A 62-year-old retired elementary school teacher presents to the emergency room with complaints of shortness of breath, swelling, and generally not feeling well.

Related Question #1

What physical assessments are priorities given her symptoms?

Related Question #2

What diagnostic tests should be ordered immediately? Explain the purpose(s) of each.

Part 2

Vital signs are obtained and recorded as BP 90/48, R24, HR 100 irregular and varying pulse quality, T 97.8°F, pulse oximetry at 92%. Cardiac monitor reveals atrial fibrillation with variable ventricular response. The following laboratory values are returned: troponin 0.02 ng/ml, BNP 400, Hb 10.6, Hct 31.8, BUN 44 Cr 2.

Related Question #3

Which of the laboratory tests are abnormal?

Related Question #4

What do the abnormal tests indicate?

Part 3

Physical examination reveals obese white female in acute distress with frequent deep sighing breaths. HEENT unremarkable, CN I to CN XII grossly intact. Responds slowly but accurately and appropriately. Negative jugular vein distention. Chest: crackles lower lobes bilaterally. Pansystolic murmur, irregular rhythm. Abdomen: mildly distended, soft with bowel sounds present all quadrants. No organomegaly. Genitalia: deferred. Extremities: moves all extremities on command. 2+ pitting edema bilaterally.

Related Question #5

Which physical signs and symptoms are indicative of congestive heart failure?

Related Question #6

What are the expected interventions?

Related Question #7

What is the purpose of each of these medications in the treatment of CHF?

Part 4

The patient is admitted with the following diagnoses:

Mitral valve regurgitation

CHF secondary to mitral valve disease

Renal failure secondary to CHF

Atrial fibrillation

Anemia

Related Question #8

Explain the development of congestive heart failure in this patient.

Related Question #9

Explain the relationship between the CHF, renal failure, and anemia.

Related Question #10

What is the significance of the atrial fibrillation?

Chris is undecided about whether to go back to school and get his master’s degree. He is trying to perform a cost-benefit analysis to determine whether the cost of attending the school of his choice will be outweighed by the increase in salary he will receive after he attains his degree. He does research and compiles data on annual salaries in the industry he currently works in (he has been working for 10 years), along with the years of experience for each employee and whether or not the employee has a master’s degree. Earning his master’s degree will require him to take out approximately $20,000 worth of student loans. He has decided that if the multiple regression model shows, with 95% confidence, that earning a master’s degree is significant in predicting annual salary, and the estimated increase in salary is at least $10,000, he will enroll in a degree program.

5. What is the average difference between the salaries of people with and without Master’s degree (holding years of experience constant)?

6. Does the master’s degree significantly influence the salary of the employees at the alpha level of 0.01?

7. Do the years of experience significantly influence the salary of the employees at the alpha level of 0.01? Make sure to show which values you use to make the decision.

8. Remember, Chris has decided that if the multiple regression model shows that earning a master’s degree is significant in predicting annual salary (at alpha of 0.05), and the estimated increase in salary is at least $10,000, he will enroll in a degree program. Should he? Use the actual numbers from the regression model to prove your answer. there should be two sets of values/numbers used.

Jack is undecided about whether to go back to school and get his master’s degree. He is trying to perform a cost-benefit analysis to determine whether the cost of attending the school of his choice will be outweighed by the increase in salary he will receive after he attains his degree. He does research and compiles data on annual salaries in the industry he currently works in (he has been working for 10 years), along with the years of experience for each employee and whether or not the employee has a master’s degree. Earning his master’s degree will require him to take out approximately $20,000 worth of student loans. He has decided that if the multiple regression model shows, with 95% confidence, that earning a master’s degree is significant in predicting annual salary, and the estimated increase in salary is at least $10,000, he will enroll in a degree program.

1. Is the regression model effective in predicting the DV at an alpha of 0.025? Make sure to show which values you use to make the decision.

2. Write down the multiple regression equation using actual names of IVs and DVs. You need an equation for each level of the qualitative IV.

3. What is the value of the estimated intercept? Interpret the value in terms of years of experience, master’s degree, and salary.

4. What are the values of the estimated slope for the variable “Master’s degree”? Interpret each value in terms of actual IVs and the DV.

A 16-year-old student comes to the school nurse’s office and tells the nurse that she thinks she might be pregnant. The student tells the nurse that she has not had a period in 3 months. The nurse checks the student’s file and finds that she has a history of asthma and a seizure disorder for which she has been prescribed daily drugs. Because the student takes these drugs at home, the nurse has not seen her on a regular basis. The nurse counsels the student about obtaining a pregnancy test. The student tells the nurse that before she can leave the office, she needs to know what might be wrong with her baby. The student states that she drinks heavily on weekends and that she probably was drunk when she became pregnant. She also states that she was concerned about taking her seizure medication during the months she thought she was pregnant, but she was too embarrassed not to take it because she did not want to have a seizure in front of her friends. The student tells the nurse that she has not taken any asthma medication and that she has been having a difficult time breathing.

question 1:

What can the nurse tell the student about the interval when she was taking her medications after possibly becoming pregnant?

Question 2:

When the student asks specifically how her baby may have been affected, how should the nurse reply?

question 3:

The student asks what alcohol can do to her baby. What would be the best response by the school nurse?

