Researchers at the Mayo Clinic found a significant association between hospital sound levels and patient healing (louder hospital sound level is associated with slower healing). Based on these findings, a new hospital installed a new flooring that is supposed to reduce the noise level in hospital corridors. Using α = 0.01, did the variance of noise level decrease? (use both methods) Problem 4: Mayors of nine communities started a watch program to reduce vandalism. The number of vandalism incidents before and after starting the watch program was collected for each community. Does the data collected show that the watch program was effective? (use both methods)

Mayors of nine communities started a watch program to reduce vandalism. The number of vandalism incidents before and after starting the watch program was collected for each community. Does the data collected show that the watch program was effective? (use both methods)

using excel

All Time Box Office Revenues Aggregated by Months

1. Calculate the mean for the gross revenues.
2. Calculate the mean for the Movies tracked.
3. Calculate the standard deviation for the movies tracked.

You have been given the final results of this study. What are your conclusions? Describe your conclusions and how you derived them.

RQ: To what extent does our new composite material improve load-bearing capacity of aircraft wings?

Ha: Aircraft wings constructed with the new composite material will have greater load bearing capacity than aircraft wings that are not constructed with the new material.

H0: There is no difference between composite aircraft wing load bearing capacity and other aircraft wings.

Population 1: Aircraft wings constructed with a new composite material.

Population 2: Aircraft wings in general.

• Confidence Interval: 95%
• Population Mean = 59.945, Sample N=50, Sample X-bar=61, Sample SD=4, p=.034

Part I:

How the analysis was derived

Conclusion (Find each one)

Test that was conducted
Description of the data
Confidence interval selected
One or two tail test selected
T-critical value(s)
Test statistics (t-stat)
Decision to reject or not reject the null hypothesis by comparing the t-critical value to the test statistics
Statistically significant statement

Listed below are amount of court income and salaries paid to the town justices. All amounts are in the thousands of dollars. Construct a scatteplot salaries? Base on the results, dose it appears that justices might profit by levying large fines?
Court Income- 66.0 405.0 1566.0 1130.0 273.0
Just Salary-         31   43         90        57      48

250.0 110.0 150.0 31.0
62          26     27   17
post one question

Question # 1:A dispensing machine is set to produce 1 pound lots of a particular compound. The machine is fairly accurate, producing mean weight of lots equal to 1.0 pound with a standard deviation of 0.12 pounds. Thirty five lots are randomly selected:

(a)What is the mean weight of the sample mean of the thirty five randomly selected lots?

(b)What is the standard deviation of weight of the sample mean of the thirty five randomly selected lots?

(c)Find the probability that the mean weight is greater than 1.1 pounds.

(d)Find the probability that the mean weight is less than 0.95 pounds

1. What is the difference between the Sampling Distribution of a Proportion and theSampling Distribution of a Mean? (3 points)

2. What is the mean of the sample means? (2 points)

3. What is the standard deviation of the sample means? (2 points)

Construct a scattergram for each data set. Then calculate r and r 2 for each data set. Interpret their values. Complete parts a through d

Calculate r.

r=. 9853 ​(Round to four decimal places as​ needed.)

Calculate r2.

r2=0.9709. ​(Round to four decimal places as​ needed.)

Interpret r. Choose the correct answer below.

A.There is not enough information to answer this question.

B.There is a very strong negative linear relationship between x and y.

C.x and y are not related.

D.There is a very strong positive linear relationship between x and y. Your answer is correct.

Interpret

r2=97.09% of the total sample variability around y overbary is explained by the linear relationship between x and y.

​(Round to two decimal places as​ needed.)

Calculate r.

r=−0.9934 ​(Round to four decimal places as​ needed.)

Calculate r2.

r2=. 9868. ​(Round to four decimal places as​ needed.)

Interpret r. Choose the correct answer below.

A.There is a very strong negative linear relationship between x and y. Your answer is correct.

B.There is not enough information to answer this question.

C. There is a very strong positive linear relationship between x and y.

D.x and y are not related.

Interpret r2.

98.68​% of the total sample variability around y overbary is explained by the linear relationship between x and y.

​(Round to two decimal places as​ needed.)

Calculate r.

r=___________​(Round to four decimal places as​ needed.)

i) Once you have calculated a standard deviation, discuss its meaning.?

ii) Discuss the pros and cons of the using the variance and the standard deviation in their usefulness in data interpretation.

An engineer designed a valve that will regulate water pressure on an automobile engine. The engineer designed the valve such that it would produce a mean pressure of 5.1 pounds/square inch. It is believed that the valve performs above the specifications. The valve was tested on 22 engines and the mean pressure was 5.4 pounds/square inch with a variance of 0.49 . A level of significance of 0.025 will be used. Assume the population distribution is approximately normal. Determine the decision rule for rejecting the null hypothesis. Round your answer to three decimal places.

