Determine the margin of error for a 99​% confidence interval to estimate the population mean when s​ =39 for the sample sizes below.

____________________________________________________________________________________

Construct a 90​% confidence interval to estimate the population mean when x overbarx =122 and s​ =26

for the sample sizes below.

​a) n=40       

​b)n=50       

​c)n=100

Problem 3: A linear regression by using famous data set found in Freedman et al. (1991) in Table 1: ‘Statistics’ refers to the percapita consumption of cigarettes in various countries in 1930 and the death rates (number of deaths per million people) from lung cancer for 1950.

1. Order the data by cigarette using into 5 groups by (2, 2, 2, 2, 3), calculate the standard deviation, and make the graph of standard deviation against cigarettes.
2. Check the graph in 1, what kind of transformation should be used to stabilize the variance?

Can someone please explain these steps from this data description

All of Bubba Gump’s data has recently been integrated in a data warehouse. That enterprise data warehouse was built specifically to support data mining initiatives like the one you have been assigned to conduct, by consolidating data from multiple operations and channels in one place and integrating the data across sources for a complete view of the customer experience. For the first time, Bubba Gump analysts can link sales transactions to specific customers at specific restaurants, for example. It also means that you can link customer transactions across channels; that is, for any given customer, you can link to both their restaurant purchases, their online purchases, and (in some cases) their purchases from third-party retail partners.

You have been selected to develop and execute the data mining analysis plan for Bubba Gump’s customer analysis project. Your project will be the first major data mining project conducted against the new Bubba Gump data warehouse. Because Bubba Gump’s data was not previously integrated in a single data warehouse, company leadership has never been able to analyze its customers across their complete experience. In other words, customer restaurant purchases, online purchases, and third-party retailer purchases could not be analyzed together previously; each channel had to be analyzed separately.

As a first step, a sample of 500 customers has been selected from the analytics data warehouse and given a survey in exchange for purchase credits at one of Bubba Gump’s sales channels. The survey sample was selected from the universe of customers who have made purchases from at least one Bubba Gump outlet (restaurant, web store, etc.). Responses to various customer satisfaction questions were recorded, and historical purchase information has been extracted from the data warehouse for each customer in the sample.

To answer these questions I am having trouble to know what these questions wants if it is ok can someone please explain this to me thank you.

Your task is to analyze the survey responses to understand whether there are natural “clusters” within Bubba Gump’s customer population. You are then to
create a visualization of this survey data that describes Bubba Gump’s customers across any dimensions that define those subgroups.
Your Assignment
In your response, address the following critical elements:
Analysis Tools
What data mining tools will you use to perform the analysis?

Why these particular ones?

Data Visualizations
What data visualizations will you use in your report, and why?

Research Question
What is the specific research question that needs to be addressed?

What research question will you work from in order to analyze the given data for meaningful
patterns?
Research Measurement
How will you determine if your research question was answered or if your hypothesis-generation was successful?

How will you measure progress?

Follow-Up Questions
What are cogent follow-up questions or explorations that should follow from your initial research?
Research and Support
Are there any published sources or other resources that address your line of inquiry? Where do they fall short? How will they help guide your analysis?

Test the Hypothesis If the Mean travel time in minutes between Point A to Point B is equal to the mean of the travel time in minutes from Point B to your A. First you must find the mean and standard deviations. Then perform and list the complete required steps for the TWO required Hypothesis tests and ALSO USE THE P-VALUE AS A REJECTION RULE FOR BOTH TESTS. One Hypothesis test is an F test for the equality of the variances of travel Times and the second test is a T test for the equality of the means of travel times in minutes. The F test must be performed first in order to select either Case1 or Case 2 for the T-test. PLEASE SHOW HOW YOU OBTAINED ALL ANSWERS

Recorded Time values in minutes from point A to point B: 32, 34, 51, 30, 29, 35, 36, 29, 32, 29, 33, 32, 29, 30, 33, 30, 30, 33, 30, 31, 35, 35, 34, 32, 33, 33, 31, 33, 34, 30, 30, 29, 34, 32, 36, 29, 30, 32, 30, 33, 31

n1=41

Recorded Time values in minutes from point B to point A: 36, 28, 48, 28, 27, 54, 34, 29, 26, 34, 33, 42, 29, 34, 31, 48, 27, 42, 28, 45, 26, 43, 32, 41, 30, 36, 27, 44, 29, 29, 35, 26, 31, 28, 27, 28, 32, 41, 34, 28, 31

n2=41

When you do a Kruskal Wallis test, why do you always use a right tail test?

