Math Statistics Powerpoint 5-7 slides For Kim Woods

 PLEASE USE ATTACHMENT TO COMPLETE POWERPOINT

Create a 5- to 7-slide Microsoft® PowerPoint® presentation including:

• Introduction (approximately 1 minute and 1 slide)

• Which topic and scenario did you choose? I chose Health Services and Nursing Scenario in order to predict future medicare costs.
• Why did it interest you? I wanted to find the average medicare costs to payers in 2018 so people know what to expect to be paying in the future compared to past averages. 
• Visuals/Evidence (approximately 4 to 5 minutes and 3-4 slides)

• Show your data table, scatterplot, other two visuals, calculations, and any other evidence to support your conclusion.
• Explain what information in the data tables is not needed for your analysis. Explain why the unused information is not needed.
• Discuss why you selected each visual and what you can conclude from the visuals.
• Conclusion (approximately 1 minute and 1-2 slides)

• Restate your topic and scenario and give your conclusion.
• Discuss how your topic relates to a real-world scenario.
• Explain how confident you are that your conclusion is sound.
• Explain what work would need to be done to increase your confidence in your conclusion.
• Discuss what you learned from this project.
• Include detailed speaker notes for each slide.

TITLE: Health Service and Nursing Visuals from Data

John Tidwell

MTH/216

December 13, 2017

Mark Fisher

The scatter plot for the Health Service and Nursing scenario is given as below:

The scatter plot shows the distribution of the Medicare payers from 2002 – 2014. From the scatter plot, it is evident that the data sets have a positive relationship. As the year of payment increases, the number of payers also increases in the same manner. The coefficient of determination R2 is 0.9224, this implies that 92% of the number of payers are explained by the time periods on which they made the payments. Given the regression equation, the prediction for 2015 which is 13 years from now, x = 13, we have that:

Number of payers (2015) = 31852 + 2613.2x where x = 13

= 31852 + 2613.2 × 13

= 65,554 medical payers

Given that 92% of the number of payers are explained by the model, am quite confidence that the prediction holds since the model explains 92% of the variability of the number of payers.

The pie chart for the scenario is shown below:

The pie chart shows the proportion of Medicare Payers for each year in relation to the total payers. It is evident that 2014 has the highest number of payers (representing 11%) whereas 2003 and 2004 have the smallest proportion of the payers, i.e. 6% each.

The corresponding histogram is shown below:

The histogram shows the proportion of the payer that are within a given rage. From the histogram above, the highest payers ever experienced lie between 35,000 and 41,000. The lowest number of payers lies between 46,000 and 52,000. Therefore, the average medical payers are between 35,000 and 41,000.

References

Bennett, J. & Briggs, W. (2014). Using & Understanding Mathematics: A Quantitative Reasoning Approach (6th ed.). Pearson

Medicare Payers Scatter plot

Medicare payers

35612 37412 39841 40123 43122 44125 51229 59748 57008 56727 57985 63123 35612 37412 39841 40123 43122 44125 51229 59748 57008 56727 57985 63123

Time Period

Numbers of Medicare Payers

Medicare Payers Pie Chart

Medicare payers

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 35612 37412 39841 40123 43122 44125 51229 59748 57008 56727 57985 63123