Consider a regression study involving a dependent variable y, a quantitative independent variable 2, and a categorical independent variable with two levels (level 1 and level 2).a. Write a multiple regression equation relating 2 and the categorical variable to y.1. E(y) Bo + B1x12. E(y) = Bo + Baz3. E(y) Bo + B1x1 + B₂4. E(y) = Bo + B1n+B22Option 4Enter the values of dummy variable ₁ that are used to indicate the two levels of the qualitative variable. If your answer is zero, enter "0".Level 1Level 2x1b. What is the expected value of y corresponding to level 1 of the categorical variable?1. E(y)= Bo + Bui2. E(y)= Bo + B223. E(y) = Bo + B +4. E(3) = Bo + Bun+B22Option 2c. What is the expected value of y corresponding to level 2 of the categorical variable?1. E(y)= Bo + Bun2. E(y) = Bo + B223. E(y) = Bo + B+B4. E(y) Bo + B₁ + B₂x2Option 4d. Interpret the parameters in your regression equation.B₁ = E(y|level2) - E(y|level1)B₂ is the change in E(y) for a 1 unit change in [x2✔ holding the categorical variable constant.

Answered: Image /qna-images/answer/ea73ed2f-c3f8-467b-b0cf-d6a53dbd3368.jpg

Answered: Consider a regression study involving a…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

I’m interested in seeing whether or not there is a relationship between the number of hours someone sleeps and traffic accidents. I gather data from the Department of Transportation and get the following data: X (hours of sleep) Y (Traffic accidents) 5 2 5 1 3 4 4 4 2 6 6 3 8 1 9 1 5 0 6 4 Using the above data, create a linear regression equation to predict traffic accidents from hours of sleep. What is the Pearson correlation coefficient? Is it strong or weak? Positive or negative? What is the linear regression equation? (in the form of Y’ = bX + a) How many traffic accidents might we predict with someone that gets 0 hours of sleep? How many traffic accidents might we predict with someone that gets 11 hours of sleep?
Consider a regression study involving a dependent variable y, a quantitative independent variable x1, and a categorical independent variable with three possible levels (level 1, level 2, and level 3). a. How many dummy variables are required to represent the categorical variable? b. Consider the following regression equation relating x 1 and the categorical variable to y. E(v) = Bo + B1x 1 + B 2 x 2 + B 3 x 3 1X1 + Enter the values of dummy variables x 2 and x 3 that are used to indicate the three levels of the qualitative variable. Level X 2 X 3 Select v Select v 2 Select v Select v Select v Select v c. Interpret the parameters in your regression equation. B1 is the change in E(y) to a 1 unit change in Select v holding the categorical variable constant. B2 = Select B 3 = Select
A researcher conducted a number of descriptive statistics for two variables X and Y. They were as follows: SP = 15; SSx = 3; My = 7; Mx = 3 What is b equal to (Please include the sign: e.g., -20)? What is a equal to (please include the sign: e.g., +4.0)? Using b and a construct a regression equation, and then using the regression equation, calculate the value of predicted Y when X = 2?
ANSWER THE FOLLOWING QUESTION.
Management proposed the following regression model to predict sales at a fast-food outlet. y=B₁ + B₁x₁ + B₂x₂ + Bzx3 +6 where x₁ = number of competitors within one mile X₂= population within one mile (1,000s) x3 = [1 if drive-up window present lo otherwise y = sales ($1,000s). The following estimated regression equation was developed after 20 outlets were surveyed. 9-10.1-4.2x₁ + 6.8x₂ + 15.3x3 (a) What is the expected amount of sales (in dollars) attributable to the drive-up window? $ (b) Predict sales (in dollars) for a store with four competitors within one mile, a population of 8,000 within one mile, and no drive-up window. $ (c) Predict sales (in dollars) for a store with one competitor within one mile, a population of 3,000 within one mile, and a drive-up window. $
1. Consider the following regression model: Fram Risk Score; = Bo + B1 × Health Insurance; + u¿ The Framingham Risk Score predicts 10-year risk of cardiovascular disease based on age, cholesterol levels, blood pressure, blood sugar, use of medication for high blood pressure, and smoking. A higher score means worse overall cardiovascular health. A researcher who collects data and regresses the Fram Risk Score against Health Insurance (= 1 if have insurance) finds that B, 2. Consider the following regression model: Class Average; = Bo + B1 x Office Hours; + u; Class Average is the students' average grade in the class at the end of the term and Office Hours is the number of office hours held by the instructor over the entire term. A researcher who collects data and regresses Class Average against Office Hours finds that, surprisingly, B V A V A
Which of the following is/are true for logistic regression model? I. The independent variable must be continuous. II. The dependent variable can only have 2 levels/categories. I only II only…
Consider a simple linear regression model with predictor variable x and response variable y, where the regression line is represented by the equation y = β0 + β1x. If β0 = -5 and β1 = 3, what is the predicted value of y for a given x = 4?
A study examined the eating habits of 20 children at a nursery school. The variables measured for each child included: calories (the number of calories eaten at lunch), time (the time in minutes spent eating lunch), and sex (male=1, female=0). A multiple linear regression model using Y = calories, X1 = time, and X2 = sex led to the following model: y=547.65-2.85x1+10.67x2 For two children who spend the same amount of time eating, one male and one female, which child is predicted to consume more calories and by how much?
1
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.7 8.1 6.7 3.3 2.7 2.3 2.2 0.3 yy 13.8 10.7 9.9 6.6 6.1 5.9 6.1 4.5 xx = thousands of automatic weaponsyy = murders per 100,000 residents Determine the regression equation in y = ax + b form and write it below. (Round to 2 decimal places) A) How many murders per 100,000 residents can be expected in a state with 6.4 thousand automatic weapons? Answer = Round to 3 decimal places. B) How many murders per 100,000 residents can be expected in a state with 6.7 thousand automatic weapons? Answer = Round to 3 decimal places.
Consider the following linear regression prediction equation: Y = 12 + -1x. What is the direction of the relationship between these two variables? a. The relationship between the observed X and the predicted Y is negative. b. The relationship between the observed X and the predicted Y is positive. c. There is no relationship between the observed X and the predicated Y. d. There is a weak relationship between the observed X and the predicted Y with no direction.

SEE MORE QUESTIONS

Recommended textbooks for you

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

Elementary Statistics: Picturing the World (7th E…

Statistics

ISBN:

9780134683416

Author:

Ron Larson, Betsy Farber

Publisher:

PEARSON

The Basic Practice of Statistics

Statistics

ISBN:

9781319042578

Author:

David S. Moore, William I. Notz, Michael A. Fligner

Publisher:

W. H. Freeman

Introduction to the Practice of Statistics

Statistics

ISBN:

9781319013387

Author:

David S. Moore, George P. McCabe, Bruce A. Craig

Publisher:

W. H. Freeman

SEE MORE TEXTBOOKS