A sociologist examines the relationship between the poverty rate and several socioeconomic factors. For the 50 states and the District of Columbia (n= 51), he collects data on the poverty rate (y, in %), the percent of the population with at least a high school education (x1), median income (x2, in $1000s), and the mortality rate per 1,000 residents (x3). He estimates the following model as y= Bo + B1 Education + Bß2 Income + B3 Mortality + ɛ. The following ANOVA table shows a portion of the regression results. df MS F Regression 3 416.2 |138.73 95.7 Residual 47 68.1 1.45 Total 50 484.3 Coefficients Standard Error t-stat p-value Intercept 57.8 4.3 13.44 1.65E-16 Education -0.3 0.05 -6 5.45E-10 Income -0.2 0.01 -20 6.02E-10 Morality 0.12 0.27 0.44 0.6438 Which of the following is the value of the standard error of the estimate?

A sociologist examines the relationship between the poverty rate and several socioeconomic factors. For the 50 states and the District of Columbia (n= 51), he collects data on the poverty rate (y, in %), the percent of the population with at least a high school education (x1), median income (x2, in $1000s), and the mortality rate per 1,000 residents (x3). He estimates the following model as y= Bo + B1 Education + Bß2 Income + B3 Mortality + ɛ. The following ANOVA table shows a portion of the regression results. df MS F Regression 3 416.2 |138.73 95.7 Residual 47 68.1 1.45 Total 50 484.3 Coefficients Standard Error t-stat p-value Intercept 57.8 4.3 13.44 1.65E-16 Education -0.3 0.05 -6 5.45E-10 Income -0.2 0.01 -20 6.02E-10 Morality 0.12 0.27 0.44 0.6438 Which of the following is the value of the standard error of the estimate?

Name: A sociologist examines the relationship between the poverty rate and
Uploaded: 2024-03-20T06:38:58.000Z
Channel: Bartleby
Description: A sociologist examines the relationship between the poverty rate and several socioeconomic factors. For the 50 states and the District of Columbia (n =51), he collects data on the poverty rate (y, in %), the percent of the population with at least a

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

a. Estimate the regression line and also write the prediction equation. y = 83.4578-5.8795 x y = 5.8795 + 83.4578 x ŷ ŷ= = -5.8795 + 83.4578 x = 83.4578 + 5.8795 x
use the following information: A study of the mail survey response rate patterns of people aged 60- 90 found a prediction equation of ŷ = 90.2-0.6x relating x = age (in years) and y = percentage of people who responded to the survey. 6) Interpret the slope in the linear equation (ŷ = 90.2-0.6x). Using the linear prediction equation, find the predicted response rate for a (i) 60-year-old and (ii) 90-year-old. Predicted response rate for 60-year-old: Predicted response rate for 90-year-old:
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. x 11.9 8.4 6.6 3.8 2.6 2.3 2.2 0.9 y 14.2 11.1 9.6 7 6.2 6.1 5.8 5 x = thousands of automatic weaponsy = murders per 100,000 residentsThis data can be modeled by the equation y=0.85x+4.03. Use this equation to answer the following; Special Note: I suggest you verify this equation by performing linear regression on your calculator.A) How many murders per 100,000 residents can be expected in a state with 7.7 thousand automatic weapons?
The U.S. online grocery market is estimating sales worth approximately $29.7 billion by 2021. One of the biggest situational factors that influence the amount spent by a customer is the distance that that customer lives from its closest grocery store. Using the OLS method, the simple regression equation was estimated as: y = 40 + 3.5x. Find 1) the predicted amount a customer spends if they live 10 miles from the closest grocery store, as well as 2) the error amount. Note: the observed amount spent by a customer that lives 10 miles away is $85.50. a) $75.00, $10.50 Ob) $75.00, -$10.50 c) $73.00, $12.50 d) $73.00, -$12.50
A well-known university is interested in how salary (in thousands of dollars) is predicted from years of service for faculty and administrative staff. Below are the estimated regression equations.Faculty (n = 170): ŷ = 60 + 1.1xAdmin. (n = 155): ŷ = 57 + 1.5x a) How much would a faculty member be earning after 5 years of service? b) In how many years will an administrator earn the same amount as in a)?
The City of Bellmore’s police chief believes that maintenance costs on high-mileage police vehicles are much higher than those costs for low-mileage vehicles. If high-mileage vehicles are costing too much, it may be more economical to purchase more vehicles. An analyst in the department regresses yearly maintenance costs (Y) for a sample of 200 police vehicles on each vehicle’s total mileage for the year (X). The regression equation finds: Y = $50 + .030X with a r2 of .90 What is the IV? What is the DV? If the mileage increases by one mile, what is the predicted increase in maintenance costs? If a vehicle’s mileage for the year is 50,000, what is its predicted maintenance costs? What does an r2 of .90 tell us? Is this a strong or weak correlation? How can you tell?
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.4 8 7 3.6 2.7 2.5 2.7 0.8 yy 13.4 11 10.1 7.2 6.2 6.1 6.4 4.7 xx = thousands of automatic weaponsyy = murders per 100,000 residentsThis data can be modeled by the equation y=0.84x+4.09.y=0.84x+4.09. Use this equation to answer the following;A) How many murders per 100,000 residents can be expected in a state with 4.7 thousand automatic weapons?Answer = Round to 3 decimal places.B) How many murders per 100,000 residents can be expected in a state with 6.6 thousand automatic weapons?Answer = Round to 3 decimal places.
When using population size as the explanatory variable, x, and broadband subscribers as the response variable, y, for data on the number of individuals in a country with broadband access and the population size for 36 nations, the regression equation is y = 4,975,098 +0.0342x. a. Interpret the slope of the regression equation. Is the association positive or negative? Explain what this means. b. Predict broadband subscribers at the (i) population size 7,014,655, (ii) population size 1,155,173,053. c. For one nation, y = 71,110,000, and x = 322,413,902. Find the predicted broadband use and the residual for this nation. Interpret the value of this residual. a. Since the association is positive, the slope means that as the (Type an integer or a decimal.) b. (i) The predicted broadband subscribers for population size 7,014,655 is (Round to the nearest whole number as needed.) population size increases by 1 unit, the number of broadband subscribers tends to increase by 0.0342.
The table lists the average monthly cost to workers for family health insurance for various years. Year, x Average Monthly Cost to Workers for Family Health Insurance $298 a) Use a graphing calculator to fit a regression line to the data. b) Predict the average monthly cost to workers for family health insurance in 2020, and compare the value with $493.3, which is obtained using the points (1,340) and (4,386). c) Find the correlation coefficient for the regression line, and determine whether the line fits the data closely. 2009, 0 2010, 1 2011, 2 340 348 2012, 3 367 2013, 4 2014, 5 386 406 a) The linear equation of the regression line that best models the data is y =x+. (Round to the nearest hundredth as needed.) b) The average monthly cost to workers for family health insurance in 2020 is predicted to be $ (Round to the nearest cent as needed.) Compare the above obtained value with $493.3 This value is $ $493.3 c) The correlation coefficient is (Round to the nearest thousandth as…