1. An analyst ran a regression with four predictor variables.Variable descriptionSalary in R1000.00Years at companyAge in yearsEducation in yearsVariableNameSALARYYEARSAGEEDYEARSHe suspects that AGE can be dropped from the model and he decided to employ forwardstepwise regression. Show all the steps he has to do to get to a fitted response regression withoutage.

4 predictor variables Variable Name Description Salary Salary in 1000.00 years Years at…

Answered: 1. An analyst ran a regression with…

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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Using the regression equation developed in step 2, forecast the monthly food and beverage sales for January through December for the fourth year of operation. Discuss your findings
A researcher calculates a regression equation to predict an insurance premium based on a person's age. One person in the sample was observed to have a premium of $500 at 20 years old, but the predicted value was $400. VWhat is the value of the residual for this person? Next Page Page 10 of 14
4 3. 837 784 815 805 843 893 Use exponential regression to find Rn exponential function that best fits these data. Round all values hundredths. f(z) = Use linear regression to find a linear function that best fits these data. Round all values to the hundr g(z) = %3D Of these two, which equation best fits the data? Exponential O Linear
Using the data, run a regression where you control for “Promotion,” and test the effect of “Wins” on “Attendance”. What should be the attendance if the number of wins is 10? Wins Promotion Attendance 4 29500 36300 6 55700 40100 6 71300 41200 8 87000 53000 6 75000 44000 7 72000 45600 5 55300 39000 7 81600 47500
Shelia's doctor is concerned that she may suffer from gestational diabetes (high blood glucose levels during pregnancy). There is variation both in the actual glucose level and in the blood test that measures the level. A patient is classified as having gestational diabetes if the glucose level is above 140 milligrams per deciliter one hour after a sugary drink is ingested. Shelia's measured glucose level one hour after ingesting the sugary drink varies according to the Normal distribution with mean 127 mg/dl and standard deviation 10 mg/dl. Let L denote a patient's glucose level.
Using the regression to model annual income, a variable for years of education has a slope = 2000. This means that the model predicts each additional year of education will yield an extra 2,000 for the average person's salary, regardless of how many total years of education a person has. A. True B. False
6, 5. Kathy painted a picture and posted it on a social media site. The table shows the number of people who responded that they liked the picture since Kathy posted it. Time Since Picture Was Posted 5. 7. (days) Number of Likes 11 21 38 Write the regression equation that best models the data. a. y = 0.96(1. 55)* b. y = 2.07(1. 38)* c. y = 0.536x – 0.857x + 1.81 d. y = 1.38x´ + 0.30x + 0. 43
Develop a scatterplot and explore the correlation between customer age and net sales by each type of customer (regular/promotion). Use the horizontal axis for the customer age to graph. Find the linear regression line that models the data by each type of customer. Round the rate of changes (slopes) to two decimal places and interpret them in terms of the relation between the change in age and the change in net sales. What can you conclude? Hint: Rate of Change = Vertical Change / Horizontal Change = Change in y / Change in x
For half-life demonstration, plot ln(half-lives) in the x-axis vs ln(no. of “tails-up” coins) in the y-axis. Perform linear regression to obtain the value of the slope, the value of the y-intercept, and the correlation coefficient r. What is the significance of these values?
Using the data, run a regression where you control for “Promotion,” and test the effect of “Wins” on “Attendance”. Does “Promotion” have a significant effect on “Attendance”? Wins Promotion Attendance 4 29500 36300 6 55700 40100 6 71300 41200 8 87000 53000 6 75000 44000 7 72000 45600 5 55300 39000 7 81600 47500
The slope, b represents * O predicted value of Y when X = 0. O the estimated average change in Y per unit change in X. O variation around the line of regression. O the predicted value of Y.
An economist at Nedbank ran a study of the relationship between FTSE/JSE All Shares index return (JALSH) and consumer price index (CPI) from 2006 to 2017, the data collected is shown in the Table 1 below. FTSE/JSE All Shares index return (JALSH) and consumer price index (CPI) from 2006 to 2017. Year JALSH (Y) CPI (X) 2006 0.41 4.7 2007 0.19 7.1 2008 -0.23 11.5 2009 0.32 7.1 2010 0.19 4.3 2011 0.03 5.0 2012 0.27 5.6 2013 0.21 5.7 2014 0.11 6.1 2015 0.05 4.6 2016 0.00 6.4 2017 0.21 5.3 The estimated regression…

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1. An analyst ran a regression with four predictor variables. Variable description Salary in R1000.00 Years at company Variable Name SALARY YEARS AGE EDYEARS Age in years Education in years