By: Jackie, Molly & Franny

Hey

What’s up?What’s your Favorite Color?

TEXT REACTION

History

First text message sent in 1989 Edward Lantz Number read upside down

Not popular in 1990’s For hearing impaired

Increase in 2000 As addictive as cigarette smoking ?

What We Did

Text a random sample of 90 people and recorded their reaction to the text

We sent a text asking “ What is your favorite color? This is Franny”

Taking note of the variables : gender, age, time taken to respond, response to the question

Categorized response as following: confusion, answered, no response, other

Our goal was to find out if the way people responded would be different based on their age and gender and on the time of the day we sent the text.

How We Gathered the Data

Generated a list of random numbers on our calculator and use the number to contact the corresponding person in our contact list.

Used only one person’s cell phone to text from to reduce bias

We used numbers from each of our cell phones and each of our parents

We sent out a mass text and recorded how long it takes each person to respond (if it takes over a day we counted it as no response)

How We Gathered the Data (con’t)

We recorded the time of the day we sent the message : morning, afternoon, evening

We recorded the gender and age of the individual

Considered anyone under the age of 35 young; and over 35 as older

Chi-Square Homogeneity Test : Response vs. Age

Ho: The ages are the same throughout the different responses.

Ha: The ages are not the same throughout the different responses.

Conditions:

1) Categorical data 1) chart shows it is categorical

2) SRS 2) we took an SRS

3) Cell counts ≥ 5 3) All expected values ≥ 5

Conditions met- X²-distribution-X² test homogeneity

We fail to reject the Ho because the p-value .41 is greater than or equal to alpha = .05

We have sufficient evidence that the ages are distributed the same in each response.

exp

exp)( 22 obsx

13

)1315( 212

)1214( 2 898.2

41.)3898.2( 2 dfxp

Confusion Answer Other No Response

Young 15 14 7 9

Old 10 10 11 14

5%

15%

25%

35%

45%

55%

65%

75%

85%

95%

Response vs. Age

People

Chi-Square Independence Test :Gender vs. Response

Ho: There is no association between gender and response.

Ha: There is an association between gender and response.

Conditions

1) Categorical 1) Chart shows

2) SRS 2) We took an SRS

3) Cell count ≥ 5 3) expected cell counts all ≥ 5

Conditions met- X²-distribution-X² test independence

We fail to reject the Ho because p-value .77 is greater than alpha = .05.

We have sufficient evidence that there is no association between gender and type of response.

exp

exp)( 22 obsx

7.14

)7.1413( 23.11

)3.1113( 2 145.1

77.)3145.1( 2 dfxp

Answered

Confusion

Other

No Response

1 3 5 7 9 11 13 15Answered Confusion Other No Response

Male 14 12 5 9

Female 15 13 11 11

Response vs Gender

Answered

Confused

confused answered

Chi-Square Homogeneity Test :Response vs. Daytime

Ho: There is no association between response and daytime.

Ha: There is an association between response and daytime.

Conditions

1) Categorical data 1) chart shows

2) SRS 2) we took an SRS

3) Cell counts ≥ 5 3) all expected values ≥5

Conditions met- X²-distribution-X² test independence

We fail to reject the Ho because the p-value .56 is greater than alpha .05.

We have sufficient evidence that there is no association between response and daytime.

exp

exp)( 22 obsx

4.8

)4.810( 28

)87( 2 845.4

56.)6845.4( 2 dfxp

Confusion Answer Other No Response0

2

4

6

8

10

12

Time of Day and Response

MorningAfternoonNight

Time of Day

# o

f R

esponses

Bar Graph : Difference in # of people in each gender texted

Females: 56%Males: 44%

Bar Graph: Frequency of sex and age group

Females: Young- 48%Old- 52%

Males:Young-52.5%Old- 47.5%

Pie Chart: Distribution of responses of our sample

Confusion30%

Answered27%

Other19%

No Re-

sponse24%

Responses

Histogram: Display the time taken to respond to the text

Shape : UnimodalCenter: 147Spread: (2,298)

Bar Graph: Frequency of Responses at different parts of the day

Sources of Error/ Bias

We only have peoples’ numbers from ourselves and family

Don’t have all ages Texts might not go through People may not have their phones on

them People may not have texting

Conclusion/Personal Opinions We found that the response we got from

the people we texted was not dependent on time of day, age, or gender.

We did could not create a sufficient conclusion based on the data we collected.

It was boring waiting for people to respond It was awkward texting our parent’s friends We’re mad we didn’t come up with any

conclusions

Application to Population

Most people will respond to a random text message with a confused response such as “what?” or “huh?” or “why?”

People normally do not get random texts messages asking them “what’s there favorite color?”

Usually people text their friends or family

Using this example to conclude how people respond to text messages is not very adequate