A marketing organization wishes to study the effects of four sales methods on weekly sales of a product. The organization employs a randomized block design in which three salesman use each sales method. The results obtained are given in the following table, along with the Excel output of a randomized block ANOVA of these data.

(a) Test the null hypothesis H₀ that no differences exist between the effects of the sales methods (treatments) on mean weekly sales. Set α = .05. Can we conclude that the different sales methods have different effects on mean weekly sales?

F = 16.98, p-value = .0025; (Click to select)RejectDo not reject H₀: there is (Click to select)a differenceno difference in effects of the sales methods (treatments) on mean weekly sales.

(b) Test the null hypothesis H₀ that no differences exist between the effects of the salesmen (blocks) on mean weekly sales. Set α = .05. Can we conclude that the different salesmen have different effects on mean weekly sales?

F = 43.43, p-value = .0003; (Click to select)RejectDo not reject H₀: salesman (Click to select)dodo not have an effect on sales

(c) Use Tukey simultaneous 95 percent confidence intervals to make pairwise comparisons of the sales method effects on mean weekly sales. Which sales method(s) maximize mean weekly sales? (Round your answers to 2 decimal places. Negative amounts should be indicated by a minus sign.)

Provide at least one example of a parametric statistical test and its nonparametric equivalent, and explain how these examples illustrate the comparison of the two types of analysis

[Using SAS]

1. The data (TET) relates to a study by Reiter and others (1981) concerning the effects of injecting triethyl-tin (TET) into rats once at age 5 days. The animals were injected with 0, 3 or 6 mg per kilogram of body weight (three levels). The response was the log of the activity count for 1 hour, recorded as 21 days of age. The rat was left to move about freely in a figure 8 maze. In this question, we will choose LOGACT21 as our response, the factor DOSAGE will be considered. (You will choose significance level at .05).

a. One wants to investigate whether Dosage level will have any impact on LOGACT21. Please write out the appropriate linear model.

b. Test the hypothesis that Dosage level will have impact on LOGACT21. Set up the null and alternative hypotheses; Report the P-value and make your conclusion from SAS result.

2. Still on data TET. In this question, we will choose LOGACT21 as our response, the two factors DOSAGE and SEX will be considered. (You will choose significance level at .05).

a. Set up appropriate model for this data (including the possible interaction terms).

b. (Interaction effect) Test the hypothesis that the gender effect is the same for all three levels of DOSAGE. Set up appropriate model, hypotheses and report your results.

c. Considering the model without the interactions, does SEX have any significant impact on the mean value of LOGACT21? Set up appropriate model, hypotheses and report your results.

d. Considering the model without the interactions, does DOSAGE have any significant impact on the mean value of LOGACT21? Set up appropriate model, hypotheses and report your results.

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Data file contents:

ID   LOGACT21   Dosage   Sex
1   2.636   0   Male
2   2.736   0   Male
3   2.775   0   Male
4   2.672   0   Male
5   2.653   0   Male
6   2.569   0   Male
7   2.737   0   Male
8   2.588   0   Male
9   2.735   0   Male
10   2.444   3   Male
11   2.744   3   Male
12   2.207   3   Male
13   2.851   3   Male
14   2.533   3   Male
15   2.63   3   Male
16   2.688   3   Male
17   2.665   3   Male
18   2.517   3   Male
19   2.769   3   Male
20   2.694   6   Male
21   2.845   6   Male
22   2.865   6   Male
23   3.001   6   Male
24   3.043   6   Male
25   3.066   6   Male
26   2.747   6   Male
27   2.894   6   Male
28   1.851   6   Male
29   2.489   6   Male
30   2.494   0   Female
31   2.723   0   Female
32   2.841   0   Female
33   2.62   0   Female
34   2.682   0   Female
35   2.644   0   Female
36   2.684   0   Female
37   2.607   0   Female
38   2.591   0   Female
39   2.737   0   Female
40   2.22   3   Female
41   2.371   3   Female
42   2.679   3   Female
43   2.591   3   Female
44   2.942   3   Female
45   2.473   3   Female
46   2.814   3   Female
47   2.622   3   Female
48   2.73   3   Female
49   2.955   3   Female
50   2.54   6   Female
51   3.113   6   Female
52   2.468   6   Female
53   2.606   6   Female
54   2.764   6   Female
55   2.859   6   Female
56   2.763   6   Female
57   3   6   Female
58   3.111   6   Female
59   2.858   6   Female

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Can someone walk me through how to do this on SAS? The documentation doesn't have any examples that break things down simply (I've never used SAS before this class) and the professor has snippets of code without context of what part is doing what. This is what I have so far:

data file;
infile 'pathhere'
getnames=yes
delimiter='09'x;
proc print;
run;

I know he wants a multiple linear regression model but I really don't understand what is supposed to go where code wise for SAS.

Question one

The following table gives the distribution of marks of 60 students in applied statistics test

1. Calculate the:
2. Mean, mode, median and define statistics                     
3. Lower quartile , upper quarter, Interquartile range
4. A researcher has extracted two samples from the same target population, sample A and sample B. Sample A has a mean of 25 kg while sample B has a mean twice that of sample A. Sample size of sample A is three times more than that of sample B. Sum of sample sizes is 60. Calculate:

1. Mean of sample B (1mark)
2. Sample size of sample A and sample B
3. Summation of x variables for sample A and sample B
4. Standard deviation of sample A and sample B, consider ungrouped data

A researcher conducts a study of white and black attitudes toward the police in his state.

The percentage of a random sample of white respondents (N = 300) who say they have a favorable attitude toward the police is 61%. The percentage of a random sample of black respondents (N = 250) who say they have a favorable attitude toward the police is 47%.

