The following information on maintenance and repair costs and revenues for the last two years is available from the accounting records at Arnie’s Arcade & Video Palace. Arnie has asked you to help him understand the relation between business volume and maintenance and repair cost.

Required:

Using Excel, estimate a linear regression with maintenance and repair cost as the dependent variable and revenue as the independent variable. (Negative amounts should be indicated by a minus sign. Round "Multiple R, R square and Standard Error" to 7 decimal places, Intercept and Revenues to 4 decimal places.)

REGRESSION STATISTICS
   MULTIPLE R ?
   R SQUARE    ?
   STANDARD ERROR    ?
   OBSERVATIONS    ?
   COEFFICIENTS
   INTERCEPT ?
   REVENUES ?

The accompanying data are the number of wins and the earned run averages​ (mean number of earned runs allowed per nine innings​ pitched) for eight baseball pitchers in a recent season. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given​ x-values, if meaningful. If the​ x-value is not meaningful to predict the value of​ y, explain why not.

​(a) x=5 wins ​(b) x=10 wins ​(c) x=21 wins ​(d) x=15 wins. The equation of the regression line is y with equals ____xplus ______. ​(Round to two decimal places as​ needed.)

A mail-order catalog firm designed a factorial experiment to test the effect of the size of a magazine advertisement and the advertisement design on the number of catalog requests received (data in thousands). Three advertising designs and two different-size advertisements were considered. The data obtained follow.

Use the ANOVA procedure for factorial designs to test for any significant effects due to type of design, size of advertisement, or interaction. Use α = 0.05.

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

Find the p-value for type of design. (Round your answer to three decimal places.)

p-value =

State your conclusion about type of design.

Because the p-value ≤ α = 0.05, type of design is not significant.Because the p-value > α = 0.05, type of design is significant.     Because the p-value > α = 0.05, type of design is not significant.Because the p-value ≤ α = 0.05, type of design is significant.

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

Find the p-value for size of advertisement. (Round your answer to three decimal places.)

p-value =

State your conclusion about size of advertisement.

Because the p-value ≤ α = 0.05, size of advertisement is not significant.

Because the p-value ≤ α = 0.05, size of advertisement is significant.    

Because the p-value > α = 0.05, size of advertisement is not significant.

Because the p-value > α = 0.05, size of advertisement is significant.

Find the value of the test statistic for interaction between type of design and size of advertisement. (Round your answer to two decimal places.)

Find the p-value for interaction between type of design and size of advertisement. (Round your answer to three decimal places.)

p-value =

State your conclusion about interaction between type of design and size of advertisement.

Because the p-value > α = 0.05, interaction between type of design and size of advertisement is significant

.Because the p-value > α = 0.05, interaction between type of design and size of advertisement is not significant.     

Because the p-value ≤ α = 0.05, interaction between type of design and size of advertisement is not significant

.Because the p-value ≤ α = 0.05, interaction between type of design and size of advertisement is significant.

USE MINITAB 18 attach screen shots.... End Result Hospital wants to assess the effectiveness of diabetes education through A1c levels. The hospital created three groups of patients. In the control group no instruction is provided, in the second group instruction is provided by physicians, and in the third group instruction is provided by RNs. Use the appropriate statistical test to determine if there is any difference in patient A1c levels between the three groups. Interpret using α = .05. Include and interpret the confidence interval plot. Based on the results, what should be the recommended type of diabetes education?

#29 Among the following statements on measures of central tendency, which is/ are true?

Statement 1: The mode only focuses on the relative position of the ranked observations.

Statement 2: There are two possible calculations to be applied when solving for the median., and they depend on the parity of the sample size.

a. Both Statements 1 and 2 are true.

b. Both Statements 1 and 2 are false.

c. Neither of the above.

Develop the analysis of variance computations for the following completely randomized design. At α = 0.05, is there a significant difference between the treatment means?

State the null and alternative hypotheses.

H₀: μ_A = μ_B = μ_C
H_a: μ_A ≠ μ_B ≠ μ_CH₀: μ_A ≠ μ_B ≠ μ_C
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: Not all the population means are equal.
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 of the three treatments are not equal.Do not reject H₀. There is not sufficient evidence to conclude that the means of the three treatments are not equal.     Reject H₀. There is not sufficient evidence to conclude that the means of the three treatments are not equal.Reject H₀. There is sufficient evidence to conclude that the means of the three treatments are not equal.

