You are applying for a job in the health care field. As part of the interview process, the hiring committee would like to explore your ability to analyze data and discuss the results of your research. The committee gives you the following assignment:

The table below shows the national expenditures for health care in the United Stated for selected years.

Math 156

Due date:

Year

National Expenditures for Health Care

(in billions of dollars)

1960

27.214

1963

34.595

1967

51.565

1972

92.657

1976

152.742

1983

367.809

1986

474.686

1989

644.770

1992

854.068

1995

1021.635

1999

1277.700

2001

1486.158

2004

1895.724

2010

2598.823

2011

2689.349

2012

2797.260

2013

2879.008

2014

3026.157

2015

3200.815

2016

3337.248

Source: United States Centers for Medicare and Medicaid Services

https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/NationalHealthAccountsHistorical.html

Make a report and write it in paragraph form and complete sentences, answering the following questions.Remember, this is to a potential employer so it should be well written and free of grammatical errors.

• -Using Excel (or Numbers for Mac), Make a scatterplot of the data withxas the number of years since 1950 andE(x) as the total expenditures for health care (in billions of dollars).Scatterplot should have axes labeled (this can be done neatly by hand if needed).Describe the nature of the data. Using your knowledge of non-linear functions in Chapter 2, what type or types of functions would make a good model for this data set? Why?
• -Use Excel to find a power model for the data (don't forget the r-squared value) and display the model against the scatterplot.
• -Use Excel to find a quadratic model (polynomial - degree 2) for the data (don't forget the r-squared value) and display the model against the scatterplot.
• -Use your knowledge on r-square values and the accuracy of models to explain which model is a more accurate depiction of the data.
• -Use the more accurate model to approximate 2020 expenditures. Why is it important to a company to be able to use statistics to make predictions?