20.24 Xr20-24 The quarterly earnings (in $millions) of a large soft-drink manufacturer have been recorded for the years 2013–2016. These data are listed here. Compute the seasonal indexes given the regression line

y^=61.75+1.18t (t=1,2,...,16)

Year

2013 2014 2015 2016

Quarter

1 52 57 60 66

2   67 75 77 82

3   85 90 94 98

4  54 61 63 67

Use the seasonal indexes and trend line to forecast the quarterly earnings for the years 2014 and 2015 in Exercise 20.24 (above)

1. Consider a study on the number of accidents occurred in 10 states of the United States of America in different cities for 3 consecutive years. Create a PivotTable in Excel to answer the following questions. The PivotTable should group the number of accidents into yearly bins and display the sum of accidents occurred each year in columns of Excel. Row labels should include the accident locations and allow for grouping the locations into states or viewing by city. You should also sort the PivotTable so that the states with the greatest number of accidents between 2011 and 2013 appear at the top of the PivotTable.

1. Which state had the greatest number of accidents between 2011 and 2013?
2. How many accidents occurred in the state of Colorado (CO) in 2012? In what cities did these accidents occur?
3. Use the PivotTable’s filter capability to view only the accidents in Alabama (AL), Arizona (AZ), and Arkansas (AR) for the years 2011 through 2013. What is the total number of accidents in these states between 2011 and 2013?
4. Create a PivotChart to display a column chart that shows the total number of accidents in each year 2011 through 2013 in the state of California. Adjust the formatting of this column chart so that it best conveys the data. What does this column chart suggest about accidents between 2011 and 2013 in California? Discuss.

Hint: You may have to switch the row and column labels in the PivotChart to get the best presentation for your PivotChart.

2. Hire-a-Car System rents three types of cars at two different locations. The profit made per day for each car type and company at the two locations is listed below:

A simple random sample of 600 individuals provides 100 Yes responses.

a. What is the point estimate of the proportion of the population that would provide Yes responses (to 3 decimals, if needed)?

b. What is your estimate of the standard error of the proportion (to 4 decimals)?

c. Compute the 95% confidence interval for the population proportion (to 3 decimals).

1.When the value of the standard deviation increases, the value of the z score will generally tend to

a. increase

b. decrease

2. In a standard normal distribution, what z-score corresponds to the 75th percentile?

a. z=.67

b. z=.07

c. z=.75

d. z=1.75

3. The total area under the normal curve is approximately 1.

a. true

b. false

4. If IQ scores are normally distributed with a mean of 100 and a standard deviation of 20, then the probability of a person's have an IQ score of at least 130

a. is does not exist

b. .0668

c. is .4332

d. is .5000

5. The life of a brand of battery is normally distributed with a mean of 2 hours and a standard deviation of 6 hours. The probability that a single randomly selected battery lasts more than 70 hours is

a. .0000

b. .0918

c. .4082

d. .9082

6. Suppose family incomes in a small town are normally distributed with a mean of $1200 and a standard deviation of $600 per month. The probability that a given family has an income between $1000 and $2050 per month is

a. .0918

b. .4082

c. .9082

d. .5515

7. Suppose family incomes in a small town are normally distributed with a mean of $1200 and a standard deviation of $600 per month. The probability that a given family has an income up to $2,000 per month is

a. .9082

b. .0918

c. .4082

d. .5515

8. The normal distribution is centered at its mean.

a. true

b. false

what would the effect be of a one-tailed test and the probability of rejecting the null hypothesis?

Mean 55.533796

Std Dev 4.5528105

Std Err Mean 1.0180394

Upper 95% Mean 57.664577

Lower 95% Mean 53.403015

N 20

t Test Test Statistic Prob > t 0.9170

Answer the following questions by filling in the blanks for each situation.

Report each answer as a number and round to two (2) decimal places. Please note that answers that do not follow this exact specification will not receive any credit.