4. How many different ways can you put 8 balls in 8 boxes A1, . . . , A8

if (a) the balls are all different and no box is empty 8!

(b) the balls are all different and only three boxes A1, A2 and A3 are empty

(c) the balls are all different and exactly four boxes are empty

(d) the balls are all different and each box is either empty or contains exactly two balls

(e) the balls are identical

(f) the balls are identical and exactly two boxes are empty

please explain in detail too thanks! especially e and f

Solve the following question.

1. The following is the 8 week sales data for a Kashmiri tea house comprising the number of customers (in hundreds) and weekly sales (in thousand SRs).

1. Find the simple linear regression equation of weekly sales over number of customers.
2. What will be sales of ninth week given that the average number of customers is 30?

Question 4: The HR department of a large company needs to assign a newly hired director to either their marketing development or their marketing operations division. To help in their decision, they organize two discussion groups with randomly selected employees from each division. During the talks, the director lays out his marketing vision and employees ask questions relevant to their daily work. At the end, each employee has to rate the director on a scale from 1 to 10 (1=very bad; 10=very good). The HR department wants to know if the distribution of ratings of the marketing development employees is different among the employees of the two divisions. Ratings data for the two groups of employees are included in the Minitab file HR_Ratings.mtw and in the Excel file Assign2.xlsx under the HR_Ratings tab.

a) Examine the distributions of the ratings (show histograms) by the two groups of employees and explain why a non-parametric test is justified to perform the analysis.

b) Perform an appropriate non-parametric test using a 5% significance level to determine if the distribution of ratings of the marketing development employees is different than that of the marketing operations employees. Specify any assumptions and/or conditions you need to make to apply the test and state your hypothesis clearly. Show your manual calculations.

c) Use Minitab to perform the test in b) above and compare your results here is the data for HR_Ratings.mtw

Datafrom HR_Ratings.wtw below

# Reading the data into R:

my.datafile <- tempfile()
cat(file=my.datafile, "
 71 15 
 74 19 
 70 11 
 71 15 
 69 12 
 73 17 
 72 15 
 75 19 
 72 16 
 74 18 
 71 13 
 72 15 
 73 17 
 72 16 
 71 15 
 75 20 
 71 15 
 75 19 
 78 22 
 79 23 
 72 16 
 75 20 
 76 21 
 74 19 
 70 13 
", sep=" ")

options(scipen=999) # suppressing scientific notation

simpbasketball <- read.table(my.datafile, header=FALSE, col.names=c("height", "goals")) 

COMPUTER CALCULATIONS:

I need to know how to code in R for the solutions, not by hand.

2. Look at the data in Table 7.18 on page 368 of the textbook. These data are also

given in the SAS code labeled “SAS_basketball_goal_data” and R code labeled basketball goal data .

The dependent variable is goals and the independent variable is height of basketball players.

Complete a SAS /R program and answer the following questions about the data set:

(a) Does a scatter plot indicate a linear relationship between the two variables?

Is there anything disconcerting about the scatter plot? Explain.

(b) Fit the least-squares regression line (using SAS / R) and interpret the estimated slope

in the context of this data set. Does it make sense to interpret the estimated intercept? Explain.

(c) For these data, what is the unbiased estimate of the error variance? (Give a number.)

(d) Using the SAS / R output, test the hypothesis that the true slope of the regression line

is zero (as opposed to nonzero). State the appropriate null and alternative hypotheses,

give the value of the test statistic and give the appropriate P-value. (Use significance

level of 0.05.) Explain what this means in terms of the relationship between the two

variables.

(e) Using SAS / R, find a 95% confidence interval for the mean basketball goal for

a player with a height of 77 inches. In addition find a 95% prediction interval for

basketball goal for a player with a height of 77 inches.

This has been previously answered but I don't understand, no one did the Ho and Ha, could someone please explain step by step with formulas?

A realtor wishes to compare the square footage of houses of similar prices in 4 different cities. He took a sample of 5 houses from City 1, 4 houses from City 2, 6 houses from City 3, and 7 houses from City 4. Sum of Squares Total is 71.06 and Mean Squares Between is 8.75. Can the realtor conclude that the mean square footage is the same in all four cities? Assume that the level of significance is 0.01. [6 marks]

(Hint: Set up an ANOVA table with the given information and then complete the ANOVA table for the missing information. Also, include the key steps of a test of hypothesis question). [4 marks]