Recall again that Rind & Bordia (1996) investigated whether or not drawing a happy face
on customers’ checks increased the amount of tips received by a waitress at an upscale
restaurant on a university campus. During the lunch hour a waitress drew a happy,
smiling face on the checks of a random half of her customers. The remaining half of the
customers received a check with no drawing (18 points).
The tip percentages for the control group (no happy face) are as follows:
45% 39% 36% 34% 34% 33% 31% 31% 30% 30% 28%
28% 28% 27% 27% 25% 23% 22% 21% 21% 20% 18%
8%
The tip percentages for the experimental group (happy face) are as follows:
72% 65% 47% 44% 41% 40% 34% 33% 33% 30% 29%
28% 27% 27% 25% 24% 24% 23% 22% 21% 21% 17%

This time, you are to perform a “hypothesis test” using the tip data, answering each of
the questions below. For short-answer questions, be brief. However, you must give
enough detail to justify your answers. Single-sentence responses will generally not
suffice, but do not exceed a paragraph for any given answer.

i. Obtain the appropriate test statistic. From the SPSS menus choose Analyze
and Compare Means, followed by the appropriate test.

Fowle Marketing Research, Inc., bases charges to a client on the assumption that telephone surveys can be completed in a mean time of 15 minutes or less. If a longer mean survey time is necessary, a premium rate is charged. Suppose a sample of 35 surveys produces the data in the Microsoft Excel Online file below. Use a known σ = 3.7 minutes. Is the premium rate justified?

1. Formulate the null and alternative hypotheses for this application.

   H₀: μ _________greater than or equal to 15greater than 15less than or equal to 15less than 15equal to 15not equal to 15

   H_a: μ _________greater than or equal to 15greater than 15less than or equal to 15less than 15equal to 15not equal to 15

2. Compute the value of the test statistic (to 2 decimals).

3. What is the p-value (to 4 decimals)?

4. Using ? = .01, is a premium rate justified for this client?

Recall again that Rind & Bordia (1996) investigated whether or not drawing a happy face
on customers’ checks increased the amount of tips received by a waitress at an upscale
restaurant on a university campus. During the lunch hour a waitress drew a happy,
smiling face on the checks of a random half of her customers. The remaining half of the
customers received a check with no drawing (18 points).
The tip percentages for the control group (no happy face) are as follows:
45% 39% 36% 34% 34% 33% 31% 31% 30% 30% 28%
28% 28% 27% 27% 25% 23% 22% 21% 21% 20% 18%
8%
The tip percentages for the experimental group (happy face) are as follows:
72% 65% 47% 44% 41% 40% 34% 33% 33% 30% 29%
28% 27% 27% 25% 24% 24% 23% 22% 21% 21% 17%

This time, you are to perform a “hypothesis test” using the tip data, answering each of
the questions below. For short-answer questions, be brief. However, you must give
enough detail to justify your answers. Single-sentence responses will generally not
suffice, but do not exceed a paragraph for any given answer.

o. Considering both the probability value and effect size measure, what
interpretations would you make about the findings? That is, what are your
conclusions about the effects of leaving happy faces on checks?

Recall again that Rind & Bordia (1996) investigated whether or not drawing a happy face
on customers’ checks increased the amount of tips received by a waitress at an upscale
restaurant on a university campus. During the lunch hour a waitress drew a happy,
smiling face on the checks of a random half of her customers. The remaining half of the
customers received a check with no drawing (18 points).
The tip percentages for the control group (no happy face) are as follows:
45% 39% 36% 34% 34% 33% 31% 31% 30% 30% 28%
28% 28% 27% 27% 25% 23% 22% 21% 21% 20% 18%
8%
The tip percentages for the experimental group (happy face) are as follows:
72% 65% 47% 44% 41% 40% 34% 33% 33% 30% 29%
28% 27% 27% 25% 24% 24% 23% 22% 21% 21% 17%

This time, you are to perform a “hypothesis test” using the tip data, answering each of
the questions below. For short-answer questions, be brief. However, you must give
enough detail to justify your answers. Single-sentence responses will generally not
suffice, but do not exceed a paragraph for any given answer.

n. What is your decision concerning the null hypothesis? Did you reject or
retain?

