The following data were obtained from a repeated-measures study comparing 3 treatment conditions. Use a repeated-measures ANOVA with a=.05 to determine whether there are significant mean differences among the three treatments (do all 4 steps of conducting a hypothesis test!!):

A measure of the strength of the linear relationship that exists between two variables is called: Slope/Intercept/Correlation coefficient/Regression equation. If both variables X and Y increase simultaneously, then the coefficient of correlation will be: Positive/Negative/Zero/One. If the points on the scatter diagram indicate that as one variable increases the other variable tends to decrease the value of r will be: Perfect positive/Perfect negative/Negative/Zero. The range of correlation coefficient is: -1 to +1/0 to 1/-∞ to +∞/0 to ∞. Which of the following values could NOT represent a correlation coefficient? r = 0.99/r = 1.09/r = -0.73/r = -1.0. The correlation coefficient is used to determine: A specific value of the y-variable given a specific value of the x-variable/A specific value of the x-variable given a specific value of the y-variable/The strength of the relationship between the x and y variables/None of these. If two variables, x and y, have a very strong linear relationship, then: There is evidence that x causes a change in y/There is evidence that y causes a change in x/There might not be any causal relationship between x and y/None of these alternatives is correct. If the Pearson correlation coefficient R is equal to 1 (r=1) then: There is a negative relationship between the two variables. /There is no relationship between the two variables. /There is a perfect positive relationship between the two variables. /There is a positive relationship between the two variables. If the correlation between 2 variables is -.77, which of the following is true? There is a fairly strong negative linear relationship/An increase in one variable will cause the other variable to decline by 75%

a random sample of 175 xray machines is taken. and 54 machines in the sample malfunction. compute a 95% confidence interval for the proportion of all xray machines that malfunction. then calculate the upper and lower limit of the 95% confidence intervals

In a recent marketing campaign, Olive Garden Italian Restaurant® offered a “NeverEnding Pasta Bowl.” The customer could order an array of pasta dishes, selecting from 7 types of pasta and 6 types of sauce, including 2 with meat.

a. If the customer selects one pasta type and one sauce type, how many “pasta bowls” can the customer order?

b. How many different “pasta bowls” can the customer order without meat?

Question 11

(CO 4) Seventy-nine percent of products come off the line ready to ship to distributors. Your quality control department selects 12 products randomly from the line each hour. Looking at the binomial distribution, if fewer than how many are within specifications would require that the production line be shut down (unusual) and repaired?

Question 12

(CO 4) Out of each 100 products, 96 are ready for purchase by customers. If you selected 21 products, what would be the expected (mean) number that would be ready for purchase by customers?

A study commissioned by the power company shows that of 9,848 persons residing within 500 yards of high voltage lines, 600 have developed one of the cancers in question. Of 13,112 living more than 500 yards from such lines, 550 contracted one of the cancers. a. Calculate the point estimate of odds ratio b. Calculated 95% confidence interval of the odds ratio. Does the odds ratio significantly different from 1?

A large tank of fish from a hatchery is being delivered to a lake. The hatchery claims that the mean length of fish in the tank is 15 inches, and the standard deviation is 4 inches. A random sample of 28 fish is taken from the tank. Let x be the mean sample length of these fish. What is the probability that x is within 0.5 inch of the claimed population mean? (Round your answer to four decimal places.)

1. One method for obtaining random numbers is by Middle Square method, you are asked to create an algorithm to get a random number with an 6 digit integer number. And give an example.

-Identify why you choose to perform the statistical test (Sign test, Wilcoxon test, Kruskal-Wallis test).

-Identify the null hypothesis, Ho, and the alternative hypothesis, Ha.

-Determine whether the hypothesis test is left-tailed, right-tailed, or two-tailed.

-Find the critical value(s) and identify the rejection region(s).

-Find the appropriate standardized test statistic. If convenient, use technology.

-Decide whether to reject or fail to reject the null hypothesis.

-Interpret the decision in the context of the original claim.

