An analyst must decide between two different forecasting techniques for weekly sales of roller blades: a linear trend equation and the naive approach. The linear trend equation is F_t = 124 + 2.1t, and it was developed using data from periods 1 through 10. Based on data for periods 11 through 20 as shown in the table, which of these two methods has the greater accuracy if MAD and MSE are used? (Round your intermediate calculations and final answers to 2 decimal places.)

(Click to select)  Linear trend  Naive method  provides forecasts with less average error and less average squared error.

Use the sample information x¯ = 41, σ = 4, n = 20 to calculate the following confidence intervals for μ assuming the sample is from a normal population. (a) 90 percent confidence. (Round your answers to 4 decimal places.) The 90% confidence interval is from to (b) 95 percent confidence. (Round your answers to 4 decimal places.) The 95% confidence interval is from to (c) 99 percent confidence. (Round your answers to 4 decimal places.) The 99% confidence interval is from to (d) Describe how the intervals change as you increase the confidence level. The interval gets narrower as the confidence level increases. The interval gets wider as the confidence level decreases. The interval gets wider as the confidence level increases. The interval stays the same as the confidence level increases.

The data contained in <professional> are the number of males employed full time in a professional occupation in Australia from August quarter 1996 to August quarter 2008.

a) Plot the series of data.

b) Calculate linear trend equation and plot the trend line.

c) What are your forecasts of male full-time professional employment in November quarter 2008 and February quarter 2009?

d) Do you think it is reasonable to try to forecast employment in this way? Explain.

Below is data from the Lazy R Ranch on its production and price of meats and poultry. For the years 2014 1nd 2015.

                      Quantities 2014          Price per lb 2014           Price per lb 2015

Beef                      235,000                       3.49                              3.79

Lamb                     125,000                      3.89                              4.00

Chicken               1,000,500                      2.49                              2.89

a. Compute the price relatives for each type of meat and poultry.

b. Computed a weighted aggregate price index for the Murray Company. Comment on the change in prices.

13. Generational Differences in Workplace Attitudes. In 2015, Addison Group (a pro-vider of professional staffing services) and Kelton (a global insights firm) surveyed the work preferences and attitudes of 1,006 working adults spread over three generations: baby boomers, Generation X, and millennials (Society for Human Resource Manage-ment website, https://www.shrm.org/resourcesandtools/hr-topics/talent-acquisition/pages /millennials-raises-promotions-generations.aspx). In one question, individuals were asked if they would leave their current job to make more money at another job. The file Millenials contains the sample data, which are also summarized in the following table.

Leave Job for More Money?
Baby Boomer

Yes 129
No 207
Generation X

yes 152
no 183
Millennial

yes 164
no 171

Conduct a test of independence to determine whether interest in leaving a current job for more money is independent of employee generation. What is the p-value? Using a .05 level of significance, what is your conclusion

Let X1,X2,X3 be i.i.d. N(0,1) random variables. Suppose Y1 = X1 + X2 + X3, Y2 = X1 −X2, Y3 =X1 −X3. Find the joint pdf of Y = (Y1,Y2,Y3)′ using : Multivariate normal distribution properties.

a conference room holds meetings. the owner knows that the duration of these meetings is uniformly distributed from 30-90 mins.

a) what is the liklihood that a meeting will last between 60 and 80 mintues?

b)what is the standard deviation of the duration of the meetings?

c) a meeting has been scheduled in a room at 3pm. when should the next meeting be scheduled so that there is no more than a 10% chance that the participants for the second meering have to wait for the previosu meeting to get over?

You probably regard your university education as an investment. You spend your valuable time, effort, and tuition fees and in return you obtain a degree. The provincial and federal governements also regard their funding of universities to be an investment. But is the investment equally effective in producing graduates across all provinces? The data bellow indicates the number of graduates at the bachelors, masters and doctorate levels and funding from four sources: Investment of university endowment funds, provincial funding, federal funding, tuition fees. Can we estimate the number of graduates from the level of these sources of funding? Does population size impact the equation? What other factors could influence results?

Terry and Associates is a specialized medical testing center Denver, Colorado. One of the firm's major sources of revenue is a lot used to test for elevated of lead in the blood. Workers in auto body shops, those in the lawn care industry, and commercial house painters are exposed to large amounts of lead and thus must be randomly tested. It is expensive to conduct the test, so the kits are delivered on demand to a variety of locations throughout the Denver area.

     Kathleen Terry, the owner, is concerned about setting appropriate costs for each delivery. To investigate, Ms. Terry gathered information on a random sample 0f 46 recent deliveries. Factors thought to be related to the cost of delivering a kit were:

Prep   The time in minutes between when the customized order is phoned into the company and when it is ready for delivery.

Delivery   The actual travel time in minutes from
Terry"s plant to the customer.

Mileage    The distance in miles from Terry's plant to the customer.

