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Applied Statistics Techniques, Homework #1 For questions, you can calculate sample covariance, sample variance, sample mean, z values, t values, and F values by using any statistical software....

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Applied Statistics Techniques, Homework #1 For questions, you can calculate sample covariance, sample variance, sample mean, z values, t values, and F values by using any statistical software. However, please note that you need to do the rest of the calculations by using a portable calculator in preparation for exams. Finally, please show all the calculation processes for partial points. Question 1 for the survey data. (25 points) ? Provide sample Pearson correlation coefficient for “intimacy” and “commit”.
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Applied Statistics Techniques, Homework #1 For questions, you can calculate sample covariance, sample variance, sample mean, z values, t values, and F values by using any statistical software. However, please note that you need to do the rest of the calculations by using a portable calculator in preparation for exams. Finally, please show all the calculation processes for partial points. Question 1 for the survey data. (25 points) ? Provide sample Pearson correlation coefficient for “intimacy” and “commit”. (5 points) ? Obtain 90% confidence interval of the population Pearson correlation coefficient. (10 points) ? Test the null hypothesis, H : , H : under the desired significance level, 0 1 XXXXXXXXXXpoints) Question 2 for the salary data. (55 points) ? ,? ? Estimate in the case that the response is “salary” and the predictor is “years”. (15 1 0 points) ? Obtain ANOVA table. (20 points) ? Obtain 90% confidence interval of ? XXXXXXXXXXpoints) 1 ? Test the null hypothesis, H : H : under the desired significance level, 0 1 XXXXXXXXXXpoints) Question 3 for the hypothetical data. (20 points) ? Obtain grand mean and unadjusted means for the ANCOVA model where covariate, ”xc”, Treatment, “a”, response, “y” are considered. (5 points) ? Calculate adjusted means given the estimates below. (15 points) Coefficients: (Intercept XXXXXXXXXXxc XXXXXXXXXXa XXXXXXXXXXa3 XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX

Answered Same Day Dec 22, 2021

Solution

Robert answered on Dec 22 2021
128 Votes
1 z<-read.table("C:/Users/Desktop/survey data.csv",header=TRUE,sep=",")
z6<-z[,6]
z7<-z[,7]
cor.test(z6,z7,alternative=c("greater"),method=c("pearson"),conf.level=0.9)
2 a<-read.table("C:/Users/Desktop/q1.csv",header=TRUE,sep=',')

-a[,1]
d<-a[,3]
e<- lm(b~d,data=a)
summary(e)...
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