please answer the question in the attached picture with work shown, thanks!#4 G 国14. Suppose we have 51 observations on income per capita (y) and the percentage of population with abachelor's or higher degree (x). Using this data, the following regression model has been estimated:y =(a) + 1.029xse (2.672)(c)t (4.31) (10.75),where se stands for the standard errors of the estimated coefficients b, and b2; t stands for the t-ratiosof the two estimated regression coefficients (b, and b2) when testing the hypothesis Ho:b120, Ha: b1,2 + 0. (H5:3.7)a. Calculate the estimated intercept, b1. Interpret (explain the meaning) of the two regressioncoefficients, b, and b2. (Please remember that the t-ratio is equal to the estimated value of aparameter over its standard error when testing the null hypothesis that the parameter is equalto zero.)b. Sketch the estimated relationship.it increasing, or decreasing? Is it a positive, or negativerelationship? Is it increasing or decreasing at a constant rate, or is it increasing or decreasing atan increasing or decreasing rate?С.Calculate the standard error of the slope coefficient b2 of the regression model. Show yourwork.d. What is the value of the t-statistic for the null hypothesis that the intercept is equal to 10?The p-value of the two-tail test that the intercept parameter equals 10 from part (d) is 0.572.Show the p-value in a sketch. On the sketch, show the rejection region if a = 0.05.Construct a 99% interval estimate of the slope coefficient, b2. Interpret the interval estimate.g. Test the null hypothesis that the slope coefficient is equal to 1 against the alternative that it isе.f.not 1 at the 5% level of significance. State the economic result of the test in the context of thisproblem.

Hi! Thank you for the question, as per the honor code, we are allowed to answer three sub-parts at a…

Suppose we have 51 observations on income per capita (y) and the percentage of population with a bachelor's or higher degree (x). Using this data, the following regression model has been estimated: y = (a) + 1.029x se (2.672) (c) t (4.31) (10.75), where se stands for the standard errors of the estimated coefficients b, and b2; t stands for the t-ratios of the two estimated regression coefficients (b, and b2) when testing the hypothesis Ho: b.2 = 0, Ha: b12 + 0. (H5:3.7) a. Calculate the estimated intercept, b,. Interpret (explain the meaning) of the two regression coefficients, b, and b2. (Please remember that the t-ratio is equal to the estimated value of a parameter over its standard error when testing the null hypothesis that the parameter is equal to zero.)

Suppose we have 51 observations on income per capita (y) and the percentage of population with a bachelor's or higher degree (x). Using this data, the following regression model has been estimated: y = (a) + 1.029x se (2.672) (c) t (4.31) (10.75), where se stands for the standard errors of the estimated coefficients b, and b2; t stands for the t-ratios of the two estimated regression coefficients (b, and b2) when testing the hypothesis Ho: b.2 = 0, Ha: b12 + 0. (H5:3.7) a. Calculate the estimated intercept, b,. Interpret (explain the meaning) of the two regression coefficients, b, and b2. (Please remember that the t-ratio is equal to the estimated value of a parameter over its standard error when testing the null hypothesis that the parameter is equal to zero.)

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)

6th Edition

ISBN:9781337111348

Author:Bruce Crauder, Benny Evans, Alan Noell

Publisher:Bruce Crauder, Benny Evans, Alan Noell

Chapter3: Straight Lines And Linear Functions

Section3.CR: Chapter Review Exercises

Problem 16CR: XYZ Corporation Stock Prices The following table shows the average stock price, in dollars, of XYZ...

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XYZ Corporation Stock Prices The following table shows the average stock price, in dollars, of XYZ Corporation in the given month. Month Stock price January 2011 43.71 February 2011 44.22 March 2011 44.44 April 2011 45.17 May 2011 45.97 a. Find the equation of the regression line. Round the regression coefficients to three decimal places. b. Plot the data points and the regression line. c. Explain in practical terms the meaning of the slope of the regression line. d. Based on the trend of the regression line, what do you predict the stock price to be in January 2012? January 2013?
For the following exercises, consider this scenario: The profit of a company decreased steadily overa ten-year spam.The following ordered pairs shows dollars and the number of units sold in hundreds and the profit in thousands ofover the ten-year span, (number of units sold, profit) for specific recorded years: (46,600),(48,550),(50,505),(52,540),(54,495). Use linear regression to determine a function Pwhere the profit in thousands of dollars depends onthe number of units sold in hundreds.
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?
A regression was run to determine whether there is arelationship between the diameter of a tree (x, in inches) and the tree’s age (y, in years). Theresults of the regression are given below. Use this topredict the age of a tree with diameter 10 inches. y=ax+ba=6.301b=1.044r=0.970
Zipfs Law The following table shows U.S cities by rank in terms of population and population in thousands. City Rank r Population N New York 1 8491 Chicago 3 2722 Philadelphia 5 1560 Dallas 9 1280 Austin 11 913 San Francisco 13 852 Columbus 15 836 A rule known as Zipfs law tells us that it is reasonable to approximate these data with a power function. a Use power regression to express the population as a function of the rank. b Plot the data along with the power function from part a. c Phoenix is the sixth largest city in the United States. Use your answer from part a to estimate population of Phoenix. Round your answer in thousands to the nearest whole number. Note: The actual population is 1537 thousand.