a) Find the equation of the regression line. Provide slope and y-intercept, explicitly. Ifyou can’t find slope, use slope = −500.b) Create a 95% confidence interval for the slope of the regression line and explain whatyour interval means in the context of this problem. Provide Lower Confidence Limit andUpper Confidence Limit explicitly. 5. Classified ads in a website offered several used Toyota Corollas for sale. Listed beloware the ages (x) of the cars and the advertised prices (y).Price Advertised12000Age (yr)Prices ($)Age (yr)Prices ($) 69994000 6000 80001139906Figure 1 plots x against y. Calculation shows that: n = 15; ñ = 6.13 and S₁ = 3.38; y =8403.8 and Sy = 3333.58; Say = -10942.26 and (y₁ - y)² = 8660659.=14551349510495 8995 9495781010136950 7850 6999 5995 4950 4495 285023412999 950078Figure 1uercu6Age8●●1012

Regression is the method used for prediction. It has two types of variables and two types of…

a) Find the equation of the regression line. Provide slope and y-intercept, explicitly. If you can’t find slope, use slope = −500. b) Create a 95% confidence interval for the slope of the regression line and explain what your interval means in the context of this problem. Provide Lower Confidence Limit and Upper Confidence Limit explicitly.

a) Find the equation of the regression line. Provide slope and y-intercept, explicitly. If you can’t find slope, use slope = −500. b) Create a 95% confidence interval for the slope of the regression line and explain what your interval means in the context of this problem. Provide Lower Confidence Limit and Upper Confidence Limit explicitly.

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 researcher plans to study the causal effect of police on crime using data from a random sample of U.K. counties. He plans to regress the county’s crime rate on the (per capita) size of the county’s police force. Explain why this regression is likely to suffer from omitted variable bias. Which variable would you add to the regression to controlfor important omitted variable? Determine whether the regression will likely over or underestimate the effect of police on the crime rate?
Show the best fitted line on scatter diagram and Find the predicted value for each y using the exposure time and the equation obtained in part b (b. Find the equation of regression line between radiation doses on exposure time .usingleast square method)
Please show all working manually
Provide an example of a regression that arguably would have a high value of R² but would produce biased and inconsistent estimators of a causal effect. Explain why the R² is likely to be high. Explain why the OLS estimators would be biased and inconsistent.
Does the Regression line give information about all the data points in the data set? Does the Regression line usually have all the points in the data set on it?
Write the linear model to test the hypothesis that there is no treatment effect. Clearly describe each term in the model, and the range of the subscripts. Write the null hypothesis that you are testing. Call: lm(formula = score ~ list, data = hearing) Residuals: Min 1Q Median 3Q Max -14.7500 -5.5833 -0.2083 6.3333 16.4167 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 32.750 1.612 20.315 < 2e-16 *** listList2 -3.083 2.280 -1.352 0.17955 listList3 -7.500 2.280 -3.290 0.00142 ** listList4 -7.167 2.280 -3.144 0.00225 ** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 7.898 on 92 degrees of freedom Multiple R-squared: 0.1382, Adjusted R-squared: 0.1101 F-statistic: 4.919 on 3 and 92 DF, p-value: 0.00325
The line of best fit through a set of data isy=21.974+1.021xy=21.974+1.021xAccording to this equation, what is the predicted value of the dependent variable when the independent variable has value 140? Y=
The following regression equation is based on the analysis of four variables: SM_DOLLARS is the dollar amount of a watershed conservation agency's weekly spending on social media ads. RADIO_ADS is the number of radio advertisements aired weekly by the agency. WS_DOLLARS is the dollar amount of the agency’s weekly spending on web search ads. The variable WEB_VISITS is the number of weekly visitors to their educational website. These data have been recorded every week for the past three years. WEB_VISITS (expected) = 208 + 1.25*SM_DOLLARS + 1.5*RADIO_ADS + 1.2*WS_DOLLARS The data meet the assumptions for regression analysis, and the regression results, including the coefficients, were found to be statistically significant. Initially, $320 was spent on social media ads, 10 radio ads were aired, and $120 spent on web search ads. How many additional weekly web visits would you predict when the agency increases its weekly spending on social media ads by $440 without changing the…
Hawk thinks his heartrate will increase as he increases his skateboarding speed. To see if this relationship exists, he records six different speeds and models it with a scatterplot and regression output. Part A: Write the equation of the regression line using the regression output. Part B: What do the slope and intercept parameters mean using the context of the problem? Part C: Compute the margin of error that Hawk should use if he wants to provide a 99% confidence interval for the slope. Assume that conditions for inference are satisfied.