) Predict any categorical variable from other categorical variables.
D) Predict a continuous variable from dichotomous or continuous variables.
A) Predict a continuous variable from dichotomous ones.
B) Predict a dichotomous variable from continuous or dichotomous variables.
C) Predict any categorical variable from other categorical variables.
D) Predict a continuous variable from dichotomous or continuous variables.
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12
A researcher is interested in predicting whether a company might attempt to buy out a competitor (score = 1) or not (score = 0), using market share (%) as an independent variable. She establishes that the value of 'exp(B)' is 2.56. How should she interpret this?
A) If two companies have a market share that differs by 1 unit, then the odds of the company with the higher score attempting a takeover are 2.56 higher than for the other company.
B) 2.56 times more companies who attempted takeovers scored highly on market share.
C) If two companies have market share scores that differ by 1 unit, then the odds of the company with the higher score attempting a takeover are 2.56 lower than for the other company.
D) Takeover rates are 2.56 times as high in companies with a large share of their market.
A) If two companies have a market share that differs by 1 unit, then the odds of the company with the higher score attempting a takeover are 2.56 higher than for the other company.
B) 2.56 times more companies who attempted takeovers scored highly on market share.
C) If two companies have market share scores that differ by 1 unit, then the odds of the company with the higher score attempting a takeover are 2.56 lower than for the other company.
D) Takeover rates are 2.56 times as high in companies with a large share of their market.
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13
In logistic regression, the values of the parameters are estimated using?
A) Maximum-likelihood probability
B) Minimum-likelihood estimation
C) Minimum-likelihood probability
D) Maximum-likelihood estimation
A) Maximum-likelihood probability
B) Minimum-likelihood estimation
C) Minimum-likelihood probability
D) Maximum-likelihood estimation
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14
Which of the following is not a research question that should be investigated with logistic regression?
A) Prediction of group membership
B) Strength of association between criterion and predictors
C) Differences between groups
D) Interaction between predictors
A) Prediction of group membership
B) Strength of association between criterion and predictors
C) Differences between groups
D) Interaction between predictors
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15
The odds of an event are?
A) The ratio of the probability for an event not happening to the probability of the event happening.
B) The ratio of the probability for an event happening to the probability of the event not happening.
C) The probability of an event occurring.
D) None of the above.
A) The ratio of the probability for an event not happening to the probability of the event happening.
B) The ratio of the probability for an event happening to the probability of the event not happening.
C) The probability of an event occurring.
D) None of the above.
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16
The odds ratio is?
A) The natural log to the bth power, where b is the unstandardized parameter estimate.
B) The natural log to the bth power, where b is the standardized parameter estimate.
C) The base 10 log to the bth power, where b is the unstandardized parameter estimate.
D) The base 10 log to the bth power, where b is the standardized parameter estimate.
A) The natural log to the bth power, where b is the unstandardized parameter estimate.
B) The natural log to the bth power, where b is the standardized parameter estimate.
C) The base 10 log to the bth power, where b is the unstandardized parameter estimate.
D) The base 10 log to the bth power, where b is the standardized parameter estimate.
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17
In logistic regression, the dependent variable is called a logit, which is?
A) The natural log of the odds
B) The rolling mean
C) A log rolling
D) A mean log
A) The natural log of the odds
B) The rolling mean
C) A log rolling
D) A mean log
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