• Is there a real (statistically significant) difference between the percentage of Whites and African Americans who have a positive attitude toward the police in the larger population, or are these results likely to have occurred by chance?
• Construct a 95% confidence interval for the proportion of Whites in the population who have a favorable attitude toward the police.
• Construct a 95% confidence interval for the proportion of African Americans in the population who have a favorable attitude toward the police.

Please show work. I want to learn how to execute the question. Class does not use any statistical softwares or excel.

In a survey of smokers who tried to quit smoking with the nicotine patch therapy, 39 were smoking one year after treatment and 32 were not smoking one year after treatment. We want to use a 0.05 significance level to test the claim that among smokers who try to quit with nicotine patch therapy the majority are smoking one year after treatment..

What is the p-value if the claim is modified to state that if the proportion is equal to 0.05?

Whenever you are asked to test a hypothesis, be sure to: (a) state the null and alternative hypotheses; (b) state the relevant sample statistic; (c) give the rejection region; (d) compute the test; (e) give your decision and a conclusion in English.

1. Assume that last year, licensed American drivers drove an average of 10,000 miles, with a standard deviation of 2,000 miles (these are population figures). This year, the government campaigned to get people to save gas by driving less. To test the effectiveness of the campaign, a study is conducted. A sample of 100 drivers is drawn at random from the general population and the number o fmiles driven by each person is recorded. On the average, these 100 drivers drove 11,000 miles. Was the campaign effective? Use alpha = .01.

Use Excel/Megastat to find the discrete probability and cumulative probability of the Binomial distribution with probability of success p = 0.3 and n = 70.

Find its mean and variance.

Based upon the chart on Excel, what can you conclude about the binomial convergence?

Use binom.dist function on Excel and sketch the curve.

New York City is the most expensive city in the United States for lodging. The mean hotel room rate is $204 per night (USA Today, April , ). Assume that room rates are normally distributed with a standard deviation of $55.

a. What is the probability that a hotel room costs $225 or more per night (to 4 decimals)?

b. What is the probability that a hotel room costs less than $140 per night (to 4 decimals)?

c. What is the probability that a hotel room costs between $200 and $300 per night (to 4 decimals)?

d. What is the cost of the 20% most expensive hotel rooms in New York City? Round up to the next dollar.

A baseball team's 40-man roster contains 21 pitchers, 4 catchers, 9 infielders, and 6 outfielders. If a player from this roster is selected randomly, what is the probability that he is an infielder or outfielder?

The Mozart Effect pertains to the hypothesis that listening to Mozart might induce a short-term improvement on the performance of certain kinds of mental tasks. A team of researchers were interested in seeing if this would apply to a general intelligence test. They do not know if this will improve or lower scores for this particular task but they collected data from two groups:

a. Treating these two groups as independent, answer the following:
* State the hypotheses for this analysis and if this is a one- or two-tailed test.
* State your alpha value and the critical values.
* Test this hypothesis (showing your calculations).
* State your decision regarding the null hypothesis.

b. Now, conduct those four steps again but treat these two groups as dependent (e.g., each row now belongs to the same person in a repeated-measures design).

c. Do the two tests lead to different conclusions? Comment on why or why not.

Consider a population proportion p = 0.88.

a-1. Calculate the expected value and the standard error of P−P− with n = 30. (Round "expected value" to 2 decimal places and "standard deviation" to 4 decimal places.)

b-1. Calculate the expected value and the standard error of P−P− with n = 60. (Round "expected value" to 2 decimal places and "standard deviation" to 4 decimal places.)  

To illustrate the effects of driving under the influence (DUI) of alcohol, a police officer brought a DUI simulator to a local high school. Student reaction time in an emergency was measured with unimpaired vision and also while wearing a pair of special goggles to simulate the effects of alcohol on vision. For a random sample of nine teenagers, the time (in seconds) required to bring the vehicle to a stop from a speed of 60 miles per hour was recorded.

Note: A normal probability plot and boxplot of the data indicate that the differences are approximately normally distributed with no outliers.

Whether the student had unimpaired vision or wore goggles first was randomly selected. Why is this a good idea in designing the experiment? (b) Use a 95% confidence interval to test if there is a difference in braking time with impaired vision and normal vision where the differences are computed as "impaired minus normal." State the appropriate conclusion.

Subject Normal,Xi Impaired, Yi

1 4.49 5.86

2 4.24 5.67

3 4.58 5.51

4 4.56 5.29

5 4.31 5.90

6 4.80 5.49

7 4.59 5.23

8 5.00 5.61

9 4.79 5.63

A machine in the math lab dispenses coffee. The average cup of coffee is supposed to contain 7 oz. Eight cups of coffee from this machine show the average content to be 7.3 oz. The population standard deviation is 0.5 oz. Do you think the machine has slipped out of adjustment and the average amount of coffee per cup is different from 7 oz? Use a 5% level of significance.

1. stating the null and alternate hypothesis

2. find the p value

3. make your decision to reject or fail to reject the null hypotheses

4. write your conclusion to the problem.

5.  Use the results from above, find a 0.95 confidence interval for the mean number of cups of coffee.

6. Explain in a sentence what the results in #5 mean.

Shown below is a portion of a computer output for a regression analysing relating Y(dependent variable) and X(independent variable)

ANOVA

df SS

Regression    1    115.064

Residual 13    82.936

Coefficient    Standard error

Intercept 15.532    1.457

X -1.106 0.761

Required :- A) Perform a t test using the p value approach and determine whether x and y are related Let alpha=0.5 . B) Using the p value approach, perform an F test and determine whether x and y are related. C) Compute the coefficient of determination and fully interpret its meaning. Be specific.