Cost          Prep     Delivery     Mileage

32.60          10          51             20

23.37          11          33             12

31.49           6           47             19

19.31           9           18              8

28.35           8           88             17

28.17           5           35             16

20.42           7           23              9

21.53           9           21             10

27.55         7 37 16

23.37 9 25 12

17.10    15    15 6

27.06    13    34    15

15.99    8    13 4

17.96    12 12    4

25.22    6      41               14

24.29            3         28               13

22.76          4         26               10

28.17            9         54               16

19.68            7         18                 8

25.15            6         50               13

20.36            9         19                7

21.16            3         19                8

25.95           10        45               14

18.76           12        12                 5

18.76            8       16                 5

24.49            7         35                13

19.56            2         12                 8

22.63            8         30                11

21.16            5         13                 8

21.16           11        20                 8

19.68             5        19                 8

18.76             5        14                 7

17.98             5        11                 4

23.37            10       25                12

25.22              6       32                14

27.06              8       44                16

21.06              9       28                  9

22.63              8       31                 11

19.68              7       19                   8

22.76              8       28                  10

21.96             13      18                   9

25.95             10      32                  14

26.14               8      44                  15

24.29               8      34                  13

24.35               3      33                  12

1. Write the regression equation.

2. Interpret the regression constant and partial regression coefficients.

3. Test the overall significant of the regression model

4. Is there any indication of multicollinearity.

The Seneca Children's Fund is a local charity that runs summer camps for disadvantaged children. The fund's board of directors has been working very hard in recent years to decr4ease the amount of overhead expenses, a major factor in how charities are rated by independent agencies. The following data show the percentages of the money the fund has raised that was spent on administrative and fund-raising expenses for 2006-2012.

Year      Expense (%)

2006            13.7

2007            13.9

2008            14.8

2009            14.6

2010            14.9

2011            15.1

2012            15.6

a. Construct a time series plot. What kind of relationship exists in the data?

b. Develop a linear trend equation for these data.

c. Forecast the percentage of administrative expenses for 2013.

d. Using a smoothing constant of .2 forecast a value for 2013.

Hypothesis Testing. The researcher believes that if pregnant women take vitamins, the birth weight of their babies will be greater than 7.2 pounds. The researcher feeds vitamins to 49 pregnant women and measures the birth weights of their babies. The mean birth weight of the 49 babies born to women who take vitamins is 7.5 pounds, with a standard deviation of 0.9.

1. At alpha = .05, test the claim that the mean birth weight of babies whose mothers took vitamins is greater than 7.2 pounds.
2. Explain what a Type I Error would be for this experiment.
3. Explain what a Type II Error would be.

A manufacturer of potato chips would like to know whether its bag filling machine works correctly at the 446 gram setting. It is believed that the machine is overfilling the bags. A 33 bag sample had a mean of 452 grams. Assume the population variance is known to be 676. Is there sufficient evidence at the 0.1 level that the bags are overfilled?

Step 1 of 6: State the null and alternative hypotheses.

Step 2 of 6:

Find the value of the test statistic. Round your answer to two decimal places.

Step 3 of 6:

Specify if the test is one-tailed or two-tailed.

Step 4 of 6:

Find the P-value of the test statistic. Round your answer to four decimal places.

Step 5 of 6:

Identify the level of significance for the hypothesis test.

Step 6 of 6:

Make the decision to reject or fail to reject the null hypothesis.

A telephone company claims that the service calls which they receive are equally distributed among the five working days of the week. A survey of 8080 randomly selected service calls was conducted. Is there enough evidence to refute the telephone company's claim that the number of service calls does not change from day-to-day?

Copy Data

Step 1 of 10:

State the null and alternative hypothesis.

H0H0: Service calls are not equally distributed over the five working days.

HaHa: Service calls are equally distributed over the five working days.

or

H0H0: Service calls are equally distributed over the five working days.

HaHa: Service calls are not equally distributed over the five working days.

Step 2 of 10:

What does the null hypothesis indicate about the proportions of service calls received each day?

The proportions of service calls received each day are all thought to be equal.

or
The proportions of service calls received each day are different for each category (and equal to the previously accepted values).

Step 3 of 10:

State the null and alternative hypothesis in terms of the expected proportions for each category.

Ho:Pi=

Step 4 of 10:

Find the expected value for the number of service calls received on Monday. Round your answer to two decimal places.

Step 5 of 10:

Find the expected value for the number of service calls received on Thursday. Round your answer to two decimal places.

Step 6 of 10:

Find the value of the test statistic. Round your answer to three decimal places.

Step 7 of 10:

Find the degrees of freedom associated with the test statistic for this problem.

Step 8 of 10:

Find the critical value of the test at the 0.0250.025 level of significance. Round your answer to three decimal places.

Step 9 of 10:

Make the decision to reject or fail to reject the null hypothesis at the 0.0250.025 level of significance.

Fail to Reject Null Hypothesis

or

Reject Null Hypothesis

Step 10 of 10:

State the conclusion of the hypothesis test at the 0.0250.025 level of significance.

There is not enough evidence to refute the claim that the service calls are distributed evenly among the days.

or
There is enough evidence to refute the claim that the service calls are distributed evenly among the days.

The reaction time before lunch was compared with the reaction time after lunch for a group of 28 office workers. Twenty two workers found their reaction time before lunch was shorter, and two could detect no difference, while the rest had a longer reaction time before lunch. Is there evidence that the reaction time before lunch is significantly shorter than the reaction time after lunch?

Sampling is the process of selecting a representative subset of observations from a population to determine characteristics (i.e. the population parameters) of the random variable under study. Probability sampling includes all selection methods where the observations to be included in a sample have been selected on a purely random basis from the population. Briefly explain FIVE (5) types of probability sampling.