The data shown in the table were collected by surveying 100 employees with five years’ experience. Find the correlation relationship for the data. Use Microsoft Excel. Create a scatter plot. Identify and discuss the type of correlation, and whether is negative or positive, strong or weak. Create a regression line and analyze the coefficients for significance. Predict the estimates salary with 20 years of schooling.

It is assumed that there is an average of 12 customers per hour at a service counter according to a Poisson process.

a) How likely is it that 4 customers show up at this counter in the next 15 minutes?

b) Given that 4 customers showed up at this counter in a given 15-minute period, what is the probability that there were at least 2 customers that showed up in the last 5 minutes of this period?

You may need to use the appropriate technology to answer this question.

The following data are from a completely randomized design.

(a)

Compute the sum of squares between treatments.

(b)

Compute the mean square between treatments.

(c)

Compute the sum of squares due to error.

(d)

Compute the mean square due to error. (Round your answer to two decimal places.)

(e)

Set up the ANOVA table for this problem. (Round your values for MSE and F to two decimal places, and your p-value to four decimal places.)

(f)

At the α = 0.05 level of significance, test whether the means for the three treatments are equal.

State the null and alternative hypotheses.

H₀: μ_A = μ_B = μ_C
H_a: μ_A ≠ μ_B ≠ μ_CH₀: Not all the population means are equal.
H_a: μ_A = μ_B = μ_C    H₀: μ_A = μ_B = μ_C
H_a: Not all the population means are equal.H₀: At least two of the population means are equal.
H_a: At least two of the population means are different.H₀: μ_A ≠ μ_B ≠ μ_C
H_a: μ_A = μ_B = μ_C

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

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

p-value =

State your conclusion.

Do not reject H₀. There is sufficient evidence to conclude that the means for the three treatments are not equal.Reject H₀. There is sufficient evidence to conclude that the means for the three treatments are not equal.    Do not reject H₀. There is not sufficient evidence to conclude that the means for the three treatments are not equal.Reject H₀. There is not sufficient evidence to conclude that the means for the three treatments are not equal.

Graeter’s is thinking about expanding its ice cream flavors. They have created three new flavors of ice cream: (1) Lemon Merengue Pie, (2) Butterscotch, and (3) Banana Cream Pie. They recruit 18 people to participate in their study, and they assign each participant to taste-test one of their new ice cream flavors. After tasting the flavor, participants rate their likelihood of ordering that ice cream flavor on their next trip to Graeter’s, using a scale from 1 (I definitely wouldn’t order this flavor) to 10 (I definitely would order this flavor). The data is as follows:

For this problem, complete the following steps. You must show ALL OF YOUR WORK to receive credit for this problem.(21 pts.)

(1) Identify the two hypotheses. (2 pts.)

(2) Determine the critical region for your decision (use α = 0.05). (3 pts.)

(3) Compute the test statistic. (8 pts.)

(4) Use the test statistic to make a decision and interpret that decision. (1 pt.)

(5) If needed, conduct a post hoc test. (5 pts.)

(6) Compute and interpret η2 as a measure of the effect size.(2 pts.)

The Pepsi Corporation wants to explore the relationship between the daily temperature in California and the quantity of soft drinks that it sells at Dadger’s Baseball Stadium. The average daily temperature for 12 randomly selected days and the quantity of soft drinks sold on each of these days are given below:

Average Daily Temperature

            70
            75
            80
            90
            93
            98
            72
            75
            75
            80
            90
            95

Quantity Sold (thousands)

           30
           28
           40
           52
           57
           54
           27
           38
           32
           46
           49
           51

Construct a 90% confidence interval for the quantity of soft drinks sold when the temperature is 750.

A consumer product testing organization uses a survey of readers to obtain customer satisfaction ratings for the nation's largest supermarkets. Each survey respondent is asked to rate a specified supermarket based on a variety of factors such as: quality of products, selection, value, checkout efficiency, service, and store layout. An overall satisfaction score summarizes the rating for each respondent with 100 meaning the respondent is completely satisfied in terms of all factors. Suppose sample data representative of independent samples of two supermarkets' customers are shown below.

(a)

Formulate the null and alternative hypotheses to test whether there is a difference between the population mean customer satisfaction scores for the two retailers. (Let μ₁ = the population mean satisfaction score for Supermarket 1's customers, and let μ₂ = the population mean satisfaction score for Supermarket 2's customers. Enter != for ≠ as needed.)

H₀:

H_a:

(b)

Assume that experience with the satisfaction rating scale indicates that a population standard deviation of 13 is a reasonable assumption for both retailers. Conduct the hypothesis test.

Calculate the test statistic. (Use

μ₁ − μ₂.

Round your answer to two decimal places.)

Report the p-value. (Round your answer to four decimal places.)

p-value =

At a 0.05 level of significance what is your conclusion?

Reject H₀. There is sufficient evidence to conclude that the population mean satisfaction scores differ for the two retailers.Do not reject H₀. There is not sufficient evidence to conclude that the population mean satisfaction scores differ for the two retailers.    Do not reject H₀. There is sufficient evidence to conclude that the population mean satisfaction scores differ for the two retailers.Reject H₀. There is not sufficient evidence to conclude that the population mean satisfaction scores differ for the two retailers.

