You run a regression to analyze the relationship between the hourly earnings and years of schooling. The data to the right shows WAGE (hourly earnings) and EDUC (years of schooling). X=EDUC Y=WAGE26The following are observed values from the data for years of schooling and hourly earnings: EDUC =18 WAGE =26.87 The prediction error for the above number of years of schooling is,a-1.32 b-2.21 c-3.68 d-6.13 WAGEEDUC41.3521121019.5822.82181126.431313.49149.091110.39119.191126.87188.811014.051412.031310.711416.22107.871019.181211.391253.612521.711621.44157.3110161219.671719.531615.651316.881311.381115.81327.081416.881110.07117.491311.841418.411235.181511.041210.87108.851222.571316.951710.9412Find the intercept and slope coefficients of the regression.bo =b1 =

Answered: alyze the relationship between the…

alyze the relationship between the hourly earnings and years of schooling. The data to the right shows WAGE (hourly earnings) and EDUC (years of schooling). X=EDUC Y=WAGE 26 The following are observed values from the data f

Here we have to calculate prediction error. Prediction error can be defined as difference between…

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 chart below shows the correlation between degrees Fahrenheit and degrees Celsius. Part a: Make a scatter plot and determine which type of model best fits the data.Part b: Find the regression equation.Part c: Use the equation from Part b to determine ºC when ºF = 47.Part d: Does this answer seem reasonable? Explain.
You run a regression of Iowa crop yield per acre on average growing season temperature, average growing season rainfall, and average growing season total precipitation. You get the following results: Data Table Variable Coefficient Std. Error t value p-value (Intercept) 103.4183 42.891 2.411 0.0161 Temp 1.9446 0.0636 30.577 0.000001 Rain 43.988 21.1693 2.078 0.038 Precipitation −46.5995 21.1768 −2.2 0.028 What problem(s) do you think this regression has? Group of answer choices a) Omitted variable of how much fertilizer was used. This will impact the Rain coefficient. b) Multi-collinearity. Rain and precipitation are very highly correlated, their estimates are unreliable. c) Huge outliers are driving the result from years in drought. d) No issues, regression is probably fine.
The table gives the amount of money (in dollars) spent on football by a major university. Letting a represent the number of years since 2005, and letting y represent the amount of money spent on football, in thousands of dollars, use the regression capabilities of a graphing calculator to find the equation of the line of best fit. Round values off to the nearest hundredth. Then, use your equation to make the following predictions. Year 2005 2006 2007 2008 2009 2010 Dollars spent on football 165,000 196,000 210,000 226,000 242,000 279,000 The equation of the line of best fit is: Hint Predict the amount of money that will be spent on football in the year 2024. +A Predict the amount of money that will be spent on football in the year 2041.
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 (mg/dl) one hour after a sugary drink. Shelia's measured glucose level one hour after the sugary drink varies according to the Normal distribution with µ = 124 mg/dl and σ = 13 mg/dl. If a single glucose measurement is made, what is the probability that Shelia is diagnosed as having gestational diabetes?
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=-1.223 b=22.907 r2=0.600625 r=-0.775 Use this to predict the number of sit ups a person who watches 5 hours of TV can do, and please round your answer to a whole number.
Using the regression formula with a slope = .704 and an intercept = .719, what would the predicted college GPA be for a student whose current high school GPA = 3.2?
The table gives the amount of money (in dollars) spent on football by a major university. Letting x represent the number of years since 2006, and letting y represent the amount of money spent on football, in thousands of dollars, use the regression capabilities of a graphing calculator to find the equation of the line of best fit. Round values off to the nearest hundredth. Then, use your equation to make the following predictions. Year 2006 Dollars spent on football 173,000 The equation of the line of best fit is: Hint 2009 2010 2011 2007 2008 19 000 210,000 223,000 243,000 271,000 Predict the amount of money that will be spent on football in the year 2022. Predict the amount of money that will be spent on football in the year 2041.
The table below shows the average weekly wages (in dollars) for state government employees and federal government employees for 10 years. Construct and interpret a 98% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $878.The equation of the regression line is y=1.342x+55.816. Wages [state]- 712, 746, 786, 803, 841, 879, 918, 926, 954, 979 Wages [federal]- 1,024, 1,048, 1,098, 1,135, 1,195, 1,240, 1,270, 1,299, 1,340, 1,376 Construct and interpret a 98% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $878. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as needed.) PICK THE CORRECT ANSWER [A] We can be 98% confident that when the average weekly wages of state government employees is $878, the average weekly wages of…
Using your favorite statistics software package, you generate a scatter plot with a regression equation and correlation coefficient. The regression equation is reported as y = -10.91x + 44.13 and r = -0.92. What proportion of the variation in y can be explained by the linear regression equation found above? % Report answer as a percentage accurate to one decimal place.
I need help with this last part of this exercise.
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 128 mg/dl and standard deviation 9 mg/dl. Let ? denote a patient's glucose level. (a) If measurements are made on four different days, find the level ? such that there is probability only 0.01 that the mean glucose level of four test results falls above ? for Shelia's glucose level distribution. What is the value of ??ANSWER: (b) If the mean result from the four tests is compared to the criterion 140 mg/dl, what is the probability that Shelia is diagnosed as having gestational…
Using your favorite statistics software package, you generate a scatter plot with a regression equation and correlation coefficient. The regression equation is reported as y=−66.75x+57.0 and the r=−0.504. Report answer as a percentage accurate to one decimal place.

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You run a regression to analyze the relationship between the hourly earnings and years of schooling.
The data to the right shows WAGE (hourly earnings) and EDUC (years of schooling).

The prediction error for the above number of years of schooling is,