Creating Visual Data

Use the data from the nursing scenario from the file I uploaded.

Create at least two visuals using your data from the data you chose in Week 2.

Create one scatter plot of the data, and apply a linear model (also known as a regression) in Excel®. Include the equation, R2 value, and prediction value on the visual.
Create one scatter plot of the data, and apply an exponential model in Excel®. Include the equation, R2 value, and prediction value on the visual.
Determine whether the linear or the exponential model is a better representation of your data to base your prediction on. Explain why the model you chose is a better representation of your data.

Hints for Making an Effective Chart:

Health Services and Nursing Scenario
Topic 1	Predicting the Number of Babies Born
Scenario 1	Review the data involving the number of babies born in Humboldt County from 2006-2015. Predict the number of babies who will be born in 2018.
Year	Babies Born in Humboldt County
2006	275
2007	280
2008	320
2009	366
2010	358
2011	336
2012	375
2013	390
2014	455
2015	487

Security and Criminal Justice Scenario
Topic 2	Predicting the Number of People Arrested for Drug Possession
Scenario 2	Review the data involving the number of people arrested for drug possession from 2006-2015. Predict the number of people who will be arrested for drug possession in 2018.
Year	People Arrested for Drug Possession
2006	1,519,760
2007	1,361,658
2008	1,321,824
2009	1,387,915
2010	1,179,728
2011	1,143,931
2012	1,237,708
2013	1,203,323
2014	982,169
2015	801,560

Humanities and Sciences Scenario
Topic 3	Predicting Student Smartphone Usage
Scenario 3	Review the data involving the average number of hours students spent on their smartphones from 2002-2015. Predict the number of hours students will spend on their smartphones in 2018.
Year	Average Number of Hours Students Spend on their Smartphones
2002	0.1
2003	0.75
2004	1
2005	1.5
2006	1.75
2007	5.5
2008	6
2009	9.3
2010	9.5
2011	8.9
2012	9
2013	11
2014	12.5
2015	10.6

Social Sciences Scenario
Topic 4	Predicting Test Performance Based on Sleep
Scenario 4	Review the data involving the number of hours students sleep and their average score on a test they take the next day. Predict the optimal hours of sleep students need the night before a test to achieve the highest score on the test.
Hours of Sleep	Average Score on Test
4	55
4.25	40
4.5	53
4.75	59
5	60
5.25	63
5.5	66
5.75	75
6	70
6.25	72
6.5	80
6.75	77
7	85
7.25	90
7.5	100
7.75	95
8	88
8.25	85
8.5	74
8.75	88
9	90
9.25	87
9.5	86
9.75	95
10	82

Business Scenario
Topic 5	Predicting Fuji Apple Purchases
Scenario 5	Review the monthly data involving Fuji apples purchased at a large grocery store. Predict how many Fuji apples will need to be in stock to have available for the customers in December (month 12)?
Month	Fuji Apples Purchased	Hint: When determining the solution to this question remember that amounts needed in a store will go up around holidays. Seasonality is a characteristic of a time series in which the data experiences regular and predictable changes that recur every calendar year. Any predictable change or pattern in a time series that recurs or repeats over a one-year period can be said to be seasonal.
1	5,325
2	5,648
3	5,873
4	9,842
5	8,234
6	9,421
7	10,123
8	9,784
9	10,443
10	9,564
11	10,147

Education Scenario
Topic 6	Elementary Education: Math Skills
Scenario 6	Review the data involving elementary students in Apache County who passed the AZ Merit Test from 2006-2015. Predict the number of students who will pass the AZ Merit test in 2018.
Fiscal Year	Students in Apache County who Pass the AZ Merit Test
2006	12
2007	7
2008	14
2009	18
2010	25
2011	37
2012	33
2013	39
2014	45
2015	42