Question 1

How is $R _ { \mathrm { L } } ^ { 2 }$ calculated?

Accepted Answer

A)  $R _ { \mathrm { L } } ^ { 2 } = \frac { - 2 L L ( \text { model } ) } { - 2 L L ( \text { baseline } ) }$ 
B)  $R _ { \mathrm { L } } ^ { 2 } = \frac { 2 L L ( \text { baseline } ) } { 2 L L ( \text { model } ) }$ 
C)  $R _ { \mathrm { L } } ^ { 2 } = \frac { - 2 L L ( \text { baseline } ) } { - 2 L L ( \text { model } ) }$ 
D)  $R _ { \mathrm { L } } ^ { 2 } = \frac { 2 L L ( \text { model } ) } { 2 L L ( \text { baseline } ) }$ 
A)  $R _ { \mathrm { L } } ^ { 2 } = \frac { - 2 L L ( \text { model } ) } { - 2 L L ( \text { baseline } ) }$ 
B)  $R _ { \mathrm { L } } ^ { 2 } = \frac { 2 L L ( \text { baseline } ) } { 2 L L ( \text { model } ) }$ 
C)  $R _ { \mathrm { L } } ^ { 2 } = \frac { - 2 L L ( \text { baseline } ) } { - 2 L L ( \text { model } ) }$ 
D)  $R _ { \mathrm { L } } ^ { 2 } = \frac { 2 L L ( \text { model } ) } { 2 L L ( \text { baseline } ) }$ A

Question 2

Logistic regression can be used to?

Accepted Answer

A) Support the calculations made in the chi-square test 
B) Predict the outcome of a categorical dependent variable based on one or more predictor variables 
C) Confirm the analysis of variance 
D) Minimize human error in calculations involving predictor variables 
A) Support the calculations made in the chi-square test 
B) Predict the outcome of a categorical dependent variable based on one or more predictor variables 
C) Confirm the analysis of variance 
D) Minimize human error in calculations involving predictor variables B

Question 3

You join a research project midway through and are handed the results of a study in which 199 teachers are asked whether or not they think corporal punishment should be used in the classroom.They are given either a 'yes' or 'no' alternative.23 respondents say 'yes',and 176 say 'no'.What type of model will give you the best prediction for the most frequently occurring outcome?

Accepted Answer

A) Bottom line 
B) Baseline 
C) Reduction 
D) Initial 
A) Bottom line 
B) Baseline 
C) Reduction 
D) Initial B

Question 4

What does logistic regression measure?

Accepted Answer

A) The relationship between a categorical dependent variable and a continuous independent variable 
B) The relationship between a continuous dependent variable and a categorical independent variable 
C) The relationship between multiple continuous dependent variables and one categorical independent variable 
D) None of the above 
A) The relationship between a categorical dependent variable and a continuous independent variable 
B) The relationship between a continuous dependent variable and a categorical independent variable 
C) The relationship between multiple continuous dependent variables and one categorical independent variable 
D) None of the above

Question 5

How does logistic regression measure this relationship?

Accepted Answer

A) By converting the independent variable to probability scores 
B) By converting the dependent variable to probability scores 
C) By converting the independent variable to a fixed value 
D) By converting the dependent variable to a fixed value 
A) By converting the independent variable to probability scores 
B) By converting the dependent variable to probability scores 
C) By converting the independent variable to a fixed value 
D) By converting the dependent variable to a fixed value

Question 6

What is complete separation in logistic regression?

Accepted Answer

A) When the dependent variable negatively influences the independent variable 
B) When the plot of the dependent and independent variables do not intersect 
C) When the outcome variable can be perfectly predicted by one other variable,or a combination of other variables 
D) The use of standard errors to predict the outcome variable 
A) When the dependent variable negatively influences the independent variable 
B) When the plot of the dependent and independent variables do not intersect 
C) When the outcome variable can be perfectly predicted by one other variable,or a combination of other variables 
D) The use of standard errors to predict the outcome variable

Question 7

In the z-statistic equation,when the regression coefficient (b)is large,the standard error can be inflated,resulting in an underestimated z-statistic.What does an inflated standard error increase the probability of?

Accepted Answer

A) Producing a significant standard deviation 
B) Rejecting the null hypothesis 
C) Rejecting a predictor as being significant,when in reality it is making a significant contribution to the model 
D) Nothing,it has no effect. 
A) Producing a significant standard deviation 
B) Rejecting the null hypothesis 
C) Rejecting a predictor as being significant,when in reality it is making a significant contribution to the model 
D) Nothing,it has no effect.

Question 8

There are two types of logistic regression,differentiated by the number of categorical outcomes trying to be predicted.What are they?

