From 1995 to 2012, researchers surveyed the number of honeybee colonies in order to determine whether the population changed over time. The scatterplot below shows the relationship between these two variables along with the least squares fit. Round all calculated results to 4 decimal places.

1.The relationship between year and number of honeybee colonies is  ? positive negative ,  ? weak strong , and  ? linear non-linear .

2. The explanatory variable is  ? year days number of bees number of bee colonies  and the response variable is  ? year days number of bees number of bee colonies .

The summary statistics for number of colonies and year are listed below. The correlation between number of colonies and year is -0.3520 .

Year: mean = 2004.0625, standard deviation = 5.2086

Colonies: mean = 2536.3750, standard deviation = 111.5944

3. The equation for the regression line is y =  +  x

4.Complete the following sentence to interpret the slope of the regression line:

In 2 years, the number of colonies are expected to  ? decrease increase  by

5. Use the regression equation to estimate the number of colonies in 2012.

6. The actual number of colonies in 2012 was 2624. Complete the following sentence:

The residual for 2012 is  . This means the number of colonies in 2012 is
A. the same as
B. higher than
C. lower than
the number of colonies predicted by the regression model.

7. Would it be appropriate to use this linear model to predict the number of honeybee colonies in 1982?

A. No, because 1982 is beyond the range of the data used to build the regression model.  
B. Yes, because 1982 is a reasonable year to predict data for.
C. No, because 2702.7841 number of colonies is too large to be a reasonable number of colonies, even for this year.

The American Journal of Public Health (July 1995) published a study of the relationship between passive smoking and nasal allergies in Japanese female students. The study revealed that 40% of the students from heavy-smoking families showed signs of nasal allergies on physical examination. Let x denote the number of students with nasal allergies in a random sample of 6 Japanese female students exposed daily to heavy smoking.

a. What is the probability that at least four of the students will have nasal allergies?

b. What is the probability that at least two of the students will have no nasal allergies?

c. Suppose instead of 6, a random sample of 20 Japanese female students were exposed daily to heavy smoking, what is the probability that between 4 and 14 (both points inclusive) of the students will have nasal allergies?

An organization monitors many aspects of elementary and secondary education nationwide. Their 1995 numbers are often used as a baseline to assess changes. In 1995​, 42 % of students had not been absent from school even once during the previous school year. In the 1999 ​survey, responses from 7146 randomly selected students showed that this figure had slipped to 41 %. Officials would note any change in the rate of student attendance. Answer the questions below.

​(a) Write appropriate hypotheses.

Upper H 0 : The percentage of students in 1999 with perfect attendance the previous school year (1)_______

Upper H Subscript Upper A Baseline : The percentage of students in 1999 with perfect attendance the previous school year (2)_________

​(b) Check the necessary assumptions and conditions.

The independence assumption is (3)___________

The randomization condition is (4) __________

The​ 10% condition is (5)____________

The​ success/failure condition is (6) ​______________

(c) Perform the test and find the​ P-value. ​

P-value equals _____________ ​(Round to three decimal places as​ needed.)

​(d) State your conclusion. Consider probabilities less than 0.05 to be suitably unlikely.

A. We fail to reject the null hypothesis. There is not sufficient evidence to suggest that the percentage of students with perfect attendance in the previous school year has changed.

B. We fail to reject the null hypothesis. There is sufficient evidence to suggest that the percentage of students with perfect attendance in the previous school year has changed.

C. We can reject the null hypothesis. There is sufficient evidence to suggest that the percentage of students with perfect attendance in the previous school year has changed.

(1) is greater than 42%.

is different from 42%.

is less than 42%.

is equal to 42%.

(2) is less than 42%.

is different from 42%.

is greater than 42%.

is equal to 42%.

(3) satisfied. not satisfied.

(4) satisfied. not satisfied.

(5) not satisfied. satisfied.

(6) satisfied. not satisfied.

1. SIMPLE LINEAR REGRESSION. For this and the next 3 parts. The journal, Fisheries Science (Feb 1995) reported on a study of the variables that affect endogenous nitrogen excretion (ENE) in carp raised in Japan. Carp were divided into groups of 2 to 15 fish each according to body weight and each group placed in a separate tank. The carp were then fed a protein-free diet three times daily for a period of 20 days. One day after terminating the feeding experiment, the amount of ENE in each tank was measured. The table below gives the mean body weight (in grams) and ENE amount (in milligrams per 100 grams of body weight per day) for each carp group [Source: Watanabe, T. and Ohta, M. "Endogenous Nitrogen Excretion and Non-Fecal Energy Loss in Carp and Rainbow Trout," Fisheries Science, Vol. 61, No. 1, Feb 1995, p. 56]. You should be able to determine which variable is the response variable and which is the explanatory variable. Which of the following is true? [I] Plot of the residuals shows an upward curvature [II] Plot of the residuals shows a downward curvature [III] The regression is significant at the 1% level [IV] Correlation coefficient of the two variables = -0.68 [V] Standard error of the estimate is 0.0297.