A weight-lifting coach claims that weight-lifters can increase their strength by taking vitamin E. To test the theory, the coach randomly selects 9 athletes and gives them a strength test using a bench press. Thirty days later, after regular training supplemented by vitamin E, they are tested again. The results are listed below. Use the Wilcoxon signed-rank test to test the claim that the vitamin E supplement is effective in increasing athletes' strength. Use α = 0.05.

Please answer all parts, it is not that lengthy. If you can't answer last parts, don't attempt then . Leave for someone else

A manufacturing process produces defective items 15% of the time. A random sample of 80 items is taken from the 3000 produced on a particular day, and each sampled item is tested to see if it is defective or not.
In the context of this problem, identify each of the following:
a. Population:
b. Parameter of interest:
c. Sampling frame:
d. Sample:
e. Sampling method:
f. Is there any potential bias? Explain your answer.

You are an analyst for the Coral Cola Company and are interested in the association between age and rating of a new type of soda (Irish-Cream Cream-Soda). You suspect that younger individuals will prefer the soda over older individuals which could be useful for developing advertisement programs that can appeal to the population that likes Irish-Cream Cream-Soda the most (e.g., younger individuals). You conduct a study in which you allow participants (n = 15) to taste the new soda and rate how much they like it on a scale from 1 – 10 (1 being the “worst thing I ever tasted” to 10 being the “best thing I ever tasted”). In addition, you record their age. Use the 6 steps of hypothesis testing and SPSS to determine whether there is an association between ratings of Irish-Cream Cream-Soda and age. The data is provided below. Conduct the appropriate statistical test either by hand or via SPSS (listed at the bottom), record your answers on the answer sheet, and attach SPSS output.

a) State (0.5 pt) and calculate (0.5 pt) an acceptable measure of variability for Age? (1 pt)

b) What is the appropriate statistical test to answer question? (0.5 pt)

c) Step 1: What is your prediction regarding the results of the statistical test? (0.5 pt)

d) Step 2: Set up hypotheses (2 pts)

H₀ (1 pt):   

H₁ (1 pt):   

e) Step 3: Set criteria for decision (2 pts)

Critical value (1 pt):

Decision Rule (1 pt):   

f) Step 5: Report Results (2 pts) – Must include test statistic (0.5 pt), degrees of freedom (0.5 pt), p-value (0.5 pt), and appropriate measure of effect size (0.5 pt)

g) Step 6: Interpret the results of the statistical test in terms of the research question (1 pt)

SPSS DATA
(First Section = Age)
(Second Section = Rating)
48   1
48   4
26   8
24   3
24   7
23   10
23   9
33   6
33   5
30   5
29   5
26   10
41   3
40   2
35   3

We performed a linear regression analysis between number of times on phone per drive and number of near accidents. The equation is Y= 0.320 + 0.943X, where Y is the number of times on phone per drive and X is the number of near accidents. calculate the p-value and give a conclusion.

Find the expected count and the contribution to the chi-square statistic for the left-parenthesis C comma F right-parenthesis cell in the two-way table below. Upper D Upper E Upper F Upper G Total Upper A 39 30 36 36 141 Upper B 77 88 70 55 290 Upper C 21 37 27 28 113 Total 137 155 133 119 544 Round your answer for the excepted count to one decimal place, and your answer for the contribution to the chi-square statistic to three decimal places. EXPECTED COUNT: CONTRIBUTION TO THE CHI-SQUARE STATISTICS:

Complaints concerning excessive commercials seem to grow as the amount of “clutter,” including commercials and advertisements for other television shows, steadily increases on network and cable television. A recent analysis by Nielsen Monitor-Plus compares the average nonprogram minutes in an hour of prime time for both network and cable television. Data for selected years are shown as follows. Year 1996 1999 2001 2004 Network 9.88 14.00 14.65 15.80 Cable 12.77 13.88 14.50 14.92 a. Calculate the correlation coefficient for the average nonprogram minutes in an hour of prime time between network and cable television. b. Conduct a hypothesis test to determine if a positive correlation exists between the average nonprogram minutes in an hour of prime time between network and cable television. Use a significance level of 0.05 and assume that these figures form a random sample.