A. Holding constant the other variables, for every one unit increase in \( X_1 \) or \( X_2 \), the value of \( Y \) increases by \( 100 \cdot b_1 \) or \( 100 \cdot b_2 \) percent, respectively.B. For every decrease of one unit of ln \( Y \), holding \( b_0 \) constant, the estimated change in \( X_1 \) or \( X_2 \) is \( 100 \cdot b_1 \) or \( 100 \cdot b_2 \) units, respectively.C. Holding constant the other variables, for every one percent increase in \( X_1 \) or \( X_2 \), the value of \( Y \) increases by \( b_1 \) or \( b_2 \) units, respectively.D. Holding constant the other variables, for every one percent increase in \( X_1 \) or \( X_2 \), the value of \( Y \) increases by \( b_2 \) or \( b_1 \) percent, respectively. **Regression Analysis Overview**This section will explore a given regression equation and interpret its components.**Equation:**\[\ln \hat{Y}_i = 3.89 + 0.5X_{1i} + 0.3X_{2i}\]**Tasks:**1. **Predictive Analysis** - **Objective:** Calculate the predicted value of \( Y \) when \( X_1 = 7.1 \) and \( X_2 = 4.9 \). - **Procedure:** Substitute these values into the regression equation to solve for \( \ln \hat{Y}_i \), then exponentiate the result to obtain \( \hat{Y}_i \).2. **Coefficient Interpretation** - **Objective:** Interpret the scaled regression coefficients \( 100 \cdot b_1 \) and \( 100 \cdot b_2 \). - **Explanation:** Understand what a 1-unit increase in \( X_1 \) and \( X_2 \) implies in percentage terms for \( Y \), assuming the other variable is held constant.**Note:** This section covers predictive analysis using a logarithmic regression model and provides insights into interpreting regression coefficients in a multiplicative context.

The estimated regression equation is

Answered: Consider the regression equation In Y₁…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable. Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min 760 1119 1125 850 965 785 D Temperature (°F) 70.5 90.8 90.8 74.7 77.1 69.9 What is the regression equation? (Round the x-coefficient to four decimal places as needed. Round the constant to two decimal places as needed.)
A regression analysis was performed to determine if there is a relationship between hours ofTV watched per day r) and number of sit ups a person can do (y). The results of the regression were: у-ах+b a=-0.827 b=35.329 r2=0.540225 r=-0.735 Use this to predict the number of sit ups a person who watches 13.5 hours of TV can do, and please round your answer to a whole number.
A regression analysis was performed to determine if there is a relationship between hours of TV watched per day (xx) and number of sit ups a person can do (yy).The results of the regression were: y=ax+b a=-0.904 b=24.378 r2=0.64 r=-0.8 Use this to predict the number of sit ups a person who watches 9.5 hours of TV can do, and please round your answer to a whole number.
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Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed lemon/crash data, where lemon imports are in metric tons and the fatality rates are per 100,000 people, find the best predicted crash fatality rate for a year in which there are 500 metric tons of lemon imports. Is the prediction worthwhile? Find the equation of the regression line. (Round the constant three decimal places as needed. Round the coefficient to six decimal places as needed.) The best predicted crash fatality rate for a year in which there are 500 metric tons of lemon imports is _______ fatalities per 100,000 population. (Round to one decimal place as needed.) Is the prediction worthwhile? A. Since the sample size is small, the prediction is not appropriate. B. Since common sense suggests there should not be much of a relationship between the two variables, the prediction does not make much sense. C. Since all of the requirements…
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A regression was run to determine if there is a relationship between hours of TV watched per day (x) and the number of sit-ups a person can do (y). The results were: Y a+bx b = -0.79 = 23.04 a r² = 0.4493 r = -0.6703 a. If a person watches 10 hours of television a day, predict how many sit-ups he can do. b. If a person can do 7 sit ups, predict how many hours of television a day they watch. hours
The data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable. Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min 924 1150 840 1166 1087 930 Temperature (°F) 77.5 84.6 74.1 91 79.6 79.7 What is the regression equation? What is the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute? What is wrong with this predicted value? Choose the correct answer below. A. It is unrealistically high. The value 3000 is far outside of the range of observed values. B. The first variable should have been the dependent variable. C. It is only an approximation. An unrounded value would be considered accurate. D. Nothing is wrong with this value. It can be…
A regression analysis was performed to determine if there is a relationship between hours of TV watched per day (x) and number of sit ups a person can do (y ). The results of the regression were: y=ax+b a=-1.33 b=25.138 r2=0.712336 r=-0.844 Use this to predict the number of sit ups a person who watches 10 hours of TV can do, and please round your answer to a whole number.

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Consider the regression equation In Y₁ = 3.89 +0.5X11 +0.3X2i. a. Predict the value of Y when X₁ = 7.1 and X₂ = 4.9. Interpret the meaning of the regression coefficients 100-b and 100.h