A researcher is interested in finding out the factors which determined the yearly spending on family outings last year (Y, measured in dollars). She compiles data on thenumber of members in a family (X, ), the annual income of the family (X,), and the number of times the family went out on an outing in the last year (Xa). She collectsdata from 152 families and estimates the following regression:Y= 120.45+ 1.12X, + 1.98X2 + 1.98X3.Suppose B1, B2, B3, denote the population slope coefficients of X1, X2, and X3, respectively.The researcher wants to check if neither X, nor X, have a significant effect on Y or at least one of them has a significant effect, keeping X, constant. She calculatesthe value of the F-statistic for the test with the two restrictions (Ho: B, =0, B, = 0 vs. H, : B, #0 and/or B, #0) to be 2.30.The p-value for the test will be.(Round your answer to two decimal places.)At the 1% significance level, we willV the null hypothesis.

Answered: A researcher is interested in finding…

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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A researcher is hired to investigate the relationship between the number of unauthorized days that employees are absent per year and the distance in miles between home and work for the employees. A sample of 10 employees was chosen and the results are listed in the chart below. Use the proper Data Analysis function in Excel to computethe regression equation needed to predict the number of missed days that could be expected foremployees who live certain distances away from the workplace. Distance to Work (miles): 1, 3, 4, 6, 9, 10, 12, 14, 14, 18 Number of Days Absent: 9, 6, 7, 7, 6, 4, 5, 3, 4, 2
Might we be able to predict life expectancies from birthrates? Below are bivariate data giving birthrate and life expectancy information for each of twelve countries. For each of the countries, both x, the number of births per one thousand people in the population, and y, the female life expectancy (in years), are given. Also shown are the scatter plot for the date and the least-squares regression line. The equation for this line is y=82.84-0.49x. Birthrate, x (number of births per 1000 people) 24.6 50.1 40,6 20.0 50.7 28.1 143 49.0 31.9 14.8 33.6 46.5 Send data to calculator Send data to Excel Female life expectancy, y (in years) 74.3 54.4 66.2 73.6 58.9 72.7 76.1 61.5 62.4 71.4 68.0 57:5 Based on the sample data and the regression line, complete the following. Female life expectancy (in years) Birthrate (number of births per 1000 people)
Given that the systolic blood pressure in the right arm is 90 mm Hg, the best systolic blood pressure in the left arm is how many mm Hg?
What is the differed annual expenditures of two families if their annual net incomes are differed by 2000? The computed regression line has a value of a=4.32 and b=2.12.
While attempting to measure its risk exposure for the upcoming year, an insurance company notices a trend between the age of a customer and the number of claims per year. It appears that the number of claims keep going up as customers age. After performing a regression, they find that the relationship is (claims per year) = 0.385*(age) + 5.218. If a customer is 44.315 years old and they make an average of 11.239 claims per year, the residual is -11.04. Interpret this residual in terms of the problem. Question 10 options: 1) The number of claims per year is 11.04 claims less than what we would expect. 2) The age is 11.04 years larger than what we would expect. 3) The age is 11.04 years less than what we would expect. 4) The number of claims per year is 11.239 claims less than what we would expect. 5) The number of claims per year is 11.04 claims…
Below is some of the regression output from a regression of the amount various customers paid for a new car (expressed in dollars) versus the age of the customer (expressed in years), the number of previous cars the customer had purchased from the dealership in the past, a dummy variable indicating the gender of the customer (=1 for a Man and = 0 for a woman), and an interactive term the multiplies the age of the customer with the gender dummy variable. Regression Statistics Multiple R 0.963 R Square Adjusted R Square Standard Error Observations 20 ANOVA df SS MS F Significance F Regression 24686354.49 6171589 47.8 2.3289E-08 Residual 129243 Total 26625000…
Would I use the regression line to predict Y from X ? And what is the pattern of the scatterplot?
Assume that a randomly selected subject is given a bone density test. Those test scores are normally distributed with a mean of 0 and a standard deviation of 1. Draw a graph and find the bone density test scores that can be used as cutoff values separating the lowest 10% and highest 10%, indicating levels that are too low or too high, respectively. Sketch the region containing the lowest 10% and highest 10%. Choose the correct graph below. OA. -Za Za Q The bone density scores are ☐ OB. -Za Za (Use a comma to separate answers as needed. Round to two decimal places as needed.) ○ C. Q Za -Za D. Q a G Za -Za
For the following questions, THERE IS NO NEED FOR EXPLANATION. PLEASE PROVIDE JUST THE ANSWER THANK YOU. Please DO NOT waste time on writing things to explain. Please answer in 30 mintues or else I will write a bad review. If you follow my rules and answer in less than 30 mintues then I will write a very long and wonderful review about you. ANSWER the questions correlty and please answer all the questions with what it regards in saying exactly.
Increase in sales (percent) An advertising firm wishes to demonstrate to its clients the effectiveness of the advertising campaigns it has conducted. The following bivariate data on twelve recent campaigns, including the cost of each campaign (in millions of dollars) and the resulting percentage increase in sales following the campaign, were presented by the firm. Based on these data, we would compute the least-squares regression line to be y = 6.16+0.18x, with x representing campaign cost and y representing the resulting percentage increase in sales. (This line is shown below, along with a scatter plot of the data.) Increase in sales, y Campaign cost, x (in millions of dollars) (percent) 3.02 6.91 7.2+ 1.92 6.80 3.83 6.85 6.8- 1.40 6.37 6.6 - 3.12 6.42 3.56 6.82 6.4- 4.06 6.94 6.2 1.64 6.56 6- 2.06 6.50 1.62 6.18 1.5 2.5 3.5 6.66 Campaign cost (in millions of dollars) 2.87 2.25 6.61 Send data to calculator Based on the firm's data and the regression line, complete the following. (a)…
The regression line for the given data is = 6.91x + 46.26. Determine the residual of a data point for which x = 4 and y = 75.
please only answer the last part "Suppose that real income per capita in New Jersey increases by 1% in the next year. Use the results in column (4) to predict the change in the number of traffic fatalities in the next year. "

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