A budget is an expression of management's expectations and goals concerning future revenues and costs. To increase their effectiveness, many budgets are flexible, including allowances for the effect of variation in uncontrolled variables. For example, the costs and revenues of many production plants are greatly affected by the number of units produced by the plant during the budget period, and this may be beyond a plant manager's control. Standard cost-accounting procedures can be used to adjust the direct-cost parts of the budget for the level of production, but it is often more difficult to handle overhead. In many cases, statistical methods are used to estimate the relationship between overhead (y) and the level of production (x) using historical data. As a simple example, consider the historical data for a certain plant. Enter the data into EXCEL and analyze it to answer the following items.

(a) Test the hypotheses H₀: β₁ = 0 versus  H_a: β₁ ≠ 0 at the 5% level of significance.

State the decision rule. (Which Option below should we use)

1. Reject H₀ if p value > 0.025.
2. Do not reject H₀ if p value ≤ 0.025.Reject H₀ if p value > 0.05.
3. Do not reject H₀ if p value ≤ 0.05.    Reject H₀ if p value < 0.025.
4. Do not reject H₀ if p value ≥ 0.025.Reject H₀ if p value < 0.05.
5. Do not reject H₀ if p value ≥ 0.05.

State the appropriate test statistic name, degrees of freedom, test statistic value, and the associated p-value (Enter your degrees of freedom as a whole number, the test statistic value to three decimal places, and the p-value to four decimal places).

(Choose: (x, ,z p, t, G)) ( _______  ) = ___________  , p (Choose: (≥, >, <, ≤, = )) ___________

State your decision. Are production and overhead costs linearly related?

1.) Reject the null hypothesis: Yes, production and overhead costs appear to be linearly related

2.) Reject the null hypothesis: No, production and overhead costs do not appear to be linearly related.

3.) Do not reject the null hypothesis: Yes, production and overhead costs appear to be linearly related.

4.) Do not reject the null hypothesis: No, production and overhead costs do not appear to be linearly related.

(b) Test the hypotheses  H₀: β₁ = 1 versus  H_a: β₁ ≠ 1 at the 5% level of significance.

State the appropriate test statistic name, degrees of freedom, test statistic value, and the associated p-value (Enter your degrees of freedom as a whole number, the test statistic value to three decimal places, and the p-value to four decimal places).

(Choose: (x, t, p, G, z)) (________  ) = __________ , p (Choose:(= ≥ > ≤ < )) _____________

State your decision. Choose one of the following:

1.) Do not reject the null hypothesis: The slope of the line representing the relationship between overhead costs and production is not significantly different from 1.

2.) Do not reject the null hypothesis: The slope of the line representing the relationship between overhead costs and production is significantly different from 1.

3.) Reject the null hypothesis: The slope of the line representing the relationship between overhead costs and production is not significantly different from 1.

4.) Reject the null hypothesis: The slope of the line representing the relationship between overhead costs and production is significantly different from 1.

James is a baseball player who hits left handed. Based on his past statistics, his strikeout rate against left-handed pitchers is 12.5%. He would like to reduce this rate, so he changes his batting stance. To test whether it works, he uses a pitching machine to simulate 200 at bats. In these, he struck out 16 times.

James conducts a one-proportion hypothesis test at the 5% significance level, to test whether the true proportion of strikeouts against left-handed pitchers using James's new stance is less than 12.5%.

(a) H0:p=0.125; Ha:p<0.125, which is a left-tailed test.

(b) Use Excel to test whether the true proportion of strikeouts against left-handed pitchers using James's new stance is less than 12.5%. Identify the test statistic, z, and p-value from the Excel output, rounding to three decimal places.

Problem 3: A linear regression by using famous data set found in Freedman et al. (1991) in Table 1: ‘Statistics’ refers to the percapita consumption of cigarettes in various countries in 1930 and the death rates (number of deaths per million people) from lung cancer for 1950.

