Using FARS Queries For Concept Papers

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

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

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

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

FAR Tables

Find data using:

Pre-created Table

Create Table in Query

FARS Pre-created Tables

Inspect tables to view different data types

FARS Tables Created by Query

If data is not in pre-created table, start a query to create a table

FARS Tables Created by Query

Choose a year

Example 1: FARS Table

Choose an option for data sets (ex: Option 1)

Example 1: FARS Table

Choose two data checkboxes (ex: “Age” and “Restraint System”)

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

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

Example 1: Statistical Statements

Example 2: Formulate Problem

Vehicles are not yielding to pedestrians at crosswalks

Pedestrians departing bus stops are not crossing safely

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

Example 2: FARS Table

Example 2: FARS Table

Example 2: Statistical Statements

Writing Statistical StatementsMust 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

Persuasive Words   

In Support Of In Support Against

AccurateAdvantage

Always/NeverBest

CertainConfident

ConvenientDefinitelyEffective

EmphasizeExpect

InterestingMagnificent

Most Most Important

PopularProfitable

ShouldStrongly Recommend

SuperbSuperior

TremendousTruly

TrustworthyWorkable

Worthwhile

AggravateAgony

AtrociousConfusing

CruelDamaging

DisadvantagesDispleased

DreadfulHarmfulHarsh

HorribleInconsiderate

InferiorIrritateOffendOrdeal

OutrageousnessProvoke

RepulsiveSevere

ShamefulShockingTerrible

UnreliableUnstable

Source www.education.umd.edu

Statistical Statement Example 1

70.6% of fatalities reported were male

Where did this data come from?

How was this statistical percentage determined?

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

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)

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

Find the Trend: Motorcycle Fatalities

Find the Trend: Motorcycle Fatalities

Motorcycles involved in fatal crashes per 100M VMT

1994

1996

1998

2000

2002

2004

2006

2008

2010

05

101520253035404550

Motorcycle FatalitiesColumn2Column3

Trends Show Problems

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

Using Statistics in News

Other Data Sources

Other sources contain crash, injury and fatality data:

Florida Crash Facts

National Center for Statistics and Analysis (NCSA)

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