The following data lists the grades of 6 students selected at random: Mathematics grade: (70, 92, 80, 74, 65, 85) English grade: (69, 88, 75, 80, 78, 90)

a). Find the regression line.

b). Compute and interpret the correlation coefficient.

74 years female patient Jevity 65ml/hours on 11 am off at 8 am

1-describe causes of enteral nutrition

2-steps of how to administer enteral nutrition formulas with enteral pumps

3-in a word document ,arial x 12

Weisbro and Sons common stock sells for $21 a share and pays an annual dividend that increases by 5.4 percent annually. The market rate of return on this stock is 9.4 percent. What is the amount of the last dividend paid by Weisbro and Sons?

• $.74

• $1.08

• $1.87

• $.80

• $.89

Organizations use budgets to reach their financial goals. A planning budget is a detailed financial plan that shows future income and expenses. For example, all of us sometimes create household budgets that plan projected income and expenses for food, clothing, housing, etc. At the end of the budgeting period, we compare what we earned and our expenses to the planning budget to make sure we followed the plan. For example, if we buy a boat and didn’t budget for that boat, what might happen? Organizations use budgets in a similar way.

We also create flexible budgets to help guide actual operations. For example, an organization’s actual expenses will rarely equal its budgeted expenses as estimated. Activities, such as sales, are rarely the same as budgeted. Many actual expenses and revenues will naturally differ from what was budgeted. A flexible budget is an estimate of what revenues and costs should have been, given the actual level of activity for the period. A flexible budget might help us to justify buying that boat!

Variance analysis evaluates and improves performance. A varianceis the difference between the actual amount and the amount budgeted in a certain time period. In other words, the amounts are different. Revenue variance is the difference between actual revenue and budgeted revenue. If the actual revenue is higher than budgeted revenue, the variance is labeled favorable. If actual revenue is less than budgeted, the variance is labeled unfavorable. Spending variances also occur. If the actual spending exceeds budgeted spending, the variance is unfavorable. If the actual spending is less than budgeted spending, the variance is favorable. As you can see, earning more than budgeted is good, but we should try to avoid spending more than what we budget. Think about the boat!

• Describe the budgeting process at your place of work. If you do not work or if this information is not available, you may describe the budgeting process you use in your personal life.
• Explain how using a flexible budget and variance analysis can help make the process you described above more effective.

"The Simon Machine Tools Company is considering purchasing a new set of machine tools to process special orders. The following financial information is available.
- Without the project, the company expects to have a taxable income of $487,000 each year from its regular business over the next three years.
- With the three-year project, the purchase of a new set of machine tools at a cost of $54,000 is required. The equipment falls into the MACRS three-year class. The tools will be sold for $10,000 at the end of project life. The project will be bringing in additional annual revenue of $80,000, but it is expected to incur additional annual operation of $16,000.
What are the additional income taxes paid because of the project in year 2 if the tax rate is 34%?"

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

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