Accepted Answer

A) Egocentric and multivariate 
B) Binomial and multinomial 
C) Binary and multivariate 
D) Binary and multinomial 
A) Egocentric and multivariate 
B) Binomial and multinomial 
C) Binary and multivariate 
D) Binary and multinomial

Question 9

In logistic regression,what is the R-statistic?

Accepted Answer

A) The partial correlation between the outcome variable and each of the predictor variables 
B) The partial correlation between the predictor variables and each of the outcome variables 
C) The full correlation between the outcome variables and each of the predictor variables 
D) The full correlation between the predictor variables and each of the outcome variables 
A) The partial correlation between the outcome variable and each of the predictor variables 
B) The partial correlation between the predictor variables and each of the outcome variables 
C) The full correlation between the outcome variables and each of the predictor variables 
D) The full correlation between the predictor variables and each of the outcome variables

Question 10

The log-likelihood statistic is analogous to what in multiple regression,as an indicator of the amount of unexplained information after a model has been fitted?

Accepted Answer

A) The residual sum of squares 
B) The number of degrees of freedom present 
C) The unique variance score 
D) The quality control 
A) The residual sum of squares 
B) The number of degrees of freedom present 
C) The unique variance score 
D) The quality control

Question 11

A synonym for the z-statistic is the what?

Accepted Answer

A) Poisson regression 
B) Wald statistic 
C) Kuder-Richardson formula 20 
D) Odds ratio 
A) Poisson regression 
B) Wald statistic 
C) Kuder-Richardson formula 20 
D) Odds ratio

Question 12

How does logistic regression differ from discriminant analysis?

Accepted Answer

A) It doesn't; they are one and the same. 
B) Discriminant analysis separates two groups using several predictors,whereas logistic regression can be used to separate multiple groups. 
C) Logistic regression separates two groups using several predictors,whereas discriminant analysis can be used to separate multiple groups. 
D) None of the above. 
A) It doesn't; they are one and the same. 
B) Discriminant analysis separates two groups using several predictors,whereas logistic regression can be used to separate multiple groups. 
C) Logistic regression separates two groups using several predictors,whereas discriminant analysis can be used to separate multiple groups. 
D) None of the above.

Question 13

What is the equation for deviance?

Accepted Answer

A) Deviance = log-likelihood 
B) Deviance = log-likelihood/2 
C) Deviance = 2 × log-likelihood 
D) Deviance = -2 × log-likelihood 
A) Deviance = log-likelihood 
B) Deviance = log-likelihood/2 
C) Deviance = 2 × log-likelihood 
D) Deviance = -2 × log-likelihood

Question 14

The z-statistic is used to discover whether a variable is an accurate predictor of an outcome.

Accepted Answer

A) True 
 B)False

Question 15

You are carrying out a study into an area of research in which no previous relevant studies exist,and causality is not your primary concern.You are only intending to find a model to fit your data.What type of method would you employ for theory testing?

Accepted Answer

A) Likelihood ratio method 
B) A simple regression 
C) Forward method 
D) Stepwise method 
A) Likelihood ratio method 
B) A simple regression 
C) Forward method 
D) Stepwise method

Question 16

The fundamental difference between linear regression and logistic regression is that in linear regression it is possible to predict possible values,whereas in logistic regression it is the probability that a value will occur which is predicted.

Accepted Answer

A) True 
 B)False

Question 17

If logistic regression and discriminant function analysis are different ways of achieving the same result,then why would a researcher prefer logistic regression?

Accepted Answer

A) There are much more restrictive assumptions associated with logistic regression,meaning calculations are more robust. 
B) There are much fewer restrictive assumptions associated with logistic regression,and it is generally more robust. 
C) There are much more restrictive assumptions associated with logistic regression,which mean it is a simpler test to administer. 
D) None of the above. 
A) There are much more restrictive assumptions associated with logistic regression,meaning calculations are more robust. 
B) There are much fewer restrictive assumptions associated with logistic regression,and it is generally more robust. 
C) There are much more restrictive assumptions associated with logistic regression,which mean it is a simpler test to administer. 
D) None of the above.

Question 18

In logistic regression,it should be possible to create a table of all possible values of all variables.If there are gaps in the table,then this will increase the risk of large:

Accepted Answer

A) Standard deviation 
B) Mean scores 
C) Standard errors 
D) Distribution anomalies 
A) Standard deviation 
B) Mean scores 
C) Standard errors 
D) Distribution anomalies

Question 19

Calculating the odds of an event occurring can be a lucrative thing.What is the equation to calculate odds?

Accepted Answer

A) odds = probability 
B) odds = probability of event not occurring / probability of event occurring 
C) odds = predictor variable effect size / probability of event occurring 
D) odds = probability of event occurring / probability of event not occurring 
A) odds = probability 
B) odds = probability of event not occurring / probability of event occurring 
C) odds = predictor variable effect size / probability of event occurring 
D) odds = probability of event occurring / probability of event not occurring

Question 20

What type of distribution does the z-statistic follow?