Recall again that Rind & Bordia (1996) investigated whether or not drawing a happy face
on customers’ checks increased the amount of tips received by a waitress at an upscale
restaurant on a university campus. During the lunch hour a waitress drew a happy,
smiling face on the checks of a random half of her customers. The remaining half of the
customers received a check with no drawing (18 points).
The tip percentages for the control group (no happy face) are as follows:
45% 39% 36% 34% 34% 33% 31% 31% 30% 30% 28%
28% 28% 27% 27% 25% 23% 22% 21% 21% 20% 18%
8%
The tip percentages for the experimental group (happy face) are as follows:
72% 65% 47% 44% 41% 40% 34% 33% 33% 30% 29%
28% 27% 27% 25% 24% 24% 23% 22% 21% 21% 17%

This time, you are to perform a “hypothesis test” using the tip data, answering each of
the questions below. For short-answer questions, be brief. However, you must give
enough detail to justify your answers. Single-sentence responses will generally not
suffice, but do not exceed a paragraph for any given answer.

h. Enter the data above into SPSS. You will enter in two variables for each
restaurant patron: 1) which experimental group they belonged to (1 = no
happy face, 2 = happy face) and 2) the tip percentage left.

1. A high-level voltage power supply should have a nominal output voltage of 350 V. A sample of four units is selected each day and tested for process-control purposes. The data (20 days, 1 sample/day) shown in the table below give the difference between the observed reading on each unit and the nominal voltage times ten; that is, x_i = (observed voltage on unit 350)*10.

1. Calculate the UCL and LCL for the x̄-chart.
2. Calculate the UCL and LCL for the R-chart.
3. Set up x̄ and R charts on this process. Is the process in statistical control?
4. If specifications are at 350 V ± 5 V, what can you say about process capability? Calculate C_p. Interpret the calculated value of C_p.
5. Calculate C_pk. Interpret the calculated value of C_pk.

Consider a multiple-choice examination with 50 questions. Each question has four possible answers. Assume that a student who has done the homework and attended lectures has a 65% chance of answering any question correctly. (Round your answers to two decimal places.)

(a)

A student must answer 44 or more questions correctly to obtain a grade of A. What percentage of the students who have done their homework and attended lectures will obtain a grade of A on this multiple-choice examination? Use the normal approximation of the binomial distribution to answer this question.

%

(b)

A student who answers 34 to 39 questions correctly will receive a grade of C. What percentage of students who have done their homework and attended lectures will obtain a grade of C on this multiple-choice examination? Use the normal approximation of the binomial distribution to answer this question.

%

(c)

A student must answer 30 or more questions correctly to pass the examination. What percentage of the students who have done their homework and attended lectures will pass the examination? Use the normal approximation of the binomial distribution to answer this question.

%

(d)

Assume that a student has not attended class and has not done the homework for the course. Furthermore, assume that the student will simply guess at the answer to each question. What is the probability that this student will answer 30 or more questions correctly and pass the examination? Use the normal approximation of the binomial distribution to answer this question.

Recall again that Rind & Bordia (1996) investigated whether or not drawing a happy face
on customers’ checks increased the amount of tips received by a waitress at an upscale
restaurant on a university campus. During the lunch hour a waitress drew a happy,
smiling face on the checks of a random half of her customers. The remaining half of the
customers received a check with no drawing (18 points).
The tip percentages for the control group (no happy face) are as follows:
45% 39% 36% 34% 34% 33% 31% 31% 30% 30% 28%
28% 28% 27% 27% 25% 23% 22% 21% 21% 20% 18%
8%
The tip percentages for the experimental group (happy face) are as follows:
72% 65% 47% 44% 41% 40% 34% 33% 33% 30% 29%
28% 27% 27% 25% 24% 24% 23% 22% 21% 21% 17%

This time, you are to perform a “hypothesis test” using the tip data, answering each of
the questions below. For short-answer questions, be brief. However, you must give
enough detail to justify your answers. Single-sentence responses will generally not
suffice, but do not exceed a paragraph for any given answer.

f. Recall that one of the assumptions of the independent t-test is homogeneity
of variance. If you had to explain this assumption to someone with little
statistical expertise, how would you explain it?

Recall again that Rind & Bordia (1996) investigated whether or not drawing a happy face
on customers’ checks increased the amount of tips received by a waitress at an upscale
restaurant on a university campus. During the lunch hour a waitress drew a happy,
smiling face on the checks of a random half of her customers. The remaining half of the
customers received a check with no drawing (18 points).
The tip percentages for the control group (no happy face) are as follows:
45% 39% 36% 34% 34% 33% 31% 31% 30% 30% 28%
28% 28% 27% 27% 25% 23% 22% 21% 21% 20% 18%
8%
The tip percentages for the experimental group (happy face) are as follows:
72% 65% 47% 44% 41% 40% 34% 33% 33% 30% 29%
28% 27% 27% 25% 24% 24% 23% 22% 21% 21% 17%

d. Write null and alternate hypotheses that correspond with your answer to
question #c. If you decided to perform a one-tailed test, make sure and
specify which of the two groups you predict will be higher/lower.