Revenue Cycle Management
Data is collected at each step of the revenue cycle, and an error or lack of action at any step in the cycle may result in delayed or lost revenue.

Discuss three steps in the revenue cycle, explaining what action occurs; provide an example for each step.

Describe a negative result, for each of your selected three steps, which may occur if the action is completed incorrectly or not at all.

Select one impact, from those you identified, and apply a policy which notes the process to be taken to prevent or minimize future occurrences of the noted negative event.

A steel mill in Canada has inverse demand function p = 100 – q (so its revenue function is given by R = 100q – q²) and cost function is C = 80 + 4q.

a) What is the firm’s output under each of the following three regimes?

i) Profit maximization.

ii) Revenue maximization.

iii) Output maximization subject to nonnegative revenue.

b) If MC = 0, which of the above three regimes (profit-maximizing, revenue-maximizing or output maximizing) is likely to yield higher total surplus (or be closer to competitive equilibrium)? Explain briefly without any calculation.

Nicholas Grammas is an investment analyst examining the performance of two mutual funds with Janus Capital Group: The Janus Balanced Fund and the Janus Overseas Fund.The following table reports the annual returns (in percent) of these two funds over the past 10 years. We assume the sample returns are drwan independently from normally distributed populations.

In a report, use the above information to:

1. Describe the similarities and differences in these two funds’ returns that you can observe from their descriptive statistics.

2. What is the two-tailed p-value?

3. Determine whether the risk of one fund is different from the risk of the other fund at the 5% significance level. (Two Sentences: one stating your decision using the p-value approach, and another stating your conclusion.)

Show all working out and reasoning, be specific and detailed please. Please do all working out in Excel only. Thank you. This is about Chi Squared Distribution:Statistical Inference Concerning Variance and F Distribution:Inference Concerning Ratio of Two Population Variances to give you an idea about what formulas I'm looking for. Thank you.

1. Do the variables have significant correlation? For full credit, you must show each step of the hypothesis test. Use the 0.05 significance.

2. In 2008, the price of gas dropped drastically and hit a low average of $1.59 for the nation. What effect do you think this will have on the alternative-fuel car sales, if any? Do you think that this would affect the number of alternative-fueled vehicles used in the United States? Do you think that it would follow the same pattern as before 2008? Write 2 or 3 sentences explaining how you think the new vehicles will affect the number of alternative-fueled vehicles in the United States.

3. Use your regression equation to predict the number of alternative-fueled vehicles used in the United States in 2010. Assume that the pattern remains the same after the introduction of the electric-gas vehicles. Show your work.

4. Search online to find some evidence for or against your opinion in part e. Give the information that you found and state the URL to the data. Was your prediction correct or incorrect? Why do you think that happened? Write 2 or 3 sentences summarizing the information that you found and explain why you think that happened. Be sure to answer each question.

An economist with a major bank wants to learn, quantitatively, how much spending on luxury goods and services can be explained based on consumers’ perception about the current state of the economy and what do they expect in the near future (6 months ahead).  Consumers, of all income and wealth classes, were surveyed.  Every year, 1500 consumers were interviewed.  The bank having all of the data from the 1500 consumers interviewed every year, computed the average level of consumer confidence (an index ranging from 0 to 100, 100 being absolutely optimistic) and computed the average dollar amount spent on luxuries annually.  Below is the data shown for the last 24 years.

Date                 X                     Y (in thousands of dollars)

1994                79.1                 55.6

1995                79                    54.8

1996                80.2                 55.4

1997                80.5                 55.9

1998                81.2                 56.4

1999                80.8                 57.3

2000                81.2                 57

2001                80.7                 57.5

2002                80.3                 56.9

2003                79.4                 55.8

2004                78.6                 56.1

2005                78.3                 55.7

2006                78.3                 55.7

2007                77.8                 55

2008                77.7                 54.4

2009                77.6                 54

2010                77.6                 56

2011                78.5                 56.7

2012                78.3                 56.3

2013                78.5                 57.2

2014                78.9                 57.8

2015                79.8                 58.7

2016                80.4                 59.3

2017                80.7                 59.9

Question:

1. Do you think that measuring the level of optimism is a good predictor for trying to forecast future spending on luxury items?  Explain why or why not.

The following six (4) questions are based on the following data:

When performing calculations in the following problems, use the numbers in the table as-is. I.e., do NOT convert 8.5985 to 8.5985% (or 0.085985). Just use plain 8.5985.

1. Using the basic market model regression, R p = α + β R m + ϵ, what is the beta of this portfolio? Yes, this is an opportunity to practice regression analysis. You can use Excel or other tool of choice.

2. For precision, find the portfolio beta using the excess return market model:

R p − R f = α + β ∗ ( R m − R f ) + ϵ

[Hint: compute annual excess returns first, then run regression.]

3. Using the excess return beta β ∗ from the previous problem, what is Jensen's alpha for the portfolio?

[Hint: use Equation (17.6) from Moore (2015)]

4. What is the portfolio's M2 measure?

The following data set provides information on the lottery sales, proceeds, and prizes by year in Iowa.

You decided to find the linear equation that corresponds to sales and year. Create a graph using the sales and year. Add the linear equation to the graph. What is the y-intercept of the linear equation?

Round each value below to the nearest integer.

Provide your answer below: ____E+ ___

3300 Econometric HW

Problem 2.

Use the data in the “Autocorrelation” tab to test

1. For Autocorrelation using the Durbin Watson Test

2. Graph the Residuals and determine whether they are distributed normally or whether they are biased

USING MATLAB:

Using the data from table below fit a fourth-order polynomial to the data, but use a label for the year starting at 1 instead of 1872. Plot the data and the fourth-order polynomial estimate you found, with appropriate labels. What values of coefficients did your program find? What is the LMS loss function value for your model on the data?

Nursing/Microbiology Question:

1. How could you differentiate between the common childhood skin rashes?
2. Why are the multidrug resistant strains of Staphylococcus aureus a major concern for health care facilities?
3. How can health care workers contribute to good antibiotic stewardship?
4. What features of Pseudomonas aeruginosa make it a major concern for health care facilities?
5. How are primary Gram smears used to assess skin infections?