One of the authors came across an article (USA Today, 2008) that said that on average Americans have visited 16 states in the United States. In a survey of 50 students in her introductory statistics class, she found the average number of states the students had visited to be 9.48 and the standard deviation to be 7.13. The data were not strongly skewed.​

1. Identify the observational unit for this study.

a. students

b. Americans

c. number of states

2. Identify the variable of interest and whether it is categorical or quantitative.

a. number of U.S. states visited, categorial

b. number of students, quantitative

c. number of students, categorial

d. number of U.S. states visited, quantitative

3. Regardless of your answer to part (c), state the null and the alternative hypotheses in symbols, to test whether the average number of states all students at the author’s school have visited is different from 16.

a. H0: mu = 16, Ha: mu ≠ 16

b. H0: mu = 16, Ha: mu > 16

c. H0: mu = 16, Ha: mu < 16

4. Using the 2SD approach to find a 95% confidence interval for the average number of states all students at the author’s school have visited. Round to two decimal places

In the interest of detecting the few children remaining who believe in Santa Claus, you give the latest test for “Belief in Santa Claus” from Canadian Living magazine to your little brother. According to the test, if the child answers more than 10 or more of the questions with the correct “Santa answer”, then the child is declared to believe in Santa Claus. From that perspective, describe with reference to the test

(a) what would be a Type I error for the test? (1 point)
(b) what would constitute a Type II error for the test? (1 point)

(c) what would correspond to the power of the test? (1 point)

(d) what corresponds to the criterion of the test? (2 points)

From the following observations of annual EPS for a company, what is the first-order autocorrelation?

Note that using the CORREL() spreadsheet function will not produce the correct result. Though for a large sample it'll be really close, for a small sample such as this one the difference can be significant. This is because for the autocorrelation you use the variance of the full sample in the denominator, as well as use the full sample to find the mean for use in covariance. In contrast, the CORREL function will treat the two subsets of the time series as separate data, and calculate separate mean and standard deviation for each.

Answer should be 0.4 Please show who to get it in excel

In order to gain information on the required stocking levels of hospital resources, a study was conducted into the usage of latex gloves by hospital employees. Previous orders worked on the belief that the average number of gloves used per employee per week for all employees in the hospital was greater than 23. The resource manager tests this by sampling n = 35 hospital employees and found that number of gloves used by the sampled workers were summarized by an average of 20.74 and a standard deviation of s = 11. The hypotheses being tested are: H 0: μ = 23 H a: μ > 23.

An estimate of the population mean is .

The standard error is .

The distribution is (examples: normal / t12 / chisquare4 / F5,6).

The test statistic has value TS= .

Testing at significance level α = 0.01, the rejection region is:___________ (less/greater) than__________ (2 dec places).

Since the test statistic (is in/is not in) the rejection region, there (is evidence/is no evidence) to reject the null hypothesis, H 0.

There (is sufficient/is insufficient) evidence to suggest that the average number of gloves used by all employess per week, μ, is greater than 23 .

Were any assumptions required in order for this inference to be valid?

a: No - the Central Limit Theorem applies, which states the sampling distribution is normal for any population distribution.

b: Yes - the population distribution must be normally distributed.

Insert your choice (a or b): .

• In the table below are selected values for the OC curve for the acceptance sampling plan n = 210, c = 6. Upon failed inspection, defective items are replaced. Calculate the AOQ for each data point. (You may assume that the population is much larger than the sample.) Plot the AOQ curve. At approximately what population defective rate is the AOQ at its worst? Explain how this happens. How well does this plan meet the specifications of AQL = 0.015, α = 0.05; LTPD = 0.05, β = 0.10? Discuss.

information systems.
in modern organisations, most business information systems (Bis) make extensive use of information technology such as personal computers. discuss the advantages and disadvantages of this computer-based information system.

1. A box contains four red, five blue, and eleven green lenses. One lens is randomly selected from the box. is the probability that the selected lens is blue.

2. A box contains nine red, five yellow, and six green lenses. One lens is randomly selected from the box. Find the probability that the selected lens is yellow or green.

3. An unprepared student makes random guesses for the three true-false questions on a quiz. Find the probability that there is at least one correct answer.

No handwriting please type your answer.

The dataset Golfers2008.xlsx saved in Datasets in Blackboard contains data on the top 40 golfers in 2008. This was the year when Tiger Woods won the U.S. Open in June and then had year-ending surgery.

Using all the explanatory variables, run a regression predicting Earnings per Round.

