Perform a test that shows the different applications of the central tendency and dispersion measures. Compare showing both advantages and disadvantages. Why use the standard deviation instead of the average deviation?

Minimum : 3 Pages plz....

An important application of regression in manufacturing is the estimation of cost of production. Based on DATA (see chart below) from Ajax Widgets relating cost (Y) to volume (X), what is the cost per widget?

A: 8.75

B. 7.54

C: None of the answers are correct

D: 8.21

E. 7.38

Present the regression output below noting the coefficients, assessing the adequacy of the model and the p-value of the model and the coefficients individually.

The Getz Products Company is investigating the possibility of producing and marketing backyard storage sheds. Undertaking this project would require the construction of either a large or small manufacturing plant. The market for the product produced – storage sheds - could be either favorable or unfavorable. Getz, of course, has the option of not developing the product at all.

With a favorable market, a large facility would give Getz a net profit of $200,000. If the market is unfavorable, a $180,000 net loss would occur. A small plant would result in a net profit of $100,000 in a favorable market, but a net loss of $20,000 would be encountered if the market was unfavorable.

Getz Products’ POM manager believes that the probability of a favorable market is the same as that of an unfavorable market (.50/.50)

Suppose that Getz could have their marketing department perform a survey at a cost of $10,000. Getz would then use the results of the survey to decide whether to build a large plant or a small plant, or not to build at all

If the company decides not to conduct the survey, the probabilities and payoffs given previously apply.

If the company decides to conduct the survey, it will result in either a favorable or unfavorable forecast.

If the forecast is favorable, the probability of the market actually being favorable is 0.78, the probability of the market being unfavorable is 0.22. If a large plant is then built, the final result would be a net profit of $190,000 with a favorable market and a net loss of $190,000 with an unfavorable market. If a small plant is built, the final result would be a net profit of $90,000 with a favorable market and a net loss of $30,000 with an unfavorable market. If no plant is built the net loss will be $10,000 (the cost of the forecast survey).

If the forecast is unfavorable, the probability of the market actually being favorable is 0.27, the probability of the market being unfavorable is 0.73. The final results would be the same as above: if a large plant is then built, the final result would be a net profit of $190,000 with a favorable market and a net loss of $190,000 with an unfavorable market. If a small plant is built, the final result would be a net profit of $90,000 with a favorable market and a net loss of $30,000 with an unfavorable market. If no plant is built the net loss will be $10,000 (the cost of the forecast survey).

We estimate the probability of a favorable survey to be 0.45 and the probability of an unfavorable survey to be 0.55.

Draw and Solve a Decision Tree to determine the best plan for Getz.

Four fair dices were rolled.

Part(a) How many possible outcomes there will be, if the order of dices are considered and their faces (number of points) are recorded?

Part(b) How many possible outcomes there will be, if the sum of the points of the four dices are recorded?

Part (c) What is the probability of getting a result with the sum exactly equals to 6?

Part(d) What is the probability of getting a result with the sum no less than 6?

The following time series shows the sales of a particular product over the past 12 months.

(b)

Use α = 0.4 to compute the exponential smoothing forecasts for the time series. (Round your answers to two decimal places.)

(c)

Use a smoothing constant of α = 0.6 to compute the exponential smoothing forecasts. (Round your answers to two decimal places.)

A statistical program is recommended.

The Consumer Reports Restaurant Customer Satisfaction Survey is based upon 148,599 visits to full-service restaurant chains.†Assume the following data are representative of the results reported. The variable type indicates whether the restaurant is an Italian restaurant or a seafood/steakhouse. Price indicates the average amount paid per person for dinner and drinks, minus the tip. Score reflects diners' overall satisfaction, with higher values indicating greater overall satisfaction. A score of 80 can be interpreted as very satisfied. (Let x₁ represent average meal price, x₂ represent type of restaurant, and y represent overall customer satisfaction.)

(a)

Develop the estimated regression equation to show how overall customer satisfaction is related to the independent variable average meal price. (Round your numerical values to two decimal places.)

ŷ =

Develop the estimated regression equation to show how overall customer satisfaction is related to the average meal price and the type of restaurant. (Use the dummy variable developed in part (c). Round your numerical values to two decimal places.)

Is type of restaurant a significant factor in overall customer satisfaction? (Use α = 0.05.)

