Creating Visual Data
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 |