Richard Thaler, (Professor, The University of Chicago Booth School of Business) said: “We failed to learn from the hedge fund failures of the late ’90s.” His message (Links to an external site.)to overconfident risk managers: There’s more risk out there than you think.

a) What do you think of Wall Street (or any financial markets)? Do we need Wall Street? Why or Why not?

b) What is "The Paradox of Thrift"? How does that apply to our current situation?

–Construct a reasonable frequency distribution of High School GPA (HSGPA)

–Construct a histogram

–Present the frequency distribution and histogram

There are a total of 196 HS student GPAs. 1.6, 2, 2.1, 2.1, 2.2, 2.2, 2.2, 2.4, 2.4, 2.5, 2.5, 2.5, 2.5, 2.5, 2.6, 2.7, 2.75, 2.75, 2.75, 2.75, 2.75, 2.8, 2.8, 2.8, 2.9, 2.9, 2.9, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3.1, 3.1, 3.1, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 3.2, 3.23, 3.25, 3.25, 3.25, 3.25, 3.3, 3.3, 3.3, 3.3, 3.3, 3.31, 3.34, 3.4, 3.4, 3.4, 3.4, 3.4, 3.4, 3.4, 3.4, 3.4, 3.45, 3.479, 3.5, 3.5, 3.5, 3.5, 3.5, 3.5, 3.5, 3.5, 3.5, 3.5, 3.5, 3.5, 3.5, 3.5, 3.5, 3.5, 3.5, 3.5, 3.5, 3.5, 3.5, 3.5, 3.6, 3.6, 3.6, 3.6, 3.6, 3.6, 3.6, 3.6, 3.63, 3.63, 3.64, 3.65, 3.65, 3.7, 3.7, 3.7, 3.7, 3.7, 3.7, 3.7, 3.7, 3.7, 3.7, 3.7, 3.7, 3.7, 3.7, 3.729, 3.75, 3.75, 3.75, 3.8, 3.8, 3.8, 3.8, 3.8, 3.8, 3.8, 3.8, 3.8, 3.8, 3.8, 3.8, 3.8, 3.8, 3.8, 3.8, 3.8, 3.8, 3.8, 3.8, 3.8, 3.8, 3.81, 3.81, 3.83, 3.9, 3.9, 3.9, 3.9, 3.9, 3.92, 3.94, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4

Williams Products Inc. manufactures and sells a number of items, including school knapsacks. The company has been experiencing losses on the knapsacks for some time, as shown by the contribution format income statement below:

*Allocated on the basis of machine-hours.
^†Allocated on the basis of sales dollars.

     Discontinuing the knapsacks would not affect sales of other product lines and would have no noticeable effect on the company’s total general factory overhead or total purchasing department expenses.

Required:
a. Compute the increase or decrease of net operating income if the Williams Products Inc line is continued or discontinued. (Input all amounts as positive except Decreases in Sales, Decreases in Contribution Margin, and Net Losses which should be indicated by a minus sign.)

b. Would you recommend that the Williams Products Inc line be discontinued?

• Yes

• No

1. Within a school district, students were randomly assigned to one of two Math teachers - Mrs. Smith and Mrs. Jones. After the assignment, Mrs. Smith had 30 students, and Mrs. Jones had 25 students. At the end of the year, each class took the same standardized test. Mrs. Smith's students had an average test score of 78, with a standard deviation of 10; and Mrs. Jones' students had an average test score of 85, with a standard deviation of 15. Assume the variances are equal. At the significance level 0.10, can we conclude that Mrs. Jones is a more effective teacher than Mrs. Smith?

     a). Calculate the test statistic. (R code and R result).

     b). Find the p-value (R code and R result).

     c). Make your decision.

(1 point) Coaching companies claim that their courses can raise the SAT scores of high school students. But students who retake the SAT without paying for coaching also usually raise their scores. A random sample of students who took the SAT twice found 427 who were coached and 2733 who were uncoached. Starting with their verbal scores on the first and second tries, we have these summary statistics:

                              Try 1      Try 2      Gain

Estimate a 99% confidence interval for the mean gain of all students who are coached.

___________________ to
at 99% confidence.
Now test the hypothesis that the score gain for coached students is greater than the score gain for uncoached students. Let μ1 be the score gain for all coached students. Let μ2 be the score gain for uncoached students.

(a) Give the alternative hypothesis: μ1−μ2_______________ 0

(b) Give the tt test statistic:

(c) Give the appropriate critical value for α=5%:

High school seniors with strong academic records apply to the nation's most selective colleges in greater numbers each year. Because the number of slots remains relatively stable, some colleges reject more early applicants. Suppose that for a recent admissions class, an Ivy League college received 2851 applications for early admission. Of this group, it admitted 1033 students early, rejected 854 outright, and deferred 964 to the regular admission pool for further consideration. In the past, this school has admitted 18% of the deferred early admisiion applicants during the regular admission process. Counting the students admitted early and the students admitted during the regular admission process, the total class size was 2375. Let E, R, and D represent the events that a student who applies for early admissions is admitted early, rejected outright, or deferred to the regular admissions pool. A) Use data to estimate P(E), P(R), and P(D). B) Are events E and D mutually exclusive? Find P(EUD). C) For the 2375 students who were admitted, what is the probability that a randomly selected student was accepted during early admission? D) SUppose a student applies for early admission. What is the probability that the students will be admitted for early admission or be deferred and later admitted during the regular admission process?