Texting and DrivingJoanna Curran And Brianna Baer

Texting and Driving •How many teenagers use their phones

while driving •Are there factors that affect if people use

their phones while driving•Is texting while driving actually as

widespread as the news makes it seem??

Distractions While Driving• By observing a national survey

of 900 teens around the country• Teenagers find these attributes

the most distracting for drivers:▫ Instant or text messaging while

driving - 37 percent ▫ [The teen driver's] emotional

state - 20 percent ▫ Having several friends in the

car - 19 percent ▫ Talking on a cell phone - 14

percent ▫ Eating or drinking - 7 percent ▫ Having a friend in the car - 5

percent ▫ Listening to music - 4 percent

Gathering our Data• We observed different surveys

given by Insurance companies on teens texting and driving

• We also conducted a survey of all the different attributes of the surveys we found▫ We sent the questions out in

Penn State Altoona’s and St. Joseph’s University student Facebook groups We collected our data in a

systematic random sample, and used the results of every third person that responded

We used 57 student’s results

Age Vs. Gender• We found that the majority

of the data we collected came from females▫ Females were also the

only two 19 years olds tested in our experiment

• There were more females than males in each aspect of the experiment

Gender

0

4

8

12

16

20

f

4

8

12

16

20

m

17 18 19 20 21Age

Collection 1 Histogram

Collection 1

RowSummary

Gender

m

Gender

f

Age35

17.57141

2217.6818

1

5717.614

1S1 = countS2 = meanS3 = columnproportion

Phone Use While Driving vs. Type of Phone

• The smart phones have higher results ▫ People that own a smart

phone use their cell phone more while driving

• Yet, more people who have regular phones do not use their cell phone while driving

ny

Type_of_Phone

5 10 15 20 25 30r

0 5 10 15 20 25 30s

Frequency of Phone_use_while_driving count

Collection 1 Bar Chart

Collection 1

RowSummary

Column Summary

Type_of_Phone

s

Type_of_Phone

r

n

y

Phone_use_while_driving

80.32

70.21875

170.68

250.78125

251

321

150.263158

420.736842

571

S1 = countS2 = columnproportion

Gender vs. What Activity Used Most on Phones

• We found that females most use their phones to make calls while they drive, consisting of 19 subjects

• The males and females have low results for iPod use while only 2 males and 3 females responded yes

• Males most favor texting with 12 subjects responding yes

• There were 4 subjects that did not apply for this test for they do not use their cell phone while driving

fm

what_activity

6 12 18c

0 6 12 18ipod

0 6 12 18t

0 6 12 18X

Frequency of Gender count

Collection 1 Bar Chart

Collection 1

RowSummary

Column Summary

Gender

m

Gender

f

c

ipod

t

X

what_activity

190.542857

60.272727

30.0857143

10.0454545

100.285714

120.545455

30.0857143

30.136364

351

221

250.438596

40.0701754

220.385965

60.105263

571

S1 = countS2 = columnProportion

Share Car vs. Pay for Own Insurance

• We found that a majority of our subjects do share a car with a parent/family member

• Yet, most of the respondents stated that they do not pay for their own car insurance

• Therefore, we performed a test to see who text while driving without having to worry about paying their car insurance

nx

y

share_car

5 10 15 20 25n

0 5 10 15 20 25y

Frequency of pay_for_own_insurance count

Collection 1 Bar Chart

Collection 1

RowSummary

Column Summary

share_car

y

share_car

n

n

x

y

pay_for_own_insurance

220.666667

150.625

10.030303

20.0833333

100.30303

70.291667

331

241

370.649123

30.0526316

170.298246

571

S1 = countS2 = columnproportion

Pay for Own Car Insurance vs. Cell Phone Use

• The majority of our subjects responded that they DO use their cell phone while they are driving, but they do not pay for their own car insurance

• Those who pay for their own car insurance are less likely to use their cell phone while they are on the road

ny

pay_for_own_insurance

10 20 30n

0 10 20 30x

0 10 20 30y

Frequency of Phone_use_while_driving count

Collection 1 Bar Chart

Collection 1

RowSummary

Column Summary

pay_for_own_insurancepay_for_own_insurance

x y

pay_for_own_insurance

n

n

y

Phone_use_while_driving

80.216216

31

40.235294

290.783784

00

130.764706

371

31

171

150.263158

420.736842

571

S1 = countS2 = columnProportion

Support Laws vs. Behavior Change• A large amount of our

subjects responded that they would not support new laws against cell phone use while driving▫ Although, these same

subjects say that they would change their behavior if they were put out

• A good amount of our subjects also responded that they would support these laws