1. Perform the simple linear regression with and without USA and make the overlay graph.
2. The question is: should we use USA data, should the regression line pass through the original? Give your answer.

The Aluminum Association reports that the average American uses 56.8 pounds of aluminum in a year. A random sample of 51 households is monitored for one year to determine aluminum usage. If the population standard deviation of annual usage is 12.1 pounds, what is the probability that the sample mean will be each of the following?

a. More than 61 pounds

b. More than 56 pounds

c. Between 55 and 57 pounds

d. Less than 54 pounds e. Less than 48 pounds

(Round the values of z to 2 decimal places. Round your answers to 4 decimal places.)

What is the error of the predicted Systolic BP when Age = 39?

Assume that females have pulse rates that are normally distributed with a mean of mu equals 73.0 beats per minute and a standard deviation of sigma equals 12.5 beats per minute. Complete parts​ (a) through​ (c) below. a. If 1 adult female is randomly​ selected, find the probability that her pulse rate is between 67 beats per minute and 79 beats per minute. The probability is nothing . ​(Round to four decimal places as​ needed.) b. If 4 adult females are randomly​ selected, find the probability that they have pulse rates with a mean between 67 beats per minute and 79 beats per minute. The probability is nothing . ​(Round to four decimal places as​ needed.) c. Why can the normal distribution be used in part​ (b), even though the sample size does not exceed​ 30? A. Since the distribution is of​ individuals, not sample​ means, the distribution is a normal distribution for any sample size. B. Since the distribution is of sample​ means, not​ individuals, the distribution is a normal distribution for any sample size. C. Since the original population has a normal​ distribution, the distribution of sample means is a normal distribution for any sample size. D. Since the mean pulse rate exceeds​ 30, the distribution of sample means is a normal distribution for any sample size.

TUTOR, PLEASE DOUBLE CHECK YOUR ANSWERS, MAKE SURE THEY ARE CORRECT.

According to the Current Results website, the state of California has a mean annual rainfall of 25 inches, whereas the state of New York has a mean annual rainfall of 52 inches. Assume that the standard deviation for both states is 3 inches. A sample of 30 years of rainfall for California and a sample of 45 years of rainfall for New York has been taken. Use z-table.

a. Show the probability distribution of the sample mean annual rainfall for California. This is a graph of a normal distribution with E(x)=_____ and Ox=______ (round to 4 decimal places)

b. What is the probability that the sample mean is within 1 inch of the population mean for California? (round to 4 decimal places)

c. What is the probability that the sample mean is within 1 inch of the population mean for New York? (round to 4 decimal places)

d. In which case, part (b) or part (c), is the probability of obtaining a sample mean within 1 inch of the population mean greater? Why?

A survey of 2645 consumers by DDB Needham Worldwide of Chicago for public relations agency Porter/Novelli showed that how a company handles a crisis when at fault is one of the top influences in consumer buying decisions,with 73% claiming it is an influence. Quality of product was the number one influence, with 96% of consumers stating that quality influences their buying decisions. How a company handles complaints was number two, with 85% of consumers reporting it as an influence in their buying decisions. Suppose a random sample of 1,100 consumers is taken and each is asked which of these three factors influence their buying decisions.

a. What is the probability that more than 810 consumers claim that how a company handles a crisis when at fault is an influence in their buying decisions?

b. What is the probability that fewer than 1,030 consumers claim that quality of product is an influence in their buying decisions?

c. What is the probability that between 81% and 84% of consumers claim that how a company handles complaints is an influence in their buying decisions?

*(Round the values of z to 2 decimal places. Round the intermediate values to 4 decimal places. Round your answer to 4 decimal places.)
**(Round the values of z to 2 decimal places. Round the intermediate values to 4 decimal places. Round your answer to 5 decimal places.)

You have the following information from 2000 pairs of randomly picked numbers from 0-9:

Slope: 0.00667162

Intercept: 4.47354107

Correlation: 0.00668018

P-value of slope: 0.76527333

How do you explain the results you got for the 2000 pairs? (Discuss the slope, intercept, correlation, p-value.)​