1. The value of the population mean under the null hypothesis equals

2. The number of degrees of freedom for the sampling distribution of the t-ratio in this problem equals

3. The p-value associated with this test equals

A large consumer electronics retailer is planning to expand its e-commerce operations. To this end, the management is considering establishing a strategic partnership with courier company XYZ for the delivery of customers’ orders.
Question 1
The management of the retailer is prepared to proceed with the partnership only if XYZ can deliver orders faster than company ABC that is currently used by the retailer. The e-commerce department of the retailer has collected data from 50 random orders delivered by ABC in the last two months and 38 similar random orders delivered by XYZ in the same period. The data is included in the table below and refer to the time (in hours) between the placement of each order and the delivery to the customer. Use an appropriate statistical test to advise the management of the retailer whether or not they should partner with XYZ.

A simple random sample of size n equals 18 is drawn from a population that is normally distributed. The sample mean is found to be x overbar equals 62 and the sample standard deviation is found to be s equals 20. Construct a 95​% confidence interval about the population mean.

An analysis is interested in testing whether four population have equal means. The following sample data have been collected from population that are assumed to be normally distributed with equal variance:

You should use the output information in the following manner to answer the question.

1. Calculate the means and standard deviations.

2. Run the appropriate analysis using SPSS. Write the results in the ANOVA table below.

3. Conclusion

4. Write all SPSS Steps:

Run a regression analysis on the following bivariate set of data with y as the response variable.

Verify that the correlation is significant at an α=0.05. If the correlation is indeed significant, predict what value (on average) for the explanatory variable will give you a value of 82.3 on the response variable.

What is the predicted explanatory value?
x =

(Report answer accurate to one decimal place.)

Answer the following questions in the space provided in your own words. 1. A Bureau of Labor Statistics (BLS) economist conducts a statistical study to test his hunch that in households with a minimum-wage worker, mean household debt changes following a hike in the minimum wage. Suppose the mean household debt stays the same following a minimum-wage hike. However, when the economist collects a random sample, the sample mean difference is actually greater than zero.

a. Does this mean the economist made a mistake in his research? Explain why/why not.

b. Suppose the economist collects a random sample and decides to conduct a hypothesis test. Formulate the null and alternative hypothesis: c

. For each statement in the following table, place in X in the correct box to indicate whether the statement is the null hypothesis, the alternative hypothesis, or neither (Hint: this is a non-directional hypothesis test)

On December 17, 2007 baseball writer John Hickey wrote  an article for the Seattle P-I about increases to ticket prices for Seattle Mariners games during the 2008 season. The article included a data set that listed the average ticket price for each MLB team, the league in which the team plays (AL or NL), the number of wins during the 2007 season and the cost per win (in dollars). The data for the 16 National League teams are shown below.

Compute the correlation between average 2007 price and cost per win for these 16 teams. (Assume the correlation conditions have been satisfied and round your answer to the nearest 0.001.)

A regression model to predict Y, the state-by-state 2005 burglary crime rate per 100,000 people, used the following four state predictors: X₁ = median age in 2005, X₂ = number of 2005 bankruptcies per 1,000 people, X₃ = 2004 federal expenditures per capita, and X₄ = 2005 high school graduation percentage.

(a) Write the fitted regression equation. (Round your answers to 4 decimal places. Negative values should be indicated by a minus sign.)

yˆy^ =  +  AgeMed +  Bankrupt +  FedSpend +  HSGrad%

(b-1) The 2005 state-by-state crime rate per 100,000

(b-2) The 2005 state-by-state crime rate per 100,000    

(b-3) The 2005 state-by-state crime rate per 100,000           

(b-4) The 2005 state-by-state crime rate per 100,000      

(c) Would the intercept seem to have meaning in this regression?

(d) Make a prediction for Burglary when X₁= 34 years, X₂= 7.2 bankruptcies per 1,000, X₃= $5,044, and X₄= 84 percent.

Burglary Rate

rev: 09_26_2016_QC_CS-62964, 09_20_2017_QC_CS-1011

Why do we use adjusted R² instead of R² in variable selection? Why do we not always choose the model with the highest adjusted R²?