a)The alternative hypothesis is:O H1 : The covariance between CVD and Enrollment Site is negative.H1 : The correlation between CVD and Site is zero.O H1 : CVD and Enrollment Site are independent.O H1 : CVD and Enrollment Site are dependent.O H1 : The covariance between CVD and Enrollment Site is positive.O H1 : The covariance between CVD and Site is zero.b)Under independence, calculate the expected number of patients with a family history of CVD, at Hospital 3.Round your answer to 2 decimal places. A cross-sectional study is conducted to investigate cardiovascular disease (CVD) risk factors among a sample of patients seeking medical care at one ofthree local hospitals. A total of 800 patients are enrolled. Based on the following data, we would like to determine if there is a significant associationbetween the family history of CVD and the enrollment site.Enrollment SiteFamily History of CVDHospital 1Hospital 2Hospital 3TotalYes342838100No182126392700Total216154430800• Given:The value of the test statistic is x? = 11.894.Use a = 0.1 as the level of significance.

Test is that whether there is a significant association between the family history of CVD and the…

Answered: The alternative hypothesis is: O H1 :…

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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Refer to the Baseball 2018 data given below, which report information on the 30 Major League Baseball teams for the 2018 season. Let the number of games won be the dependent variable and the following variables be independent variables: team batting average, team earned run average (ERA), number of home runs and whether the team plays in the American or National league (American League is 1 and National League is 0). a. Develop a correlation matrix. (i) Which independent variables have strong or weak correlations with the dependent variable. (ii) Do you see any problems with multicollinearity? Explain your answer. b. Use Excel to determine the multiple regression equation. (i) Write out the regression equation and determine its practical application (i.e., interpret the equation). (ii) Report and interpret the R-square. c. Conduct a global test on the set of independent variables. Interpret. d. Conduct a test of hypothesis on each of the independent variables. Would…
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In baseball, is there a linear correlation between batting average and home run percentage? Let x represent the batting average of a professional baseball player, and let y represent the player's home run percentage (number of home runs per 100 times at bat). A random sample of n = 7 professional baseball players gave the following information.
A data set includes weights of garbage discarded in one week from 62 different households. The paired weights of paper and glass were used to obtain the results shown to the right. Is there sufficient evidence to support the claim that there is a linear correlation between weights of discarded paper and glass? Use a significance level of a = 0.05. Correlation matrix: Variables Paper Glass Раper 10.0979 Click here to view a table of critical values for the correlation coefficlent, Glass 0.0979 1 Determine the null and alternative hypotheses. Ho p H p (Type integers or decimals. Do not round.) Identify the test statistic, r. =| |(Round to three decimal places as needed.)
Table of critical values shown to the right. Is there sufficient evidence to A data set includes weights of garbage discarded in one week from 62 different hou support the claim that there is a linear correlation between weights of discarded pa Correlation matrix: Variables Paper Glass Click here to view a table of critical values for the correlation coefficient. |Раper 10.3890 Glass 0.3890 1 a = .05 a = 01 4 .950 .990 .878 .959 Determine the null and alternative hypotheses. 6 .811 .917 7 .754 .875 Ho: P 8. .707 .834 9. .666 .798 (Type integers or decimals. Do not round.) 10 .632 .765 11 .602 .735 Identify the test statistic, r. 12 .576 .708 13 .553 .684 r = (Round to three decimal places as needed.) 14 .532 .661 15 .514 .641 Identify the critical value(s). (Round to three decimal places as needed.) 16 .497 .623 17 .482 .606 O A. There is one critical value at r= 18 .468 .590 19 .456 .575 B. There are two critical values at r = ± 20 .444 .561 25 .396 .505 State the conclusion. 30 .361…
Note that this uses minitab. Make a scatterplot that will enable you to predict BBAC from number of beers consumed. What is the correlation coefficient?
For a data set of weights (pounds) and highway fuel consumption amounts (mpg) of seven types of automobile, the linear correlation coefficient is found and the P-value is 0.021. Write a statement that interprets the P value and includes a conclusion about linear corelation. The P-value indicates that the probability of a linear correlation coefficient that is at least as extreme is %, which is so there sufficient evidence to conclude that there is a linear correlation between weight and highway fuel consumption in automobiles. (Type an integer or a decimal. Do not round.)
Are MRI count and IQ linearly related? Because the correlation coefficient for females is negative/positiveand the absolute value of this correlation coefficient, enter your response here#, is greater/not greater than enter your response here#, the critical value for the female data set,no/a positive/a negativerelation exists between MRI count and IQ for females. Because the correlation coefficient for males is negative/positive and the absolute value of this correlation coefficient, enter your response here#, is greater/not greater than the critical value for the male data set, enter your response here#,no/a positive/a negative relation exists between MRI count and IQ for males. (Round to three decimal places as needed.) Critical value table 3 0.997 4 0.950 5 0.878 6 0.811 7 0.754 8 0.707 9 0.666 10 0.632 11 0.602 12 0.576 13 0.553 14 0.532 15 0.514 16 0.497 17 0.482 18 0.468 19 0.456 20 0.444 21 0.433 22 0.423 23 0.413 24 0.404 25 0.396 26 0.388 27 0.381 28 0.374…
For a data set of weights (pounds) and highway fuel consumption amounts (mpg) of twelve types of automobile, the linear correlation coefficient is found and the P-value is 0.022. Write a statement that interprets the P-value and includes a conclusion about linear correlation. The P-value indicates that the probability of a linear correlation coefficient that is at least as extreme is %, which is so there sufficient evidence to conclude that there is a linear correlation between weight and highway fuel consumption in automobiles. (Type an integer or a decimal. Do not round.)
Refer to the Baseball 2018 data given below, which report information on the 30 Major League Baseball teams for the 2018 season. Let the number of games won be the dependent variable and the following variables be independent variables: team batting average, team earned run average (ERA), number of home runs and whether the team plays in the American or National league (American League is 1 and National League is 0). a. Develop a correlation matrix. (i) Which independent variables have strong or weak correlations with the dependent variable. (ii) Do you see any problems with multicollinearity? Explain your answer. b. Use Excel to determine the multiple regression equation. (i) Write out the regression equation and determine its practical application (i.e., interpret the equation). (ii) Report and interpret the R-square. c. Conduct a global test on the set of independent variables. Interpret. d. Conduct a test of hypothesis on each of the independent variables. Would…
A sample of 548 ethnically diverse students from Massachusetts were followed over a 19-month period from 1995 and 1997 in a study of the relationship between TV viewing and eating habits. For each additional hour of television viewed per day, the number of fruit and vegetable servings per day was found to decrease on average by 0.14 serving. (a) For this study, what is the dependent variable? O location of students O number of fruit and vegetable servings per day O number of non fruit or vegetable servings per day O number of hours of television viewed per day year What is the independent variable? O location of students O number of fruit and vegetable servings per day O number of non fruit or vegetable servings per day O number of hours of television viewed per day O year (b) Would the least-squares line for predicting number of servings of fruits and vegetables using number of hours spent watching TV as a predictor have a positive or negative slope? Explain. O The slope of the least…
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