Operating cash inflows   Strong Tool Company has been considering purchasing a new lathe to replace a fully depreciated lathe that would otherwise last 5 more years. The new lathe is expected to have a​ 5-year life and depreciation charges of $2,020 in Year​ 1; $3,232 in Year​ 2; $1,919 in Year​ 3; $1,212 in both Year 4 and Year​ 5; and $505 in Year 6. The firm estimates the revenues and expenses​ (excluding depreciation and​ interest) for the new and the old lathes to be as shown in the following table

. The firm is subject to a 40% tax rate on ordinary income.

a. Calculate the operating cash inflows associated with each lathe.​ (Note: Be sure to consider the depreciation in year​ 6.)

b. Calculate the operating cash inflows resulting from the proposed lathe replacement.

c. Depict on a time line the incremental operating cash inflows calculated in part b.

a. Calculate the operating cash inflows associated with the new lathe​ below:  ​(Round to the nearest​ dollar.)

​(Round to the nearest​ dollar.)

​(Round to the nearest​ dollar.)

​(Round to the nearest​ dollar.)

​(Round to the nearest​ dollar.)

A market research firm supplies manufacturers with estimates of the retail sales of their products from samples of retail stores. Marketing managers are prone to look at the estimate and ignore sampling error. An SRS of 29 stores this year shows mean sales of 74 units of a small appliance, with a standard deviation of 12.2 units. During the same point in time last year, an SRS of 26 stores had mean sales of 62.166 units, with standard deviation 15.2 units. An increase from 62.166 to 74 is a rise of about 16%.

1. Construct a 99% confidence interval estimate of the difference μ1−μ2μ1−μ2, where μ1μ1 is the mean of this year's sales and μ2μ2 is the mean of last year's sales.

(a) ________<(μ1−μ2)<_____________

(b) The margin of error is:

2. At a 0.010.01 significance level, is there sufficient evidence to show that sales this year are different from last year?

A. Yes
B. No

A researcher wants to determine the relationship between the typing speed of administrative assistants at a major university is related to the time that it takes for the admin assistant to learn to use a new software program and may be used to predict learning time. Data are gathered from 12 departments at the university.

Dept Typing speed (words per minute) Learning time (hours)

A 48 7

B 74 4

C 52 8

D 79 3.5

E 83 2

F 56 6

G 85 2.3

H 63 5

I 88 2.1

J 74 4.5

K 90 1.9

L 92 1.5

Run a regression analysis of the data on Excel. Use your output to answer the following:

d. What is the value of the correlation coefficient between typing speed and learning time? What does is say about the strength of the relationship?

Our pulse rate is extremely important, because it is difficult to function without it! Physicians use pulse rates to assess the health of patients. A pulse rate that is abnormally high or low suggests that there might be some medical issue; for example, a pulse rate that is too high might indicate that the patient has an infection or is dehydrated.

Consider pulse rate measurements (in beats per minute) obtained from a sample of 5 females as follows:

74 68 89 62 72

Answer the following Questions:

1. The mean pulse rate of the data is

1. 74
2. 75
3. 73
4. 72

2. The standard deviation of the data is

1. 10.10
2. 10.01
3. 10.5
4. 10.6

3. Using the range rule of thumb ,the minimum “usual” pulse rate is

1. 53.98
2. 52.98
3. 54.98
4. 55.98

4. Using the range rule of thumb ,the maximum “usual” pulse rate is

1. 92.02
2. 93.02
3. 94.02
4. 95.02

Listed below are the heights of candidates who won elections and the heights of the candidates with the next highest number of votes. The data are in chronological​ order, so the corresponding heights from the two lists are matched. Assume that the paired sample data are simple random samples and that the differences have a distribution that is approximately normal. Construct a​ 95% confidence interval estimate of the mean of the population of all​ "winner/runner-up" differences. Does height appear to be an important factor in winning an​ election?

Winner 75 72 73 74 72 73 76 73

​Runner-Up 74 71 70 70 69 73 72 72

Construct the​ 95% confidence interval.​ (Subtract the height of the​ runner-up from the height of the winner to find the​ difference, d.)

B) Based on the confidence interval, does the height appear to be an important factor in winning an election?

A college physics professor thinks that two of her sections scored differently on the final exam.

She collects the scores for the two classes and stores them in a file.

We do not know anything about the test score distributions.

Answer the following. Use alpha = 0.05.

a). What is the value of the test statistic?

b). What is the p-value?

c). Is she correct in stating that the final exam scores from the two sections are not equal to each other?

Here is the data...

74   75
79   77
65   76
58   82
67   88
61   91
63   92
64   70
62   89
72   85
66   71
58   82
66   91
63   77
61   67
73   87
77   92
68   88
62   94
67   85
81   97
80   93
58   74

You will complete a question about Correlation Examples and complete a Simple Linear Regression. For the Simple Linear Regression, make sure to complete the following steps:

Construct a scatter plot.

Find the equation of the regression line.

Predict the value of y for each of the x-values.
Use this resource: Regression

Give an example of two variables that have a positive linear correlation. Give an example of two variables that have a negative linear correlation. Give an example of two variables that have no correlation. Height and Weight: The height (in inches) and weights (in pounds) of eleven football players are shown in this table.

Height, x 62 63 66 68 70 72 73 74 74 75 75

Weight, y 195 190 250 220 250 255 260 275 280 295 300

x = 65 inches x = 69 inches x = 71 inches

A study was conducted among children aged 8-10 to determine if resting heart rate differed between males and females. Independent samples of 8 females and 8 males were selected from the two respective populations.

The results were as follows (heart rates in beats/min):

Females 71, 80, 80, 75, 78, 77, 81, 82

Males 71, 81, 79, 74, 73, 78, 71, 74

Assume the samples were drawn from normally distributed populations with equal variance.

a) Use α = 0.05 (two-tailed) and assume 80% power.

b) State the null and alternative hypotheses.

c) List the critical value

d) Perform the appropriate statistical test using the attached SAS file.

e) If the decision was to fail to reject Ho, can Ho be accepted?

All work needs to be shown

Consider all observations as one sample of X (1st column) and Y (2nd column) values. Answer the following questions: (20 points)

a) Calculate the correlation coefficient r

b) Fit the regression model (predicting Y from X) and report the estimated intercept and slope.

c) Test whether the slope equals 0. Report your hypothesis, test statistic, p-value.  

All work needs to be shown

10. Ms. McNicholas wants to see if there is any difference in the Final Exam scores of her two Statistics classes. Class I 81 73 86 90 75 80 75 80 75 81 85 87 83 75 70 65 80 76 64 74 86 80 83 67 82 78 76 83 71 90 77 81 82 Class II 87 77 66 75 78 82 82 71 79 91 97 89 92 75 89 75 95 84 75 82 74 77 87 69 96 65 a) Find the five-number summary for each class. b) Construct a boxplot for each class. c) Determine the range for outliers on each graph. d) Is there a difference in the performance of the two classes?