Assume you fit a logistic regression for binary Y [i.e., replace EY in linear regression by log(EY/(1-EY))=log(odds)]. Instructor claims: beta for the main effect is log(OR), and beta for interaction effectis log(ROR), where ROR denotes the ratio of the odds ratio. Explain your agreement ordisagreement.

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Answered: Assume you fit a logistic regression…

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter4: Equations Of Linear Functions

Section4.6: Regression And Median-fit Lines

Problem 4PPS

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What does the y -intercept on the graph of a logistic equation correspond to for a population modeled by that equation?
Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4
Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
Table 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to 2012. a. Let x represent time in years starting with x=0 for the year 1997. Let y represent the number of seals in thousands. Use logistic regression to fit a model to these data. b. Use the model to predict the seal population for the year 2020. c. To the nearest whole number, what is the limiting value of this model?
For the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or older who are college graduates in a particular city, by year. Based on the set of data given in Table 5, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient. Round to three decimal places of accuracy
For the following exercises, consider the data in Table 5, which shows the percent of unemployed in a city ofpeople25 years or older who are college graduates is given below, by year. 41. Based on the set of data given in Table 7, calculatethe regression line using a calculator or othertechnology tool, and determine the correlationcoefficient to three decimal places.
For the following exercises, consider the data in Table 5, which shows the percent of unemployed ina city of people 25 years or older who are college graduates is given below, by year. 40. Based on the set of data given in Table 6, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient to three decimal places.
What is the y -intercept on the graph of the logistic model given in the previous exercise?
Consider the equation of the regression line y = 25 – 2.5x and ỹ = 12, %3D Find y when x = 6 assuming the linear correlation is not significant. %3D
Consider a regression and correlation analysis where = 1. We know that Multiple Choice SSE must be greater than one SSE can take on any negative or positive value SSE must be greater than SS Total SSE must equal to zero
The data shown below are the initial weights and gains in weight (in grams) of female rats on a high protein diet from 24 to 84 days of age. The point of interest in these data is whether the gain in weight is related to (dependent on) the initial weight. If so, then feeding experiments on female rats can be made more precise by adjusting for differences in initial weights of the rats. Statistically test this with a regression analysis. Rat Number Initial Weight (gms) Weight Gain (gms) 1 50 128 2 64 159 3 76 158 4 64 119 5 74 133 6 60 112 7 69 96 8 68 126 9 56 132 10 48 118 11 57 107 12 59 106 13 46 82 14 45 103 15 65 104 I used excel's regression took pak and got the following: SUMMARY OUTPUT Regression Statistics Multiple R 0.489416452 R Square 0.239528464 Adjusted R Square 0.181030653 Standard Error 8.869929833 Observations 15…
Calculate the estimate of σε What is the estimated resting heart rate for someone who is a smoker (Smoke=1) and exercises 1 hour a day (Exercise=1)?

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