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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It may be a concern that market value and assets are highly correlated and hence there may be a problem with including them both as explanatory variables. The following set of output is for the regression that excludes assets from the regression above. Based on this set of output, does it seem likely that assets and market value are highly correlated, and hence does it appear that multicollinearity is a problem? Explain how you know.
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
I need help with this question 1. What type of analysis is this ( give the most descriptive name possible)?
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…
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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
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
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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 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 D E G 1.51E-18 Residual C 7448393 F Total 49 42699149 Coefficients Standard Error t Stat P-value Intercept 1304.9048 197.6548 6.6019 3.29E-08 Income ($1000s) 33.133 3.9679 H 7.68E-11 Household Size 356.2959 33.2009 10.7315 3.12E-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…
2:51 A flush in the card game of poker occurs if a player gets five cards that are all the same suit (clubs, diamonds, hearts, or spades). Complete parts (a) and (b) to obtain the probability of being dealt a flush in five cards. (a) Initially concentrate on one suit, say clubs. There are 13 clubs in a deck. Compute P(five clubs) = P(first card is clubs and second card is clubs and third card is clubs and fourth card is clubs and fifth card is clubs). P(five clubs) = 0.000495 (Round to six decimal places as needed.) (b) A flush can occur if a player receives five clubs or five diamonds or five hearts or five spades. Compute P(five clubs or five diamonds or five hearts or five spades). Note that the events are mutually exclusive. P(five clubs or five diamonds or five hearts or five spades) = (Round to three decimal places as needed.) Vo) 1 LTE 4G 1% ||| = O

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