   Tank	Body Weight	ENE
   1	11.7	15.3
   2	25.3	9.3
   3	90.2	6.5
   4	213.0	6.0
   5	10.2	15.7
   6	17.6	10.0
   7	32.6	8.6
   8	81.3	6.4
   9	141.5	5.6
   10	285.7	6.0

   		I and V only
   		II, IV, V
   		I and IV only
   		II and III only
   		None of the above

Part B.

1. SIMPLE LINEAR REGRESSION (above data). Give a 99% prediction interval for the expected (mean) value of the dependent variable with X = 0 (note alpha = 0.01).

   		8.3724; 14.4355
   		6.9928; 15.8151
   		-0.0508; -0.0034
   		-0.0615; 0.0073
   		None of the above

Part C.

1. SIMPLE LINEAR REGRESSION (above data). Give a 99% confidence interval for the slope (note alpha = 0.01).

   		8.3724; 14.4355
   		6.9928; 15.8151
   		-0.0508; -0.0034
   		-0.0615; 0.0073
   		None of the above

Part D.

1. MULTIPLE REGRESSION (refer to above data). Conduct a multiple regression by introducing a quadratic term to the model. Which of the following is true? [I] About 74% of the variation in Y explained the regression [II] At the 1% level, the regression is statistically significant [III] At the 5% level, the regression is statistically significant [IV] Both coefficients are statistically significant at the 5% level [V] At least one of the independent variables is not significant

   		I, III, V
   		III, IV, V
   		I, II, IV
   		None of the above

In August 1995, Smith Company ("Smith") entered into a lease with Jones Two, Inc. ("Jones"). By the terms of the lease, Jones leased a Washington D.C. property (the "Property") that was owned by Smith for a period of ten (10) years.

In 1995, when Jones originally entered into the lease it had not filed its articles of incorporation in any state. However, it represented itself as having been incorporated in New York and Smith relied on that representation. In 1996, Smith realized that Jones was not incorporated but it continued to honor its lease with Jones.

Jones finally got around to properly incorporating in New York in 1997.

At all times, Jones conducted business as if it were a corporation and it complied with all of the terms of the Smith Lease.

By 2000, the value of the Property had increased significantly and Smith was looking for a way to get out of its lease with Jones so it could enter into a lease with a higher rent provision. Smith thought back to the 1995 creation of the lease and it recalled that Jones was not incorporated at that time.

Smith provided Jones with a notice of termination of the lease and directed Jones to vacate the Property within 90 days stating that the lease was void since Jones did not legally exist at the time it entered into the lease. Jones refused to vacated and maintained that it was entitled to use the property until 2005 under the terms of the lease.

Provide an answer to the following questions and be sure to fully explain the reasons for your answer. Be sure to use full sentences and paragraph form in providing your responses.

We know that Jones wants to keep the lease in place until 2005.

4. Could Jones use the concept of a de jure corporation to effectively counter the argument of Smith? Why or why not?

5. Could Jones use the concept of a de facto corporation to effectively counter the argument of Smith? Why or why not?

6. Could Jones use the concept of a corporation by estoppel to effectively counter the argument of Smith? Why or why not?

Each question

You are working for the CFO of AT&T. You collect stock return data from 1995 to 2016 (23 years of data): average return: 9.9%; standard deviation: 23.1%; market average excess return: 8.5%; market SD: 14.5%; average risk-free rate: 2.3%.

1. What was AT&T’s Sharpe ratio (the ratio of average excess return to standard deviation) over the period? What was the market’s Sharpe ratio?

2. What is the standard error of the sample average AT&T return? Provide a 95% and 99% confidence interval.

3. You also look at the AT&T beta which is 0.4. Is AT&T’s beta above or below average?

4. If, over the next week, the market goes up by 2%, what do you expect the AT&T stock return to be?

TzeMay was one of the first women engineering students at ABC University. She graduated in 1995 with a first class honours degree and immediately continued her studies with an MSc programme, gaining recognition for her work into environmentally friendly car engines, a largely untapped field in those days. On completion of her Masters degree she was offered a post as a research assistant where she could have developed her Masters research and worked towards her doctorate. However she decided that she needed to gain some commercial experience and joined Wallace-Price, a blue-chip engineering consultancy where, apart from a sponsored year out to study for an MBA in the United States of America, she has remained ever since.