Accepted Answer

A) Discrete uniform distribution 
B) Poisson binomial distribution 
C) Degenerate distribution 
D) Normal distribution 
A) Discrete uniform distribution 
B) Poisson binomial distribution 
C) Degenerate distribution 
D) Normal distribution

How is $R _ { \mathrm { L } } ^ { 2 }$ calculated?

Logistic regression can be used to?

What does logistic regression measure?

How does logistic regression measure this relationship?

What is complete separation in logistic regression?

In the z-statistic equation,when the regression coefficient (b)is large,the standard error can be inflated,resulting in an underestimated z-statistic.What does an inflated standard error increase the probability of?

There are two types of logistic regression,differentiated by the number of categorical outcomes trying to be predicted.What are they?

In logistic regression,what is the R-statistic?

The log-likelihood statistic is analogous to what in multiple regression,as an indicator of the amount of unexplained information after a model has been fitted?

A synonym for the z-statistic is the what?

How does logistic regression differ from discriminant analysis?

What is the equation for deviance?

The z-statistic is used to discover whether a variable is an accurate predictor of an outcome.

You are carrying out a study into an area of research in which no previous relevant studies exist,and causality is not your primary concern.You are only intending to find a model to fit your data.What type of method would you employ for theory testing?

The fundamental difference between linear regression and logistic regression is that in linear regression it is possible to predict possible values,whereas in logistic regression it is the probability that a value will occur which is predicted.

If logistic regression and discriminant function analysis are different ways of achieving the same result,then why would a researcher prefer logistic regression?

In logistic regression,it should be possible to create a table of all possible values of all variables.If there are gaps in the table,then this will increase the risk of large:

Calculating the odds of an event occurring can be a lucrative thing.What is the equation to calculate odds?

What type of distribution does the z-statistic follow?

Why Is My Evil Lecturer Forcing Me to Learn Statistic

The Spine of Statistics

The Phoenix of Statistics

The Ibm Spss Statistics Environment

Exploring Data With Graphs

The Beast of Bias

Non-Parametric Models

Correlation

Regression

Comparing

Moderation,mediation and Multicategory Predictors

Comparing Several Means

Analysis of Covariance

Factorial Anova

Repeated-Measures Designs

Mixed Design Anova

Multiple Analysis of Variance Manova

Exploratory Factor Analysis

Categorical Data

Multilevel Linear Models

Filters

Exam 20: Logistic Regression

How is RL2R _ { \mathrm { L } } ^ { 2 }RL2​ calculated?

Logistic regression can be used to?

What does logistic regression measure?

How does logistic regression measure this relationship?

What is complete separation in logistic regression?

In the z-statistic equation,when the regression coefficient (b)is large,the standard error can be inflated,resulting in an underestimated z-statistic.What does an inflated standard error increase the probability of?

There are two types of logistic regression,differentiated by the number of categorical outcomes trying to be predicted.What are they?

In logistic regression,what is the R-statistic?

The log-likelihood statistic is analogous to what in multiple regression,as an indicator of the amount of unexplained information after a model has been fitted?

A synonym for the z-statistic is the what?

How does logistic regression differ from discriminant analysis?

What is the equation for deviance?

The z-statistic is used to discover whether a variable is an accurate predictor of an outcome.

You are carrying out a study into an area of research in which no previous relevant studies exist,and causality is not your primary concern.You are only intending to find a model to fit your data.What type of method would you employ for theory testing?

The fundamental difference between linear regression and logistic regression is that in linear regression it is possible to predict possible values,whereas in logistic regression it is the probability that a value will occur which is predicted.

If logistic regression and discriminant function analysis are different ways of achieving the same result,then why would a researcher prefer logistic regression?

In logistic regression,it should be possible to create a table of all possible values of all variables.If there are gaps in the table,then this will increase the risk of large:

Calculating the odds of an event occurring can be a lucrative thing.What is the equation to calculate odds?

What type of distribution does the z-statistic follow?

Why Is My Evil Lecturer Forcing Me to Learn Statistic

The Spine of Statistics

The Phoenix of Statistics

The Ibm Spss Statistics Environment

Exploring Data With Graphs

The Beast of Bias

Non-Parametric Models

Correlation

Regression

Comparing

Moderation,mediation and Multicategory Predictors

Comparing Several Means

Analysis of Covariance

Factorial Anova

Repeated-Measures Designs

Mixed Design Anova

Multiple Analysis of Variance Manova

Exploratory Factor Analysis

Categorical Data

Multilevel Linear Models

Filters

How is $R _ { \mathrm { L } } ^ { 2 }$ calculated?