Quantitative Reasoning I Project: Selecting A Topic

The purpose of this assignment is to get you to think about what types of data-oriented problems you will be solving in your chosen career. In this assignment, you select a topic and an associated problem to solve. You will continue to work on analyzing and solving this problem throughout the remainder of this course.

Select a topic from the Quantitative Reasoning I Project Topics and Scenarios workbook. After opening the file, access the topics along with their data sets and problems by clicking the individual worksheet tabs near the bottom of the workbook. For t

Topic 1 – Health & Nursing

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

Topic 2 – Criminal Justice

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

Topic 3 – Hum. & Sciences

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

Topic 4 – Social Sciences

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

Topic 5 – Business

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

Topic 6 – Education

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

Review the data sets help document if you need assistance with locating all of the data sets.

Compose a 175-word response that addresses the following questions:

topic chosen is Health services and nursing scenario see excel sheet attached

  • What topic did you choose?
  • Why does it interest you?
  • What do you hope to discover in your analysis?