1. Using FARS Queries For Concept Papers

2. Objectives By the end of this session, you will be able to: Identify data to best support a given problem Discuss various statements expressing data as a statistic Recognize a problem by analyzing data

3. Fatality Analysis Reporting System (FARS) Compilation of fatalities across US including: –Person types involved –Location of occurrence –Possible causes of each fatality Pre-created tables of data Tables created using Query

4. Example 1: Formulate Problem Adults riding in vehicles without proper restraint device Children riding in vehicles with out child restraint Those without restraints in crashes resulting in injuries or death

5. Example 1: Determine Supporting Data Identify the number of fatal injuries due to: –no restraint –improperly used restraint List patterns common to larger groups of fatally injured, such as: –Age/race/income –Location/time of incident –Misuse of restraint

6. FAR Tables Find data using: Pre-created Table Create Table in Query

7. FARS Pre-created Tables Inspect tables to view different data types

8. FARS Tables Created by Query If data is not in pre-created table, start a query to create a table

9. FARS Tables Created by Query Choose a year

10. Example 1: FARS Table Choose an option for data sets (ex: Option 1)

11. Example 1: FARS Table Choose two data checkboxes (ex: “Age” and “Restraint System”)

12. Example 1: FARS Table Narrow data results. Will show the two you chose, plus State will show as an option. (ex: “All” on all three)

13. Example 1: FARS Table Choose which data for row and column of newly created table. (ex: chose “Age” and “Restraint System” as row and column)

15. Example 1: Statistical Statements

16. Example 2: Formulate Problem Vehicles are not yielding to pedestrians at crosswalks Pedestrians departing bus stops are not crossing safely

17. Example 2: Determine Supporting Data Identify the number of fatal injuries at: –Crosswalks –Bus stops –Other locations List patterns common to larger groups of fatally injured, such as: –Age/race/income –Location/time of incident –Violations due to vehicle or pedestrian

18. Example 2: FARS Table

21. Example 2: Statistical Statements

22. Writing Statistical Statements Must be believable/come from reliable sources Example: 4 out of 5 dentists surveyed recommend X gum to their patients who chew gum. Who said that? Find the trends in data to focus resources for the most impact Persuasive language

23. Persuasive Words In Support OfIn Support Against Accurate Advantage Always/Never Best Certain Confident Convenient Definitely Effective Emphasize Expect Interesting Magnificent Most Most Important Popular Profitable Should Strongly Recommend Superb Superior Tremendous Truly Trustworthy Workable Worthwhile Aggravate Agony Atrocious Confusing Cruel Damaging Disadvantages Displeased Dreadful Harmful Harsh Horrible Inconsiderate Inferior Irritate Offend Ordeal Outrageousness Provoke Repulsive Severe Shameful Shocking Terrible Unreliable Unstable Source www.education.umd.edu

24. Statistical Statement Example 1 70.6% of fatalities reported were male Where did this data come from? How was this statistical percentage determined?

25. Statistical Statement Example 1 70.6% of fatalities reported were male Document the source (ex. FARS) Be prepared to show the math if asked 22,860 / 32,367 * 100 = 70.62749096301789

26. Expressing Statistical Statements A single set of data can be expressed different ways: Most fatalities are male. 2/3 of all fatalities are male. Fatalities are 2 times as likely to be male. Crashes fatalities are half as likely to be women Determine which way is most relevant to your problem (makes it sound reeaallyy bad)

27. Statistical Statement Example 2 4751 fatalities under 21 years of age in US 18,179 fatalities between ages 21 and 54 360+344+637+3410=4751 3,282+5,497+4,323+5,077=18,179

28. Find the Trend: Motorcycle Fatalities

29. Motorcycles involved in fatal crashes per 100M VMT

30. Trends Show Problems

31. Things to Avoid Let the data speak: do not misrepresent the data. Do not manipulate the data so that there is no way to recalculate a percentage Avoid using “average” and “you” Use “we and us” only when you have proper authority Ex: somebody call 911

32. Using Statistics in News

33. Other Data Sources Other sources contain crash, injury and fatality data: Florida Crash Facts Florida Crash Facts National Center for Statistics and Analysis (NCSA) National Center for Statistics and Analysis (NCSA)

34. Objectives Review You should now be able to: Identify data to best support a given problem Discuss various statements expressing data as a statistic Recognize a problem by analyzing data