A customer service department asks its customers to rate their​ over-the-phone service on a scale of​ 1-20 immediately after their service has been completed. The department then matches each​ customer's rating with the number of minutes the person waited on hold. The accompanying table shows the ratings and number of minutes on hold for 10 randomly selected customers. The regression line for the data is (^ is above the Y) Y=16.85-0.15x. Use this information to complete parts a through d.

A. Calculate the coefficient of determination

R2=0.358

(round to three decimal places)

(this has already been found)

B. using a significance level of 0.05 test the significance of the population coefficient of determination

Determine the null and alternative hypotheses.

(this has already been solved below)

Ho:p2 < 0 (< has a line under it)

Ho:p2 > 0

*the F- Statistic is =

(round to two decimal places)

* the P-Value is=

(round to two decimal places)

Choose the correct answer below

*because the P-Value is greater than / less than/or equal to the significance level, do not reject / reject the null hypothesis / alternative hypothesis. There is not / is enough evidence to conclude that the coefficient of determination

C. construct a 95% confidence interval for the average rating by a customer who waits 8 minutes

UCL=

(round to two decimal places)

LCL=

(round both to two decimal points)

D. construct a 95% prediction interval for the rating given by a customer who waits 8 minutes

UPL=

(round to two decimal places)

LPL=

(round to two decimal places)

1.We are interested in conducting a study in order to determine what percentage of voters of a state would vote for the incumbent governor. What is the minimum size sample needed to estimate the population proportion with a margin of error of +/-0.08 at 95% confidence?

A.301

B.150

C.300

D.151

2.We have created a 95% confidence interval for the population mean with the result [10, 15]. What decision will we make if we test H0: m = 16 versus H1: m ¹ 16 at 10% level of significance?

A.Fail to reject H0 in favor of H1

B.Reject H0 in favor of H1

C.We cannot tell what our decision will be from the information given

D.Accept H0 in favor of H1

3.Suppose we want to test H0: m ³ 28 versus H1: m < 28. Which one of the following possible sample results based on a sample of size 36 is most likely to reject H0 in favor of H1?

A.Sample mean = 26, sample standard deviation = 9

B.Sample mean = 24, sample standard deviation = 4

C.Sample mean = 28, sample standard deviation = 2

D.Sample mean = 25, sample standard deviation = 6

4.If a null hypothesis is rejected at the 5% level of significance, it

A.will never be tested at the 1% level

B.will always be rejected at the 1% level

C.may be rejected or not rejected at the 1% level

D.will always be accepted at the 1% level

1. Let X and Y be independent Poisson random variables with parameters 1 and 2, respectively, compute

1. P(X=1 and Y=2)
2. P(X+Y>=2)

2. Find Poisson approximations to the probabilities of the following events in 500 independent trails with probabilities 0.02 of success on each trial.

1. 1 success
2. 2 or fewer success.

1) Using the Binomial Distribution formula find the probability that a family that has 13    children   has 10 girls.

2)   Given the paired data set below of Super Models ( heights and weights) to determine the line of regression.

                                X |   65    67     62     70      66     69     61       67     65     69

                               Y |110 105   113    107    109   113   104    110   116   115

3)   Calculate the Coefficient of Correlation.

4) Using the data from problem 23 predict the weight of a Model who is 69 inches tall.

The null hypothesis and the alternate hypothesis are:

H₀: The frequencies are equal.
H₁: The frequencies are not equal.

1. State the decision rule, using the 0.05 significance level. (Round your answer to 3 decimal places.)

2. Compute the value of chi-square. (Round your answer to 2 decimal place.)

3. What is your decision regarding H₀?

A computer operations department decided to study the effect of the connection media used (either cable or fiber). The team designed a study in which a total of 30 subscribers were chosen. The subscribers were randomly assigned to one of the 3 messaging systems and measurements were taken on the updated time (in seconds). The data are shown below.

(With excel functions can you help in solving these questions)

a. State the null and alternate hypotheses that would be used to test whether there is a significant difference in the average update times for the three different messaging systems. Express symbolically if possible.

b. What type of study is this and what type of hypothesis test would be used to conduct the hypothesis test?

c. What is the p-value corresponding to this hypothesis test? (use cell reference to show answer and where it is found).

d. Conduct a hypothesis test to test whether there is a significant differencewhether there is a significant difference in the average update times for the three different messaging systems. Give a complete summary.

e. State the null and alternate hypotheses that would be used to test whether there is a significant difference in the mean update times of the messaging systems using the 2 different connection media. Express symbolically if possible.

f. What is the p-value corresponding to this hypothesis test? (use cell reference to show answer and where it is found).

g. Conduct a hypothesis test to test whether there is a significant effect due to messaging system used. Give a complete summary.

h. State the null and alternate hypotheses that would be used to test whether there is an interaction between the connection media and the messaging system. Express symbolically if possible.

i. What is the p-value corresponding to this hypothesis test? (use cell reference to show answer and where it is found).

j. Conduct a hypothesis test to determine whether there is an interaction between interaction between the connection media and the messaging system. State complete conclusions.