(c)

Which retailer, if either, appears to have the greater customer satisfaction?

Supermarket 1Supermarket 2    neither

Provide a 95% confidence interval for the difference between the population mean customer satisfaction scores for the two retailers. (Use

x₁ − x₂.

Round your answers to two decimal places.)

to

Suppose x has a distribution with μ = 45 and σ = 13.

(a) If random samples of size n = 16 are selected, can we say anything about the x distribution of sample means?

Yes, the x distribution is normal with mean μ x = 45 and σ x = 13.

Yes, the x distribution is normal with mean μ x = 45 and σ x = 3.25.

Yes, the x distribution is normal with mean μ x = 45 and σ x = 0.8.

No, the sample size is too small.

(b) If the original x distribution is normal, can we say anything about the x distribution of random samples of size 16?

No, the sample size is too small.

Yes, the x distribution is normal with mean μ x = 45 and σ x = 0.8.

Yes, the x distribution is normal with mean μ x = 45 and σ x = 3.25.

Yes, the x distribution is normal with mean μ x = 45 and σ x = 13.

(c) Find P(41 ≤ x ≤ 46). (Round your answer to four decimal places.)

a). A student read that a 95% confidence interval for the mean SAT Mathematics score of Texas high school seniors in 2019 is 467 to 489. Asked to explain the meaning of this interval, the student responded, “In 2019, 95% of Texas high school seniors had SAT Mathematics scores between 467 and 489.” Is the student essentially correct? Justify your answer fully.

b). A consumer group chose to study the true population mean salary (??) of “family practice” doctors in the Greater Houston Metroplex. A random sample of one hundred family practice doctors working in this area produced the 95% confidence interval [$241,150, $249,070] for ??. Answer the following:

i). If possible, find the sample average salary for the one hundred family practice doctors involved in this study. If not possible, then state why this statistic cannot be found.

ii). Find the margin of error associated with this confidence interval.

As the assistant bank manager, you want to provide prompt service for customers at your bank's drive thru window. The bank can currently serve up to 10 customers per 15-minute period without significant delay. The average arrival rate is 7 customers per 15-minute period. Let x denote the number of customers arriving per 15-minute period. Assume this is a Poisson distribution.

a. Find the probability that 10 customers will arrive in a particular 15-minute period.
b. Find the probability that 10 or fewer customers will arrive in a particular 15-minute period.
c. Does your own personal bank have prompt service? Are there ways that your bank can improve their customer service? How?

Students have shown that children in the US who have been spanked have a significantly lower IQ score on average than children who have not been spanked.

A) What is the explanatory variable in these studies? What type of variable is it?

B) What is the response variable in these studies? What type of variable is it?

C) Do you think these studies were observational studies or experiments? Explain.

A telephone service representative believes that the proportion of customers completely satisfied with their local telephone service is different between the West and the Northeast. The representative's belief is based on the results of a survey. The survey included a random sample of 12401240 western residents and 13001300 northeastern residents. 46%46% of the western residents and 35%35% of the northeastern residents reported that they were completely satisfied with their local telephone service. Find the 98%98% confidence interval for the difference in two proportions.

Step 2 of 3:

Find the value of the standard error. Round your answer to three decimal places.

Step 3 of 3:

Construct the 98%98% confidence interval. Round your answers to three decimal places.

osteoporosis is a condition in which people experience decreased bone mass and an increase in the risk of bone fracture. Actonel is a drug that helps combat osteoporosis in postmenopausal women. In clinical trials, 1374 postmenopausal women were randomly divided into experimental and control groups. The subjects in the experimental group were administered 5 milligrams of Actonal, while the subjects in the control group were administered a placebo. The number of women who experienced a bone fracture over the course of one year was recorded. Of the 696 women in the experimental group, 27 experienced a fracture during the course of the year. Of the 678 women in the control group, 49 experienced a fracture during the course of the year.

a. Does the sample evidence suggest the drug is effective in preventing bone fractures? Use the × = 0.01 level of significance.

b. Construct a 95% confidence interval for the difference between the two population proportions, p exp - p control.

A researcher wants to study the relationship between salary and gender. She randomly selects 324324 individuals and determines their salary and gender. Can the researcher conclude that salary and gender are dependent?

Find the value of the test statistic. Round your answer to three decimal places.

part 5 find the degrees of freedom associated with the test statistic for this problem.

part 6 Find the critical value of the test at the 0.010.01 level of significance. Round your answer to three decimal places.

part 7

Make the decision to reject or fail to reject the null hypothesis at the 0.010.01 level of significance.

part 8

Make the decision to reject or fail to reject the null hypothesis at the 0.010.01 level of significance.

In a sample of 5000 people, 2% of the population have COVID. In testing, there is a false positive rate of 1.6% and a false negative rate of 4%.

a. Compile the results in a chart or a tree diagram.

b. In this sample, how many people have COVID?

c. What percent of the population have a positive test for COVID?

d. What is the probability that a patient has COVID given a positive test?

e. What is the probability that a patient has COVID given a negative test?

f. You have a relative convinced they must have COVID because their test was positive. What would you tell them, based on your answer to questions #c & d. Be specific.

g. What percent of all people have “accurate tests”?

please show all work and calculations