Problem 7.3.A study of the amount of rainfall (x) and the quantity of air pollution removed (mea-sured by the amount of particulate removed y) produced the followingxy4.3 4.5 5.9 5.6 6.1 5.2 3.8 2.1 7.5126 121 116 118 114 118 132 141 108(a) State a linear regression model to describe the relationship between the amountof particulate removed and the daily rainfall. Estimate the linear regression line.(b) Estimate the weekly sales when advertising costs are 35.(c) Find an unbiased estimator of the variance of errors.(d) Find the coefficient of determination and interpret the result.(e) Test on the slope coefficient to determine whether there exists a negative linearrelationship between the amount of particulate removed and the daily rainfall at5% level of significance.

xy4.31264.51215.91165.61186.11145.21183.81322.11417.5108The dependent variable indicates the amount…

Answered: Problem 7.3. A study of the amount of…

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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Listed below is the multiple regression equation for predicting Y by X₁ through Xs. Y is the number of sales per month. X₁ is the number of sales calls made X2 is the number of hours on the showroom floor X3 is the amount spent on radio ads X is the number of text messages sent Xs is the number of email messages sent Regression Statistics R Square 0.634 Standard Error 7.6796 Observations 45 Intercept X₁ X₂ X3 XA Xs Coefficients Standard Error 6.8163 0.1005 -0.3207 0.2084 0.1221 0.0943 77.1211 1.9439 -11.123 0.1144 11.34 1.23 What is the computed value of the F statistic you would use to test the significance of the entire model? Round your answer to two decimal places.
1. Question: Malaria is a leading cause of infectious disease and death worldwide. It is also a popular example of a vector-borne disease that could be greatly aﬀected by the inﬂuence of climate change. Table 1 is a summary from a linear regression that uses dewpoint (°C) to predict malaria prevalence in West Africa.Fig. 1: Regression(a) Write the equation of the least square regression line. (b) Find the correlation coeﬃcient r. (c) IsthereastrongcorrelationbetweendewpointandmalariaprevalenceinWestAfrica? (d) Is there a negative association between dewpoint and malaria prevalence in West Africa?
The following is the simple regression results based on the data from Madrigal Corporation: Dependent variable – Machine maintenance costs Independent variable – Machine hours Computed values Intercept P 3,500 Coefficient on independent variable P 3.50 Coefficient of correlation 0.856 R2 0.733 What percentage of the variation in maintenance costs is explained by the independent variable? (use two decimal places, e.g. 82.20%, 55.31% or 0.82, 0.55, these will be counted as correct answers)
You are given the following data, where X1 (final percentage in math class) and X2 (number of absences) are used to predict Y (standardized math test score in third grade): Y X1 X2 345 70 390 80 1 370 75 4 375 92 400 82 350 70 3 310 61 5 420 80 375 88 3 410 72 1 485 99 300 65 7 Determine the following multiple regression values. Report intercept and slopes for regression equation accurate to 3 decimal places: Intercept: a = Partial slope X1: bị = Partial slope X2: bz = Report sum of squares accurate to 3 decimal places: SSreg Test the significance of the overall regression model (report F-ratio accurate to 3 decimal places and P-value accurate to 4 decimal places): F-ratio = P-value = Report the variance of the residuals accurate to 3 decimal places: Sres = Report the results for the hypothesis test for the significance of the partial slope for final percentage in math class (report the test statistic for the regression coefficients accurate to 3 decimal places and P-value accurate to…
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46. Table 1.3 lists the ages and weights of nine girls. TABLE 1.3 Girls' Ages and Weights Age (months) Weight (pounds) 22 19 23 21 24 25 27 28 29 31 31 28 34 32 38 34 43 39 (a) Find the linear regression equation for the data. (b) Find the slope of the regression line. What does the slope represent? (c) Superimpose the graph of the linear regression equation on a scatter plot of the data. (d) Use the regression equation to predict the approximate weight of a 30-month-old girl..
nkt.1
The table below shows (lifetime) peptic ulcer rates (per 100 population), UU, for various family incomes, xx, as reported by the 1989 National Health Interview Survey. Income 4000 6000 8000 12000 16000 20000 30000 45000 60000 Ulcer rate 14.1 13.1 13.8 12.6 11.8 11.7 11.5 9.3 7.6 (a) Find the equation of the regression line. Ulcer rate, U(x)= . (b) Estimate the peptic ulcer rate for an income level of x0= 25000 according to the linear model in part (a). Ulcer rate, U(x0)= .
solve 11.7 The data in Table 11.17 are given for 9 patients with aplastic anemia 11.1 Fit a regression line relating the percentage of reticulocytes (x) to the number of lymphocytes (y) 11.7 What are the standard errors of the slope and intercept for the regression line in Problem 11.1?
In the graph shown below consider the horizontal line to represent the average y value for the data set and the slant line to represent the linear regression equation. use only the graph of the data to do the following:

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