he variable which has an insignificant effect on the duration of the stop is _____ CoefficientsStandard Errort StatP-valueLower 95%Upper 95%Intercept6.6237080.41316616.031611.1E-575.8138977.433519age-0.011040.001583-6.970623.2E-12-0.01414-0.00793height-0.008260.006816-1.21230.225405-0.021620.005096weight0.002460.000743.3252530.0008840.001010.003911arstmade1.8445180.07726423.873083.3E-1251.693081.995956Black-0.474630.037618-12.6171.95E-36-0.54836-0.4009sex-0.745610.074776-9.971292.15E-23-0.89218-0.59905Group of answer choicesheightageWeightBlackSex PreviousNext

Answered: he variable which has an insignificant…

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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is a scatterplot with RSquared equal to 0.022418 and Root Mean Square error equal to 2.422091 a good model and what do those two valus tell you about the graph. Picture of scatter plot attached.
None
determine if the frequency of deficiencies of variable (medication errors) are statistically significantly different between for-profit and non-profit nursing homes, interpret the results for the chi-square?
Q9. Using the diagram below Deviation from mean of YTSS Error → ESS Explained by regressionRSS Mean of Y Regression line identify the incorrect statement. A. TSS is a measure based on the whole deviation of Y from its mean. В. ESS is based on that part of the deviation of Y not related to the change in X. С. RSS is based on that part of the deviation caused by the change in X. D. At least one of the above statements is False. Ο Α. Α О В. В ОС. С O D. D
The commercial division of a real estate firm is conducting a regression analysis of the relationship between x, annual gross rents (in thousands of dollars), and y, selling price (in thousands of dollars) for apartment buildings. Data were collected on several properties recently sold and the following computer output was obtained. Analysis of Variance SOURCE DF Adj SS Regression 1 41587.3 Error 7 Total 8 51984.1 Predictor Coef SE Coef T-Value Constant 20.000 3.2213 6.21 X 7.210 1.3626 5.29 Regression Equation Y = 20.0 + 7.21 X (a) How many apartment buildings were in the sample? (b) Write the estimated regression equation. ŷ = (c) What is the value of sb1? Find the value of the test statistic. (Round your answer to two decimal places.) Find the p-value. (Round your answer to three decimal places.) p-value =
In this regression, which predictor(s) is/are significant? Coefficients: (Intercept) time pub O'pubs' Neither 'time' Both Estimate Std. Error t value Pr (>|t|) 43082.4 3099.5 13.900 9.26e-09 982.9 121.8 452.1 2.174 0.0504 149.7 0.814 0.4317
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What does the slope and the intercept mean in this setting?
Match each assumption on the left with the corresponding plot used to check it. Normally Distributed Residuals Linear Relationship between X and Y variables Constant variability of residuals Mean of the residuals is zero Q-Q Plot Studentized Residual Plot Profile Plot of Means Histogram Boxplot Scatterplot Q-Q Plot
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	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	6.623708	0.413166	16.03161	1.1E-57	5.813897	7.433519
age	-0.01104	0.001583	-6.97062	3.2E-12	-0.01414	-0.00793
height	-0.00826	0.006816	-1.2123	0.225405	-0.02162	0.005096
weight	0.00246	0.00074	3.325253	0.000884	0.00101	0.003911
arstmade	1.844518	0.077264	23.87308	3.3E-125	1.69308	1.995956
Black	-0.47463	0.037618	-12.617	1.95E-36	-0.54836	-0.4009
sex	-0.74561	0.074776	-9.97129	2.15E-23	-0.89218	-0.59905