InterceptAdmissionsOA).9774288B) 1.51O C) .98706O D).668591O E) 6.59E-11Coefficients1.5180530.668591Standard Error3.2489290.031354t Stat0.46724721.32375P-value0.6486936.59E-11Lower 95%-5.560750.600276Upper 95%8.596860.736907 The total expenses of a hospital (dependent variable) are related to many factors. One of these factors is the number of admissions to the hospital (independent variable). Usingthe summary output below to answer, what is the correlation coefficient?SUMMARY OUTPUTMultiple RR SquareAdjusted R SquareStandard ErrorObservationsANOVARegression StatisticsRegressionResidualTotal0.987060.9742880.9721458.106794df1411213SS29883.07788.6412306,71.71MS29883.0765.7201F454.7022Significance F6.59E-11

The correlation shows the relationship between two variables.

Answered: The total expenses of a hospital…

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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Dex Research Limited conducted a research to investigate consumer characteristics that can be used to predict the amount charged by credit card users. The following multiple regression output is based on a data collected by this research company on annual income, household size and annual credit card charges for a sample if 50 consumers. Regression Statistics Multiple R R Square Adjusted R Square Standard Error 0.9086 A 0.8181 398.0910 Observations ANOVA df SS MS Significance F Regression 2 1.50876E-18 Residual C 7448393.148 F Total 49 42699148.82 Coefficients Standard Error t Stat P-value Intercept 1304.9048 197.6548 6.6019 3.28664E-08 Income ($1000s) 33.1330 3.9679 H 7.68206E-11 Household Size 356.2959 33.2009 10.7315 3.12342E-14 a. Complete the missing entries from A to H in this output b. Estimate the annual credit card charges for a three-person household with an annual income of $40,000. C. Did the estimated regression equation provide a good fit to the data? Explain
Dex Research Limited conducted a research to investigate consumer characteristics that can be used to predict the amount charged by credit card users. The following multiple regression output is based on a data collected by this research company on annual income, household size and annual credit card charges for a sample if 50 consumers. Regression Statistics Multiple R 0.9086 R Square A Adjusted R Square 0.8181 Standard Error 398.091 Observations B ANOVA df SS MS F Significance F Regression 2 C E G 1.50876E-18 Residual D 7448393 F Total 49 42699149 Coefficients Standard Error t Stat P-Value Intercept 1304.9048 197.6548 6.6019 3.28664E-08 Income ($1000s) 33.1330 3.9679 H 7.68206E-11 Household size 356.2959 33.2009 10.7315 3.12342E-14 a. Complete the missing entries from A to H in this outputb. Estimate the annual credit card charges…
pare percentage differences between 2 or more categories of an independent variable), the following statistical test should be used: a. Simple linear regression b. Pearson correlation coefficient c. T test d. Chi-square test
How much would you expect systolic blood pressure to change if a person commits to reducing their cigarette consumption by 1 cigarette per day?
Listed below are paired data consisting of amounts spent on advertising (in millions of dollars) and the profits (in millions of dollars). Determine if there is a significant linear correlation between advertising cost and profit Use a significance level of 0.01 and round all values to 4 decimal places. Advertising Cost Profit 3 21 4 16 5 29 17 7 28 8 21 Ho: p = 0 Ha: p +0 Find the Linear Correlation Coefficient r= Find the p-value p-value = The p-value is Less than (or equal to) a OGreater than a The p-value leads to a decision to Do Not Reject Ho OReject Ho OAccept Ho
When there are omitted variables in your regression, then... Group of answer choices This has no effect on the estimation of the explanatory variable because the variable is omitted This will always bias the OLS estimation of the explanatory variable the estimation of the explanatory variable(s) is unaffected The OLS estimation is biased if the omitted variables are correlated with the included variable
Ankit
Using the following information: Coefficients Intercept -12.8094 Independent variable 2.1794 ANOVA df SS MS F Regression 1 12,323.80 12,323.80 90.0481 Residual 8 1,454.602 136.8550 Total 9 13,778.4 What is the correlation coefficient? Multiple Choice 0.8944 0.9457 −0.9457 0.8878

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