By: Jackie, Molly & Franny Hey What’s up? What’s your Favorite Color? TEXT REACTION.
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Transcript of By: Jackie, Molly & Franny Hey What’s up? What’s your Favorite Color? TEXT REACTION.
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