When only two treatments are involved, ANOVA and the Student’s t test (Chapter 11) result in the same conclusions. Also, for computed test statistics, t^₂ = F. To demonstrate this relationship, use the following example. Fourteen randomly selected students enrolled in a history course were divided into two groups, one consisting of 6 students who took the course in the normal lecture format. The other group of 8 students took the course as a distance course format. At the end of the course, each group was examined with a 50-item test. The following is a list of the number correct for each of the two groups.

1= Complete the ANOVA table. (Round your SS, MS, and F values to 2 decimal places and p value to 4 decimal places.)?

2=a-2. Use a α = 0.01 level of significance. (Round your answer to 2 decimal places.)

2. Using the t test from Chapter 11, compute t. (Negative amount should be indicated by a minus sign. Round your answer to 3 decimal places.)

3. There is any difference in the mean test scores.

In baseball a teams success is often thought to be a function of the team's hitting and pitching performance. One measure of hitting performance is the number of home runs that team hits, and one measure of pitching performance is the earned run average for the teams pitching staff. It is generally believed that teams that hit more home runs and have a lower earned run average will win a higher percentage of games played. The following data show the proportion of games won, the number of home runs (HR), and the earned run average (ERA) for the 16 teams in the National League for the 2003 Major League Baseball season.

1. Could someone please help me calculate the critical value of the model?

2. Also, I need to find the conclusion. I limited it down to these two. Could you please explain the reason for a or b?

a. Do not reject null hypothesis. there is not significant relationship between HR and wins

b. Do not reject null hypothesis. There is a significant relationship between ERA and wins

Thanks so much for your help. Will give you 5 stars

1. Nike Inc. has contracts with over 800 manufacturing factories around the world that manufacture Nike’s products; whereas Intel Inc. runs over 200 company-owned facilities around the world. Explain the reasons for the difference in the strategy for global operation by the two companies.

Ted Olson, director of the company Overnight Delivery, is worried because of the number of letters of first class that his company has lost. These letters are transported in airplanes and trucks, due to that, mister Olson has classified the lost letters during the last two years according to the transport in which the letters were lost. The data is as follows:

Mister Olson will investigate only one department, either aerial o ground department, but not both. He will open the investigation in the department which has the most number of lost letters per month, find:

26.- The expectation quadratic value of lost letters per month for truck.

27.- The expectation quadratic value of lost letters per month for airplane.

28.- The variance value of lost letters per month for truck.

29.- The variance value of lost letters per month for airplane.

1-3 Questions are the ones that need to be answered from the experiemnt listed below.

1.Advantages for each technique. Provide at least two.

2.Disadvantages for each technique. Provide at least two.

3.Discuss the criteria used to determine the appropriateness of random assignment versus matching techniques

PSY-452-Experimental Psychology Matched-Subjects Design Separate the 40 participants listed below into two groups of 20, in which each group has an equal number of men and women (10 M, 10 F each). Use a random numbers table (text, pp. 537-538) to accomplish this. (Start anywhere in the table, and proceed in any direction that you like. Odd numbers put the subjects in group 1; even numbers in group 2. When one group is filled, the rest go into the other group.) Next, separate the participants into two groups by using range matching (decide on your acceptable ranges in advance, for example, within 5 pounds). Match as many pairs of female participants as possible: find a match and randomly assign one to the first group, and the other to the second group. Next, do the same for the male participants. Next, match not only on gender, but also on weight. Finally, match the participants on all three variables. Finally, match the 40 participants on gender, weight, and height, using rank-ordered matching.

Use R programming language to answer and please so show the code as well.

A paper manufacturer studied the effect of three vat pressures on the strength
of one of its products. Three batches of cellulose were selected at random
from the inventory. The company made two production runs for each pressure
setting from each batch. As a result, each batch produced a total of six production
runs. The data follow. Perform the appropriate analysis.

Table is below

Batch Pressure Strength
A 400 198.4
A 400 198.6
A 500 199.6
A 500 200.4
A 600 200.6
A 600 200.9
B 400 197.5
B 400 198.1
B 500 198.7
B 500 198.0
B 600 199.6
B 600 199.0

C 400 197.6
C 400 198.4
C 500 197.0
C 500 197.8
C 600 198.5
C 600 199.8

You work in a factory that runs 24 hr a day, 7 days a week. The boss insists that all 10 of the machines in the factory get a good servicing before he goes on vacation. Each of these machines has a part replaced that has an MTTF(µ) of 10,000hrs. The boss will then take the next 2 months (60 days) off for his “well deserved” vacation. The purchasing department will not purchase any expensive items while the boss is on vacation. Each of the parts they just replaced costs so much, they will not be bought without the boss’s permission. And the boss wont take a call during his vacation.

What is the probability that he will replace 2 or less of these parts in a year due to failure? Use the binomial distribution.

If all 10 parts are replaced before his annual vacation, and any part that fails in a year is replaced when it fails, how many parts does he replace in a year on average? (10 + E(x))

E(x) = 10*(1-P(x))(from part ii)

If each device costs $10,000, how much does he spend on average, in a year, replacing parts?

Redo the calculations for part 3 to part 6 using a better part that has an MTTF of 100,000 and costs $80,000.

Use the above information to explain to your boss that he is a fool for using the cheap stuff.

The Excel file Burglaries contains data on the number of burglaries before and after a Citizen Police program. Apply the Descriptive Statistics tool to these data. Does Chebyshev’s theorem hold for the number of monthly burglaries before and after the citizen-police program?

Data :