Determine the best fit model by removing any insignificant x-variables.   Rerun the analysis with your best fit model. Make a clear notation of which model is your best-fit model by labeling the worksheet of that model “BEST FIT MODEL”.

Engineers concerned about a tower's stability have done extensive studies of its increasing tilt. Measurements of the lean of the tower over time provide much useful information. The following table gives measurements for the years 1975 to 1987. The variable "lean" represents the difference between where a point on the tower would be if the tower were straight and where it actually is. The data are coded as tenths of a millimeter in excess of 2.9 meters, so that the 1975 lean, which was 2.9643 meters, appears in the table as 643. Only the last two digits of the year were entered into the computer.

(a) Plot the data. Consider whether or not the trend in lean over time appears to be linear. (Do this on paper. Your instructor may ask you to turn in this graph.)

(b) What is the equation of the least-squares line? (Round your answers to three decimal places.)
y =  +  x

What percent of the variation in lean is explained by this line? (Round your answer to one decimal place.)
%

(c) Give a 99% confidence interval for the average rate of change (tenths of a millimeter per year) of the lean. (Round your answers to two decimal places.)
(  ,  )

To examine the work environment on attitude toward work, an industrial hygienist randomly assigns a group of 18 recently hired sales trainees to three "home rooms" - 6 trainees per room. Each room is identical except for wall color. One is light green, another is light blue, and the third is a deep red. During the week-long training program, the trainees stay mainly in their respective home rooms. At the end of the program, an attitude scale is used to measure each trainer's attitude toward work (a low score indicates a poor attitude and a high score a good attitude). On the basis of these data, the industrial hygenist wants to determine whether there is significant evidence that work environment (i.e., color of room) has an effect on attitude toward work, and if so, which room color(s) appear to significantly enhance attitude using the ANOVA test.

Here is the data:

Light Green Light Blue Deep Red
46 59 34
51 54 29
48 47 43
42 55 40
58 49 45
50 44 34

What is your conclusion?

Please help me to answer the question. Please give me step by step instructions on how to use SPSS program - ANOVA test. Thank you.

If subjects are randomly selected from a university using ID numbers, what sampling method is used?

If the psychologist first takes all the women, and randomly selects 51 of them by randomly drawing ID numbers. Then, she takes all the men and randomly selects 51 of them by randomly drawing ID numbers. What sampling technique did she use?

Need; Hypotheses: Test statistic and value: P-value: and Conclusion:

A) Past sales records indicate that sometimes there is a large difference between the selling prices that different sales reps are able to negotiate for robots. As sales manager, you decide to randomly select four sales over the past year for each of your three sales reps and observe the actual selling price of the robots. The following table shows the amounts at which the robots sold in thousands of dollars. Based on these data, can you conclude that there is a difference between the mean selling prices for these three salespeople at a level of significance of 0.05? Assume that the three population distributions are approximately normal with equal population variances.

In the discussion board, give an example of how you have encountered statistics in your daily life or work. Discuss how statistics were used and their impact on you

1. Optimal Profit

The costs to a store for two models of Global Positioning System (GPS) receivers are $80 and $100. The $80 model yields a profit of $25 and the $100 model yields a profit of $30.

Market tests and available resources determined the constraints below.

(a) The merchant estimates that the total monthly demand will not exceed 200 units.

(b) The merchant does not want to invest more than $18,000 in GPS receiver inventory.

What is the optimal inventory level for each model? What is the optimal profit?

2. Optimal Profit

A fruit grower has 150 acres of land for raising crops A and B. The profit is $185 per acre for crop A and $245 per acre for crop B.

Research and available resources determined the constraints below.

(a) It takes 1 day to trim an acre of crop A and 2 days to trim an acre of crop B, and there are 240 days per year available for trimming.

(b) It takes 0.3 day to pick an acre of crop A and 0.1 day to pick an acre of crop B, and there are 30 days per year available for picking.

What is the optimal acreage for each fruit?  What is the optimal profit?

For each of the following Hypotheses (including test statistic and other information), find de p-value (or its bounds) and draw basic conclusions with 99% confidence.

1) Ho : p = po, H1: P <> po n = 314 test statistics = 2.03 P

value =

Conclusion w.r.t. Ho:

2) Ho : σ1^2<= σ2^2 , H1: σ1^2>σ2^2 n1= 8, n2=4 test statistics = 3.02

P value =

Conclusion w.r.t. Ho:

3) Ho : µd = D0, , H1: µd <> D0, n=18 test statistics = -1.47

P value =

Conclusion w.r.t. Ho: