KUse the pizza cost and the subway fare in the table below to find the regression equation, letting pizza cost be the predictor (x) variable. (Pizza cost is in dollars per slice,subwayfare and CPI are in dollars.) What is the best predicted subway fare when pizza costs $3.99 per slice?YearPizza CostSubway FareCPI1960 1973 1986 1995 2002 2003 2009 2013 2015 20190.154 0.347 0.998 1.250 1.754 2.000 2.250 2.303 2.754 2.9970.153 0.352 0.999 1.351 1.502 2.002 2.250 2.551 2.747 2.74629.6 44.4 109.6 152.4 180.0 184.0 214.5 233.0 237.0 252.2The regression equation is y=-x(Round the y-intercept to four decimal places as needed. Round the slope to three decimal places as needed)

The question is about regression.Given :To find :1 ) Regression equation2 ) Predicted value of…

Answered: K Use the pizza cost and the subway…

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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It is inferred that the tip amount has a relationship with value of a dinner bill. The collected data is presented in the table. Conduct a regression analysis. X - Bill ($) 33.46 50.68 87.92 98.84 63.60 107.34 Y - Tip ($) 5.70 5.00 8.08 17.00 12.00 16.00
Prices and mileage of 48 Dodge 2500 Pickup trucks with Cummins diesel engines. Prices ranged from $28,925 to $68,650. Mileage ranged from 315 to 186,466. While I did not share the trucks were 2013 to 2020 models. Please show all work. Interpret b0 in the context of this problem. Interpret b1 in the context of this problem. What percent of total variation in prices is explained by the regression model? Provide evidence to support your answer. Price Mileage 52293 34450 50987 23372 62988 21738 37500 81176 66000 23118 47601 71143 47750 18214 42000 32303 50987 23372 28925 143737 42050 58561 51738 9691 51500 23969 44988 48781 29500 114809 46975 16918 63999 15507 46975 16918 43222 50459 38386 87192 42000 68722 62250 14042 62998 21738 32130 103644 52293 34450 52900 68883 53172 3656 53494 315 39594 88441 63246 23631 58250 34974 59391 18383 50650 42737 54976 84200 68650 14401 51114 47433 43900 74106 37450…
Predict the average lifespan of an animal in years when the incubation/gestation time is 12 months. Animal: Nile crocodile, Aldabra giant tortoise, Lake sturgeon,Galápagos tortoise, Bowhead whale Average Lifespan (in Years):100 152 152 177 211 Incubation/ Gestation (in Months)3 8 0.25 4.7 regression equation and regression line if needed
What percentage of the variation in infant mortality rate is explained by this model? Based on the results of the ANOVA table, is this a good model and why or why not? Is the relationship between percentage of GDP spent on healthcare and infant mortality rate statistically significant? What is the direction of the relationship? For each one percent increase in percentage of GDP spent on health care, we would expect the infant mortality rate to ________ (increase or decrease) by _____.
Using data from 50 workers, a researcher estimates Wage Be + B₁Education + B2Experience + B3Age +, where Wage is the hourly wage rate and Education, Experience, and Age are the years of higher education, the years of experience, and the age of the worker, respectively. A portion of the regression results is shown in the following table. Coefficients Standard Error t Stat p-Value Intercept 7.45 3.79 1.97 0.0554 Education 1.06 0.37 2.86 0.0063 Experience 0.37 0.18 2.06 0.0455 Age -0.02 0.06 -0.33 0.7404 a-1. Interpret the point estimate for ẞ1. As Education increases by 1 year, Wage is predicted to increase by 1.06/hour. As Education increases by 1 year, Wage is predicted to increase by 0.37/hour. As Education increases by 1 year, Wage is predicted to increase by 1.06/hour, holding Age and Experience constant. As Education increases by 1 year, Wage is predicted to increase by 0.37/hour, holding Age and Experience constant. a-2. Interpret the point estimate for ẞ2. ○ As Experience…
Using the data, run a regression where you control for “Promotion,” and test the effect of “Wins” on “Attendance”. Does “Promotion” have a significant effect on “Attendance”? Wins Promotion Attendance 4 29500 36300 6 55700 40100 6 71300 41200 8 87000 53000 6 75000 44000 7 72000 45600 5 55300 39000 7 81600 47500
a) Determine the least squares regression equation for the population in years since 2005. Round the slope and y-intercept to the nearest tenth. b) Find the correlation coefficient, r-value, of the line. Round your answer to the nearest thousandth. c) Predict the population for the 2020. ____ thousand people
statistic please answer
PVan
please answer for what is the p value

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