ResidualsBelly Girth vs. Residuals, Possum Model3--3-2530Belly Girth (cm)40ResidualsOrder vs. Residuals, Possum Model3--3-02550Index75100FrequencyResidual Histogram Plot, Possum Model15-10-5-0-0Residuals(a) Interpret the intercept and slope in the context of the problem.(b) Check the assumptions of linearity, independence, constant variance, and normality. Provide a 1-sentenceexplanation for each as to why you believe they are either met or not met.(c) Calculate the R² value and interpret it.(d) Give a brief 2-3 sentence discussion of if the model looks good/can be trusted. If not, explain why not. (4) Does how wide a possum's belly is (in cm) tell you how long a possum's tail is (in cm)? That's what re-searchers in Australia wanted to know. They built a simple linear regression model treating X as the possum'sbelly girth and Y as the possum's tail length. Below and at the top of the next page are all the results you willneed to answer the ensuing questions, including:● The straight line of best fit: ŷ= 30.2 + .21x• The correlation between the observed y and predicted ŷ: ry,ŷ.294• At the top of the next page are three residual plots: (a) the plot of belly girth vs. the residuals, (b) the plotof the residuals in order of collection, (c) the histogram of the residuals=These are real data (source) consisting of measurements on each of 104 mountain brushtail possums, trappedat seven sites from Southern Victoria to central Queensland, Australia.

Consider the given linear regression equation: y^=30.2+0.21x Where, x=Possum's belly girth…

Answered: (4) Does how wide a possum's belly is…

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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State the regression equation and use it to predict taxes for a house with lot size 10K.
The U.S. Postal Service is attempting to reduce the number of complaints made by the public against its workers. To facilitate this task, a staff analyst for the service regresses the number of complaints lodged against an employee last year on the hourly wage of the employee for the year. The analyst ran a simple linear regression in SPSS. The results are shown below. The current minimum wage is $5.15. If an employee earns the minimum wage, how many complaints can that employee expect to receive? Is the regression coefficient statistically significant? How can you tell?
I was wondering specifically about part D and how to interpret my findings.
Stoaches are fictional creatures that nest in truffula forests. A researcher wants to know whether there is a relationship between a stoach’s wingspan (?W, the predictor) and its nest height (?H, the response). A sample of 88 stoaches is observed, and for each, the wing-span (in cm) and the nest height (in m) are recorded. The observed data meet the assumptions for a linear regression, so the researcher fits the regression model and obtains a regression equation ℎ̂=−0.813+0.177?,h^=−0.813+0.177w, with standard error for the coefficient of ?w equal to 0.448. Determine the ?p-value from a test for a statistically significant linear dependence of nest height on wing-span. (Give your answer to 4 decimal places.
Use the given data to find the scatter plot, equation of the regression line, and prediction. 4) Managers rate employees according to job performance and attitude. The results for several randomly selected employees are given below. Performance 59 63 65 69 58 77 76 | 69 70 64 Attitude 72 67 78 82 75 87 92 83 87 78 What function do you use to see the scatterplot on the calculator. Scatterplot from the calculator:
Stoaches are fictional creatures that nest in truffula forests. A researcher wants to know whether there is a relationship between a stoach’s wingspan (?W, the predictor) and its nest height (?H, the response). A sample of 85 stoaches is observed, and for each, the wing-span (in cm) and the nest height (in m) are recorded. The observed data meet the assumptions for a linear regression, so the researcher fits the regression model and obtains a regression equation ℎ̂=−4.273+0.834?,h^=−4.273+0.834w, with standard error for the coefficient of ?w equal to 0.242. Determine the ?p-value from a test for a statistically significant linear dependence of nest height on wing-span. (Give your answer to 4 decimal places.
The accompanying table shows a portion of data that refers to the property taxes owed by a homeowner (in $) and the size of the home (in square feet) in an affluent suburb 30 miles outside New York City. Click here for the Excel Data File Taxes Size 21,987 2,403 17,353 2,451 29,238 2,866 a. Estimate the sample regression equation that enables us to predict property Taxes on the basis of the size of the home. (Round your answers to 2 decimal places.) Taxes = + Size. b. Interpret the slope coefficient. O As Property Taxes increase by 1 dollar, the size of the house increases by 6.71 ft. O As Size increases by 1 square foot, the property taxes are predicted to increase by $6.71. c. Predict the property Taxes for a 1,400-square-foot home. (Round coefficient estimates to at least 4 decimal places and final answer to 2 decimal places.) Taxes
Is it reasonable to interpret the y-intercept of the regression line? Why or why not? One home that is 1,750 square feet is listed at $590,000. Is this home's price above or below average for a home of this size? Use residuals and show your work to answer. footaget) ## (Intercept) 21.14411 136.31449 0.155 0.87954 ## footage 0.28388 0.08516 3.333 0.00667 ** ## Residual standard error: 71.64 on 11 degrees of freedom ## Multiple R-squared: 0.5025, Adjusted R-squared: 0.4573 ## F-statistic: 11.11 on 1 and 11 DF, p-value: 0.006671
Create two lists and make a scatterplot of the data and find the line-of-best-fit (regression line). For part a below, round all number values in your answer to the nearest tenth. a) What is the equation of the line-of-best-fit? ________________________ b) To the nearest thousandth, what is the value of the correlation coefficient, r ? _________ c) According to the regression equation from part a, what is the predicted salary for year 8? Round your answer to the nearest dollar. __________________
4)
write the regression code for the following data based on the below instruction, in STATA. hint: occupation=a categorical variable equal to ”1” if a person’s occupation is ”management”; ”2” if it is ”sales”; ”3” if it is ”clerical”, ”4” if it is ”service”, ”5” if it is ”professional” and ”6” if it is ”other”. Please make sure to use ”other” as the base category;
Bluereef real estate agent wants to form a relationship between the prices of houses, how many bedrooms, House size in sq ft and Lot Size in sg ft. The data pertaining to 100 houses were processed using MINITAB and the following is an extract: The regression equation is Price = B + ÞBedroom + yHouse Size + ALot Size Predictor Coef SE Coef T P Constant 37718 14177 2.66 ** Bedrooms 2306 6994 0.33 0.742 House Size 74.3 52.98 0.164 Lot Size -4.36 17.02 -0.26 0.798 s= 25023 R-Sq=56.0% R-Sq(adj)=54.6% Source DF MS F P Regression Residual 3 76501718347 25500572782 **** Error 96 60109046053 626135896 Total 99 1. Fill in the missing values *, **, and **** 2. Use the p-value approach to determine if o is significant at the 5% significance level

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