Insomnia has become an epidemic in the United States. Much research has been done in the development of new pharmaceuticals to aide those who suffer from insomnia. Alternatives to the pharmaceuticals are being sought by sufferers. A new relaxation technique has been tested to see if it is effective in treating the disorder. Sixty insomnia sufferers between the ages of 18 to 40 with no underlying health conditions volunteered to participate in a clinical trial. They were randomly assigned to either receive the relaxation treatment or a proven pharmaceutical treatment. Thirty were assigned to each group. The amount of time it took each of them to fall asleep was measured and recorded. The data is shown below. Use the appropriate t-test to determine if the relaxation treatment is more effective than the pharmaceutical treatment at a level of significance of 0.05.

1. Insomnia has become an epidemic in the United States. Much research has been done in the development of new pharmaceuticals to aide those who suffer from insomnia. Alternatives to the pharmaceuticals are being sought by sufferers. A new relaxation technique has been tested to see if it is effective in treating the disorder. Sixty insomnia sufferers between the ages of 18 to 40 with no underlying health conditions volunteered to participate in a clinical trial. They were randomly assigned to either receive the relaxation treatment or a proven pharmaceutical treatment. Thirty were assigned to each group. The amount of time it took each of them to fall asleep was measured and recorded. The data is shown below. Run an independent samples t-test to determine if the relaxation treatment is more effective than the pharmaceutical treatment at a level of significance of 0.05. Report the test statistic using correct APA formatting and interpret the results.

Q3 A package service company offers overnight package delivery to its business cus- tomers. It has recently decided to expand its facilities to better satisfy current and pro- jected demand. Current volume totals two million packages per week at a price of $12 each, and average variable costs are constant at all output levels. Fixed costs are $3 million per week, and profit contribution averages one-third of revenues on each delivery (profit contribution=(p–AV C)Q). After completion of the expansion project, fixed costs will double, but variable costs will decline by 25%.

(1). Calculate the change in the company’s weekly breakeven output level that is due to expansion. (10 points)

(2). Assuming that volume remains at 2 million packages per week, calculate the change in the degree of operating leverage that is due to expansion. (10 points)

(3). Again assuming that volume remains at two million packages per week, what is the effect of expansion on weekly profit? (10 points)

there is the question and the answer but i'm lost how we get 8$ as AVC

  Solution 3

1. (P - AVC) Q = 1/3P(Q)

P - AVC = 1/3P

AVC = 2/3($12)

AVC = $8

So, Average variable costs are $8

Using the data down and interpret 95% confidence intervals for the mean age of an American truck driver.   This data represents a random sample of drivers in America. There are about 3.5 million truck drivers in the USA.

Find:1- Sample Standard Deviation. 2- Sample Mean. 3- Sample size. 4- Standard error of the mean. 5-T-value. 6- Interval half-width. 7-Interval lower limit. 8- Interval upper limit  .

Please use this data.

A restaurant has dishes A, B, C, D, E, F and G

The owners anticipate that dishes will be ordered in the following proportions: 30% (A), 15% (B), 20% (C), 5% (D), 8% (E), 12% (F) and 10% (G). The number of orders placed during the first two days of business was 75 (A), 60 (B), 50 (C), 14 (D), 20 (E), 40 (F), and 41 (G).

   State and conduct the appropriate hypothesis test to determine whether there is sufficient evidence at the .05 significance level to conclude the owners’ anticipation is incorrect. What is the p-value associated with the test statistic? (Place bounds on the p-value if necessary.)

Annual demand is 12500 units, cost per order is $60 and carrying cost per unit as a    percentage is 8%. The company works 50 weeks a year; the lead-time on all orders placed is 5 weeks.
Assuming constant lead-time demand, and a unit cost of $40 what is the economic order quantity? What is the reorder point.
If lead-time demand shows variability that follows a normal distribution with a mean μ =280 and a standard deviation σ =20, what will the revised reorder point if two stock-outs (shortages) are allowed?
What is the company’s reorder point if the probability of a stock-out on any cycle is restricted to 0.05

FQ3. Annual demand is 12500 units, cost per order is $60 and carrying cost per unit as a    percentage is 8%. The company works 50 weeks a year; the lead-time on all orders placed is 5 weeks.

1. Assuming constant lead-time demand, and a unit cost of $40 what is the economic order quantity? What is the reorder point.
2. If lead-time demand shows variability that follows a normal distribution with a mean μ =280 and a standard deviation σ =20, what will the revised reorder point if two stock-outs (shortages) are allowed?
3. What is the company’s reorder point if the probability of a stock-out on any cycle is restricted to 0.05?

Part I

We’ll use the “Debt and Taxes” tab in the Lab 5 Excel Workbook

The Economic Data Runs from 1946 (1^st year post WW2) to 2016

Note: This issue is tremendously more complicated than the two variables presented here. This is only a partial look at the issue and there is ample room for debate as causes of the issues at hand.

1) Examining the Relationships

              Create and copy in the following Charts

                             1) Line Chart with “Year”, “Top Bracket %”, and “Debt (Relative to 1946)”

                             2) Scatterplot with “Year” and “Top Bracket %,” choose “Show Trendline”

                             3) Scatterplot with “Year” and “National Debt (Trillions),” choose “Show Trendline”

              a) What trends do you see over time?

              b) Do “Top Bracket %” and “National Debt(Trillions)” appear associated?

              c) What might be a possible confounding factor?

2) Running Regressions

              a) Use “Data->Data Analysis->Regression” with “Top Bracket” as the y variable and

“Year” as the x- variable.

What is your model? Slope t-value? F-Value? R squared?

              b) Run a second regression with “National Debt(Trillions)” as the y variable and

                             “Year” as the x-variable.

What is your model? Slope t-value? F-Value? R squared?

c) Run a final regression with “National Debt(Trillions)” as the y variable and

                             “Top Bracket %” as the x-variable

What is your model? Slope t-value? F-Value? R squared?

              d) Based on the R squared from part c) how much of the debts change is due to taxes?

Part II

We will use the “Twins Data” tab in the workbook.

1) Single Variable

              a) Create a Scatterplot of “Wins” and “Runs” (You might need to rescale the axis for each)

              b) Run a Regression with “Wins” as y and “Runs” as x

c) What is your model? Slope t-value? F-Value? R squared?

2) Multivariable

              a) Traditional Stats

                             Run a regression with “Wins” as the y variable and both “Batting Average” and “ERA”

as the two x variables

What is your model? Slope t-values? F-Value? R squared?

              b) Moneyball Stats

                             Run a regression with “Wins” as the y variable and “OPS” and “WHIP” as the x variables

What is your model? Slope t-value? F-Value? R squared?

3) Of the 3 options which model do you feel works the best? Explain.

Statistics for Criminology and Criminal Justice

The probability of being acquitted in criminal court in Baltimore, Maryland, is .40. You take a random sample of the past 10 criminal cases where the defendant had a public defender and find that there were seven acquittals and three convictions. What is the probability of observing seven or more acquittals out of 10 cases if the true probability of an acquittal is .40? By using an alpha of .05, test the null hypothesis (that the probability of an acquittal is .40 for defendants with public defenders), against the alternative hypothesis that it is greater than .40.

The following null and alternative hypotheses have been stated: H0: µ1 - µ2 = 0 HA: µ1 - µ2 = ø to test the null hypothesis, random samples have been selected from the two normally distributed populations with equal variances. the following sample data were observed. sample from population 1: 33, 29, 35, 39, 39, 41, 25, 33, 38. sample from population 2: 46, 43, 42, 46, 44, 47, 50, 43, 39. the test null hypothesis using an alpha level equal to 0.05.