Her tenacity and loyalty to Wallace-Price have paid off and she was made a partner in the firm, primarily responsible for bringing in work to the consultancy. With the promotion came various executive privileges including an annual salary of £80, 000, a chauffeur-driven car, free use of one of the company-owned London flats, a non-contributory pension scheme, various gold credit cards and first-class air travel. TzeMay herself would not describe these as benefits, however, but as necessities to enable her to do her job properly. In order to meet her business target of £2 million of work for Wallace-Price she spent forty weeks overseas, working an average of ninety hours a week.

She cannot remember the last time that she had a weekend when she was not entertaining clients or travelling but was totally free to indulge herself. During her time with Wallace-Price she has earned a reputation both as a formidable but honest negotiator and as an innovative engineer, often finding seemingly impossible solutions to problems. Known for her single-minded dedication to her job, she does not suffer fools gladly. She is frequently approached to work for rival firms with promises of even greater privileges and has been the subject of numerous magazine profiles, some concentrating on her work and reputation as a high flier but the majority focusing on her gender. Her fortieth birthday last year was spent alone in the Emergency Room of a Los Angeles hospital where she had been rushed with a suspected stomach ulcer. Deprived of her portable telephone, fax and computer she had little else to do but to reflect on her life thus far. On her return to health she was working her way through the pile of technical journals, which had accumulated during her absence and there she saw the advertisement for ABC University, an institution that had close links with her company and whose Professor of Engineering she knew well. Ignoring the instructions relating to applications she put through a telephone call to the ABC University.

Question 1 : Making reference to the appropriate theories of motivation, explain TzeMay‟s main motivating factors.

An experiment is planned to compare three treatments applied to shirts in a test of durable press fabric treatments to produce wrinkle-free fabrics. In the past formaldehyde had been used to produce wrinkle-free fabric, but it was considered an undesirable chemical treatment. This study is to consider three alternative chemicals: (a) PCA (1-2-3 propane tricarbolic acid), (b) BTCA tetracarboxilic acid), and (c) CA (citric acid). Four shirts will be used for each of the treatments. First, the treatments are applied to the shirts, which are then subjected to simulated wear and washing in a simulation machine. The chemical treatments will not contaminate one another if they are all placed in the same washing machine during the test. The machine can hold one to four shirts in a single simulation run. At the end of the simulation run each of the shirts is measured for tear and breaking strength of the fabric and how wrinkle-free they are after being subjected to the simulated wear and washing. The comparisons among the treatments can be affected by (a) the natural variation from shirt to shirt; (b) measurement errors; (c) variation in the application of the durable press treatment; and (d) variation in the run of the simulation of wear and washing by the simulation machine. Following is a brief description of three proposed methods of conducting this simple experiment.

Method I. The shirts are divided randomly into three groups of four shirts. Each group receives a durable press treatment as one batch and then each batch is processed in one run of the simulation machine. Each run of the simulation machine has four shirts that have receive and same treatment. There are three runs of the simulation machine.

Method II. The shirts are divided randomly into three treatment groups of four shirt each, and the durable press treatments are applied independently to single shirts. The shirts are grouped into four sets of three, one shirt from each durable press treatment in each of the four sets, and each set of three so constructed is used in one run of the simulation machine. There are four runs of the simulation machine.

Method III. The shirts are divided randomly into three groups of four shirts. The durable press treatments are applied independently to single shirts. The simulation of wear and washing is done as in Method I.

a. Which method do you favor?

b. Why do you favor the method you have chosen?

c. Briefly, what are the disadvantages of the other two methods?

An exercise science major wants to try to use body weight to predict how much someone can bench press. He collects the data shown below on 30 male students. Both quantities are measured in pounds.

b) Compute a 95% confidence interval for the average bench press of 150 pound males. What is the lower limit? Give your answer to two decimal places.  

c) Compute a 95% confidence interval for the average bench press of 150 pound males. What is the upper limit? Give your answer to two decimal places.

d) Compute a 95% prediction interval for the bench press of a 150 pound male. What is the lower limit? Give your answer to two decimal places.

e) Compute a 95% prediction interval for the bench press of a 150 pound male. What is the upper limit? Give your answer to two decimal places.