Question 1

A researcher conducts research on optimism. The researcher is calculating a multiple regression equation to predict levels of optimism and wishes to consider religious affiliation as one of the predictor variables. The researcher creates several dummy variables, for this purpose. Why must this be done?

Accepted Answer

B, C, and E are correct because multiple regression analysis requires numerical input for all variables, including categorical ones like religious affiliation. Creating dummy variables converts these categories into a numerical format (0 or 1) that can be used in the regression equation, allowing for mathematical computation and the development of a formula to calculate optimism based on various predictors, including those that are originally non-numeric.

Question 2

What is a multiple regression equation?

Accepted Answer

A, C, E

Question 3

A researcher collects a nationally based set of data about cholesterol levels and age at first circulatory incident (myocardial infarction or cerebrovascular accident). The researcher performs a linear regression analysis, in order to do which of the following?

Accepted Answer

Linear regression analysis is used to estimate the value of a variable based on the value of another variable (A), calculate the strength of the relationship between two variables (C), determine whether there is a linear relationship between two variables (D), and derive the formula for the line of best fit (E).

Question 4

Which of the following dependent variables is suitable for logistic regression analysis?

Accepted Answer

Logistic regression is used for predicting the probability of a binary outcome. Choices C (Born on earth-not born on earth), E (Birth gender), and F (Whether a patient with cancer goes into remission) are suitable for logistic regression because they involve binary or dichotomous outcomes, which fit the logistic regression model's requirement.

Question 5

Why does a researcher decide to calculate odds ratio instead of calculating linear regression, when comparing whether a person voted in the last election, and the person's gender?

Accepted Answer

The odds ratio is used instead of linear regression in this scenario because both the predictor variable (gender) and the dependent variable (whether a person voted in the last election) are dichotomous, meaning they each have two categories. Linear regression is not suitable for dichotomous variables.

Question 6

Which of the following terms in correlational research mean the same thing?

Accepted Answer

Predictor variable and independent variable mean the same thing in correlational research. They are the variables that are used to predict the outcome variable.

Question 7

A researcher decides to study how many college freshmen with continuous enrollment graduate within 4, 4.5, 5, 5.5, and 6 years and to analyze this according to what their majors at graduation are, as well as other demographic variables. Why would a Cox proportional hazards regression analysis be suitable for this research?

Accepted Answer

The answer of A researcher decides to study how many...

Question 8

Why does a researcher decide to use logistic regression instead of linear regression to calculate survival odds after suffering an out-of-hospital heart attack, in persons of various ages, genders, and cardiac diagnoses?

Accepted Answer

The answer of Why does a researcher decide to use...

Question 9

A researcher draws a scatter plot of study data. The researcher develops a multiple regression equation and determines R² as 0.5625. What does the calculated value R² represent?

Accepted Answer

The answer of A researcher draws a scatter plot of...

Question 10

A researcher is studying daily carbohydrate intake and the next day's first morning blood glucose monitor value. After drawing a scatter plot, the researcher develops a multiple regression equation. What is does the value R represent?

Accepted Answer

R represents the correlation coefficient, which measures the strength and direction of the relationship between two variables, in this case, daily carbohydrate intake and the next day's first morning blood glucose monitor value.

Question 11

Which of the following statements about prediction is true?

Accepted Answer

These choices are all true statements about prediction.

Question 12

A researcher is studying stress and various factors that seem to be related to it, in women with terminally ill spouses. Among other things, the researcher finds out that depression contributes to total stress; depression contributes to lack of exercise; exercise contributes to depression; exercise relieves stress; guilt contributes to depression; exercise has no effect on guilt, but it affects total stress; stress worsens depression; and stress decreases motivation to perform exercise. This is an example of what problem commonly encountered in regression analyses?

Accepted Answer

This scenario describes a situation where multiple variables are interrelated, influencing each other in various ways (e.g., depression and exercise both affect and are affected by stress). This interrelation among independent variables is a classic example of multicollinearity, a problem in regression analyses where it becomes difficult to isolate the effect of each variable due to their high correlation with each other.

Quiz 24: Using Statistics to Predict

What is a multiple regression equation?

A researcher collects a nationally based set of data about cholesterol levels and age at first circulatory incident (myocardial infarction or cerebrovascular accident) . The researcher performs a linear regression analysis, in order to do which of the following?

Which of the following dependent variables is suitable for logistic regression analysis?

Why does a researcher decide to calculate odds ratio instead of calculating linear regression, when comparing whether a person voted in the last election, and the person's gender?

Which of the following terms in correlational research mean the same thing?

Why does a researcher decide to use logistic regression instead of linear regression to calculate survival odds after suffering an out-of-hospital heart attack, in persons of various ages, genders, and cardiac diagnoses?

A researcher draws a scatter plot of study data. The researcher develops a multiple regression equation and determines R² as 0.5625. What does the calculated value R² represent?

A researcher is studying daily carbohydrate intake and the next day's first morning blood glucose monitor value. After drawing a scatter plot, the researcher develops a multiple regression equation. What is does the value R represent?

Which of the following statements about prediction is true?

Quiz 24: Using Statistics to Predict

What is a multiple regression equation?

A researcher collects a nationally based set of data about cholesterol levels and age at first circulatory incident (myocardial infarction or cerebrovascular accident) . The researcher performs a linear regression analysis, in order to do which of the following?

Which of the following dependent variables is suitable for logistic regression analysis?

Why does a researcher decide to calculate odds ratio instead of calculating linear regression, when comparing whether a person voted in the last election, and the person's gender?

Which of the following terms in correlational research mean the same thing?

Why does a researcher decide to use logistic regression instead of linear regression to calculate survival odds after suffering an out-of-hospital heart attack, in persons of various ages, genders, and cardiac diagnoses?

A researcher draws a scatter plot of study data. The researcher develops a multiple regression equation and determines R2 as 0.5625. What does the calculated value R2 represent?

A researcher is studying daily carbohydrate intake and the next day's first morning blood glucose monitor value. After drawing a scatter plot, the researcher develops a multiple regression equation. What is does the value R represent?

Which of the following statements about prediction is true?

A researcher draws a scatter plot of study data. The researcher develops a multiple regression equation and determines R² as 0.5625. What does the calculated value R² represent?