Find the value of the test statistic. (Round your answer to two decimal places.)

Find the p-value. (Round your answer to three decimal places.)

p-value =

(f)

Predict the Consumer Reports customer satisfaction score for a seafood/steakhouse that has an average meal price of $25. (Round your answer to two decimal places.)

How much would the predicted score have changed for an Italian restaurant? (Round your answer to two decimal places.)

The predicted satisfaction score increases by  points for Italian restaurants.

Using a scholarly citation, discuss a study that extends the regression analysis where either dependent, independent, or both are qualitative. Explain

1. A description of the study
2. the conclusion.

Thanks.

Toss 5 coins 25 times and note on each throw the number of heads. Make a probability distribution of the number of heads. Find mean and variance of that distribution and compare it with the mean and variance of theoretical probability distribution using binomial probability distribution.

John surfs the website on a regular basis. Suppose the time he spent surfing the website per day is normally distributed, µ = 8 minutes and σ = 2 minutes. If you select a random sample of 4 sessions, a. What is the probability that the sample mean is less than 8 minutes? b. What is the probability that sample mean is between 8 and 10 minutes? c. If you select a random sample of 16 sessions, what is the probability that a as sample mean is between 8 and 9 minutes? d. Explain the differences in the results of (b) and (c). Show your work!

Sampling Distributions and the Central Limit Theorem:

The National Survey of Student Engagement asks college students questions about the quality of their education. In 2018, NSSE reported the following result about college freshman:

During the current school year, about how often have you used numerical information to examine a real-world problem or issue (unemployment, climate change, public health, etc.)?

Mean: 2.29 SD: .92

These results were based on a survey of over 500,000 students from 725 institutions. Suppose we want to see how Coker College students compare to the national results by taking independent, random samples of 35 students each. Find the mean μ_x ̅ and standard deviation σ_x ̅ of this sampling distribution. (Hint: Use the Central Limit Theorem)

Find the probability that the sample mean of a random sample of 35 Coker College students for number of times using numerical information to examine real world issues is more than 3.

In this class, we've used numerical data to examine crime, genetic traits of fungus, political polling, and many other real-world topics. Would it be appropriate to say our statistics class sample of 19 students is unusual compared to the national average? Why or why not?

Mercury is a persistent and dispersive environmental contaminant found in many ecosystems around the world. When released as an industrial by-product, it often finds its way into aquatic systems where it can have deleterious effects on various avian and aquatic species. The accompanying data on blood mercury concentration (µg/g) for adult females near contaminated rivers in a state was read from a graph in an article.

Determine the value of the 10% trimmed mean. (Round your answer to three decimal places.)

a) A data is collected from Lab A. Sample mean is 12, SD is 2.4 and sample size if 16. Another set of data from Lab B have a mean of 10 (assuming SD_B is also 2.4 and n_B=16). If we choose α = 0.05, do you think mean of Lab B is close enough to be considered the “same” as that of Lab A? Why?

b) Same as problem 4), except SD of Lab B is SD_B=4.4. If we choose α = 0.05, do you think the mean of Lab B is close enough to be considered the “same” as that of Lab A? Why?

You wish to test the following claim (HaHa) at a significance level of α=0.10α=0.10.

      Ho:p1=p2Ho:p1=p2
      Ha:p1<p2Ha:p1<p2

You obtain a sample from the first population with 153 successes and 596 failures. You obtain a sample from the second population with 71 successes and 174 failures. For this test, you should NOT use the continuity correction, and you should use the normal distribution as an approximation for the binomial distribution.

What is the test statistic for this sample? (Report answer accurate to three decimal places.)
test statistic =

What is the p-value for this sample? (Report answer accurate to four decimal places.)
p-value =

The p-value is...

• less than (or equal to) αα
• greater than αα

This test statistic leads to a decision to...

• reject the null
• accept the null
• fail to reject the null

As such, the final conclusion is that...

• There is sufficient evidence to warrant rejection of the claim that the first population proportion is less than the second population proportion.
• There is not sufficient evidence to warrant rejection of the claim that the first population proportion is less than the second population proportion.
• The sample data support the claim that the first population proportion is less than the second population proportion.
• There is not sufficient sample evidence to support the claim that the first population proportion is less than the second population proportion.