• Almost all of our subjects stated that they would change their behavior if these laws were enforced

nx

y

behavior_change

4 8 12 16 20n

0 4 8 12 16 20X

0 4 8 12 16 20y

Frequency of support_laws count

Collection 1 Bar Chart

Collection 1

RowSummary

Column Summary

support_lawssupport_laws

x y

support_laws

n

n

X

y

behavior_change

190.826087

00

100.322581

00

00

20.0645161

40.173913

31

190.612903

231

31

311

290.508772

20.0350877

260.45614

571

S1 = countS2 = columnProportion

Analysis and Conclusions• Most teens use their phone in some way while driving

▫ The majority call, many text, and few use a music feature• People are more likely to use their phones in the

afternoon or evening• Most people would not change their behavior if laws

were put in place ▫ however most people support a law banning cell phone

use while driving

1-Proportion Z Interval• Conditions

▫ SRS▫ Np, nq >10 ▫ Pop>10n

▫ Assumed▫ 42,15>10▫ # of teens>540

Conditons met=> norm dist=> 1-prop z int

.73681.645.7368(1 .7368)

57=(.64091,8328)

We are 90% confident that the true proportion of people who use their phones while driving is between 64.091% and 83.28%.

1-Proportion Z TestConditons met=> norm dist=> 1-prop z test

z .7368 .8.8(.2057

P(p<-1.1921)=.1166=-1.1921

We fail to reject the claim because our p-value of .1166 is greater than alpha=.05

We have sufficient evidence that the true proportion of people that use their phones while driving is equal to 80%.

H0 : p .8HA : p .8

Chi-Square Goodness of Fit Test• Conditons

▫ Categorical data ▫ SRS▫ All exp counts>5

▫ Activity on phone is categorical

▫ Assumed▫ All exp counts>5

Conditons met=> chi-square dist=> chi-square GOF test

Chi-Square Goodness of Fit Test• Ho: Distribution of our data for activity on phone

matches the distribution of nationwide’s data • Ha: Distribution of our data for activity on phone

does not match the distribution of nationwide’s data

We reject the claim because our p-value of 2.504 x 10^-14 is less than alpha=.05

We have sufficient evidence that the distribution of our data for activity on phone does not match the distribution of nationwide’s data.

6366.62...14.7)14.74(

22.11)22.1122(

expexp)( 222

2

obs

Chi-Square Goodness of Fit Test

We reject the claim because our p-value of 2.504 x 10^-14 is less than alpha=.05

We have sufficient evidence that the distribution of our data for activity on phone does not match the distribution of nationwide’s data.

142 10504.26366.63 xP

Chi-Square Test for Indepence• Conditions

▫ Categorical Data▫ SRS▫ All exp cell counts>5

▫ Phone use and sharing a car are categorical data

▫ Assumed▫ All exp cell counts>5

Conditons met=> chi-square dist=> chi-square test for independence

Chi-Square Test for Independence • Ho: There is an association between cell

phone use and sharing a car• Ha: There is no association between cell

phone use and sharing a car

74202....579.23

)579.2325(421.18

)421.1817(expexp)( 222

2

obs

Chi-Square Test for Independence

•We fail to reject the claim because our p-value of .3891 is greater than alpha=.05

•We have sufficient evidence that there is an association between cell phone use and sharing a car.

3891.7402.2 xP

Chi-Square Test for Independence• Conditions

▫ Categorical Data▫ SRS▫ All exp cell counts>5

▫ Phone use and paying for insurance are categorical data

▫ Assumed▫ All exp cell counts>5

Conditons met=> chi-square dist=> chi-square test for independence

Chi-Square Test for Independence • Ho: There is an association between cell phone use and

paying for insurance• Ha: There is no association between cell phone use and

paying for insurance

4071....28

)2829(14

)1413(expexp)( 222

2

obs

Chi-Square Test for Independence

We fail to reject the claim because our p-value of .52341 is greater than alpha=.05

We have sufficient evidence that there is an association between cell phone use and paying for car insurance.

5234.4071.2 xP

Our Findings• 1-Prop Z Test

▫ Good test to perform, showed our data was not too far away from the national data

• Chi-Square GOF Test▫ Good test to perform▫ Showed a bias in our data collection (only having data

from teens)• Chi-Square Tests for Independence

▫ Good tests to perform▫ Proved a person is more likely to use their phone if they

do not have to share it with another family member▫ Proved a person is more likely to use their phone if they

do not have to pay for car insurance.

Bias/Error•Mostly females responded•Only teenagers (ages 17-19) had been

able to respond to the survey•Only students attending Saint Joe’s or

Penn State Altoona as freshman next year could respond

•Relied on voluntary response

Personal Opinions• Data

▫ Easy to collect data▫ People are more willing to participate in our survey

than we had expected▫ Surprised our data did not match the distribution of

nationwide’s data▫ Not surprised to find associations in our tests for

independence• Project

▫ Took a long time to put together all of the components (as there were many)

▫ Fun project to research