Health researchers believe that the neonatal mortality rate is higher at home (MRH) than that in the health centers (MRC). The neonatal mortality rates (both MRH and MRC) for 20 countries are recorded in SSPS file Ass_2Q2.sav.

1. Do the data support researchers’ beliefs? Use α=0.05.
2. Find a 95% confidence interval to investigate the researchers’ belief and explain its meaning.
3. Check the assumptions of the above procedure.

The true average diameter of ball bearings of a certain type is supposed to be 0.5 inch.

What conclusion is appropriate when testing H₀: μ = 0.5 versus H_a: μ ≠ 0.5 inch in each of the following situations?

(a)    

n = 15, t = 1.8, α = 0.05

1. Reject H₀

2.Fail to reject H₀    

(b)    

n = 15, t = −1.8, α = 0.05

1. Reject H₀

2. Fail to reject H₀    

(c)    

n = 27, t = −2.5,α = 0.01

1. Reject H₀

_2. Fail to reject H₀    

(d)    

n = 27, t = −3.7

1. Reject H₀ at any reasonable significance level

2. Fail to reject H₀ at any reasonable significance level    

You want to rent an unfurnished one-bedroom apartment in downtown San Diego next year. The mean monthly rent for a random sample of 100 apartments advertised on Craigslist is $1800. Assume a population standard deviation of $150. Find a confidence interval estimate for the population mean of rent for an unfurnished one-bedroom apartment in downtown San Diego.

5)Find a 95% confidence interval for the true (population) mean of rent for an unfurnished one-bedroom apartment in downtown San Diego.

• (1770.6, 1829.4)

6)Sketch the graph illustrating the 95% confidence interval making sure to label and shade appropriately. Leave the answer box empty and upload the graph after submitting the quiz.

7)The CEO of a flashlight manufacturing company claims that an average flashlight lasts 300 days. A researcher randomly selects 15 flashlights for testing. The sampled flashlights last an average of 290 days, with a standard deviation of 50 days. Use the Student's t-distribution to construct a 96% confidence interval for the average (mean) amount of hours for all flashlights. Use the confidence interval to describe the lifetime of the company’s flashlights.

Using the raw data from each trial perform a T-test comparing results from one variable group to another variable ( 6hr vs overnight ) and determine the p-value for the comparison. Report whether or not there was a statistically significant difference between the results when comparing the two variable.

The dataset HomesForSaleCA contains a random sample of 30 houses for sale in California. Suppose that we are interested in predicting the Size (in thousands of square feet) for such homes.

State   Price   Size    Beds    Baths
CA      500     3.2     5       3.5
CA      995     3.7     4       3.5
CA      609     2.2     4       3
CA      1199    2.8     3       2.5
CA      949     1.4     3       2
CA      415     1.7     3       2.5
CA      895     2.1     3       2
CA      775     1.6     3       3
CA      109     0.6     1       1
CA      5900    4.8     4       4.5
CA      219     1.1     3       2
CA      255     1.2     3       2
CA      86      0.6     1       1
CA      62      1.2     3       2
CA      165     1.9     5       3.5
CA      1695    6.9     5       5.5
CA      499     1.4     3       2
CA      47      1.5     3       2
CA      195     2       3       2.5
CA      775     1       2       2
CA      199     1.4     3       2
CA      480     3       5       3
CA      173     0.9     3       1
CA      189     2.5     2       2
CA      230     1.7     3       2
CA      380     2.1     5       3
CA      110     0.8     2       1
CA      499     1.3     3       2
CA      399     1.4     3       2
CA      2450    5       4       5

1. What is the total variability in the sizes of the 30 homes in this sample? (Hint: Try a regression ANOVA with any of the other variables as a predictor.)

2. What other variable in the HomesForSaleCA dataset explains the greatest amount of the total variability in home sizes? Explain how you decide on the variable.

3. How much of the total variability in home sizes is explained by the "best" variable identified in question 2? Give the answer both as a raw number and as a percentage.

4. Which of the variables in the dataset is the weakest predictor of home sizes? How much of the variability does it explain?

5. Is the weakest predictor identified in question 4 still an effective predictor of home sizes? Include some justification for your answer.

thank you for your help!

what type of questions can be answered by following analysis...?
Chi square
t test
anova
manova
ancova
mancova
path analysis

13. The National Institutes of Health funded a study of a random sample of 856 people age 71 and older in the United States. They found that 9.7% of these people suffer from Alzheimer’s Disease.

a.Is .097 (the decimal version of 9.7%) a parameter or a statistic? What symbol do you use to represent 0.097?

b.

First, calculate the lower end of the confidence interval.

Report your answer to three decimals and round appropriately; e.g., 0.xxx (3 points)

c.

Next, calculate the upper end of the interval.

Report your answer to three decimals and round appropriately; e.g., 0.xxx. (1 point)

d. If you were to calculate a 90% confidence interval, would it be wider or narrower than the 95% confidence interval? (1 point)