Suppose that n = 50, i.i.d observations for (Y₁, X₁) yield the following regressionsresults:Ỹ= 49.2 + 73.9 X, SER = 13.4, R²=0.78(23.5) (16.4)Another researcher is interested in the same regression, but makes an error whenentering the data into a regression program: The research enters each observationtwice, ending up with 100 observations (with observation 1 entered twice, observation2 entered twice and so forth).Using these 100 observations, what results will be produced by the regressionprogram? Complete the spaces in the equation below. Report the intercept and slopeto one decimal place, but report the R2 to two decimal places.Ŷ = +*X,R² =

The regression equation is in the form of stright line where, bo is intercept…

Answered: Suppose that n = 50, i.i.d observations…

College Algebra

1st Edition

ISBN:9781938168383

Author:Jay Abramson

Publisher:Jay Abramson

Chapter4: Linear Functions

Section: Chapter Questions

Problem 30PT: For the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or...

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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?
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?
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
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, 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.
Table 2 shows a recent graduate’s credit card balance each month after graduation. a. Use exponential regression to fit a model to these data. b. If spending continues at this rate, what will the graduate’s credit card debt be one year after graduating?
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.
A regression was run to determine if there is a relationship between hours of TV watched per day (xx) and number of situps a person can do (yy).The results of the regression were:y=ax+b a=-0.629 b=39.045 r2=0.806404 r=-0.898 Use this to predict the number of situps a person who watches 6.5 hour(s) of TV can do, and please round your answer to a whole number.
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=ax+b a=-0.711 b=30.651 r²-0.670761 r=-0.819 Use this to predict the number of situps a person who watches 10.5 hours of TV can do (to one decimal place)
A local retail store compared their monthly sales of umbrellas with the amount of rainfall that occured during that month. They computed the following statistics: Rainfall (in) # of umbrellas mean = 4.64 mean = 34.2 SD = 1.17 SD = 13.2 r = 0.8 1. Find the equation for the regression line that predicts the monthly sales of umbrellas from monthly rainfall.
The average height of people in Faroe island is 180cm. Suppose you run a regression with no independent variables. What would be the estimated form of your regression?
A regression was run to determine if there is a relationship between hours of study per week (xx) and the test scores (yy).The results of the regression were:y=ax+b a=6.686 b=35.26 r2=0.6084 r=0.78 Use this to predict the final exam score of a student who studies 8.5 hours per week, and please round your answer to a whole number.

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