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Effect of Phone Type on Texting Frequency

Effect of Phone Type on Texting Frequency

Texting and Mobile Phones among Fourth Year High School Students in Saint Augustine’s School

  • Ballocanag, Brian Emil
  • Dungan, DonEllise
  • Francisco, Ralph Vincent
  • Jacinto, Arvin Jhay
  • Javillionar, Kevin Jayson
  • Laplana, Clifford Sean
  • Lite, Gwynette
  • Manzano, Aixel
  • Nicolas, Rinalyn
  • Tacho, Mariella Stephanie Lyne

 

Abstract

This study was concluded to give an answer to the problem if there is really a significant effect of the typeof mobile phones to the frequency of texting. The researchers distributed 24 copies of questionnaire to the Junior and Senior students of Saint Augustine’s School, 2014-2015, to know if how many times do they text daily using the type of mobile phones that they have. The Chi-Square Test of Independence was used to test the null hypothesis. The researchers accepted the null hypothesis since the P-value was more than the significance level 0.05. Thus, it was concluded that the frequency of texting is not dependent on the type of mobile phone.

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Introduction

Mobile Phones are great for talking to someone without seeing his/her face. But they’re also great for messaging — especially text messaging, to get in touch with our loved ones and even some strangers without having a phone call which really requires cost.

Often, we flaunt our mobile phones simply because they are smartphones and were manufactured by some of the famous companies in the field of gadgets. We care less the phones that are locally-made and classical. Sometimes, we are fond of using the popular-branded smartphones because they are being advertised in the television and we don’t want to be left behind by the high-tech and industrialized world.

At present, we are attracted to expensive and high-class brand of mobile phones. We often believe in some cell phone companies telling that their products are better than their competitor’s products. We are then persuaded and lured by them that we begin to patronize and buy their mobile phones without so much hesitation. And our biggest and most specific reason is that, we text more when using them than when using the old-branded and normal mobile phones.

Is there really a relationship between texting and the type of mobile phone?

Teenagers from the wealthier household and who own the brands of the top five mobile phone manufacturer smart phones use text message slightly more frequent than teens who own the low-end standard mobile phones and from lower income household (PewInternet, 2009).

The objective of this study was to determine if there is a relationship between texting and the type of mobile phone.

This study did not include the originality of the mobile phones that the interviewees have. It did not matter if they were imitated or not.

Those Grade-9 and 4th year students of Saint Augustine’s School, year 2014-2015, were the ones who were interviewed.

Mobile Phones

Smartphones

Smartphone, refers to mobile phone which works like personal computers, has an independent operating system. Users can install software and games provided by the third party service providers, in order to extend the function of the mobile phone. And it can connect to mobile Internet through mobile communication network followed (Kumar, March 2012).

Texting

Frequency

The volume of texting among teens has risen from 50 texts a day in 2009 to 60 texts for the median teen text user. Older teens, boys, and blacks are leading the increase. Texting is the dominant daily mode of communication between teens and all those with whom they communicate (Lenhart, 2012).

Teen texting

The Pew Internet survey shows that the heaviest texters are also the heaviest talkers. The heaviest texters (those who exchange more than 100 texts a day) are much more likely than lighter texters to say that they talk on their cell phone daily. Some 69% of heavy texters talk daily on their cell phones, compared with 46% of medium texters (those exchanging 21-100 texts a day) and 43% of light texters (those exchanging 0-20 texts a day) (Lenhart, 2012).

The null hypothesis was there is no significant effect of the type of mobile phone on the frequency of texting.

The alternative hypothesis was there is a significant effect of the type of mobile phone on the frequency of texting.

Methodology

Participants

The 243 out of 276 Junior and Senior students of Saint Augustine’s School (SAS) who have mobile phones who answered the questionnaire, computer with access to internet where the articles, journals and data regarding the study were taken, 24 copies of questionnaire and the facts about texting and mobile phones were the participants of this investigatory project.

Procedure

The 24 copies of questionnaire were distributed to every column of each classroom of the Juniors and Seniors last November 24, 2014.Through the questionnaire, the researchers asked for the total number of the students who have smartphones and those who have regular phones. They were questioned if how many times do they text daily- 1-5 times,6-10 times,11-15 times or 15-20 times. The result of the survey was summarized in a 2×4 table but later simplified to a 2×2 table because those who text 1-5 and 6-10 times a day were taken as one as well as those who text 11-15 and 16-20 times in order to make the solution to the problem less complicated.

Data Analysis

A chi-square test of independence was performed to test the null hypothesis of no association between type of mobile phone and frequency of texting.

Results

The P-value, 0.25, which was more than the significance level 0.05 provided a very strong evidence that the frequency of texting doesn’t depend on the type of mobile phone. Thus, the researchers accepted the null hypothesis and it was proper to conclude that the type of mobile phone, smartphone and regular phone, has no significant effect on the frequency of texting.

Discussions

All the textual data were based on online articles. They were borrowed, read, analyzed, and summarized. The numerical data, which were gathered through a questionnaire, were summed up in a 2×2 table for a more concise and apprehensible look. However, they were originally summarized in a 2×4 table but to make it easier and faster to arrive to the answer, the researchers have chosen to just take those who text 1-5 and 6-10 times a day as one and the who text 11-15 and 16-20 times both in the row of smartphone and regular phone. There were approximately 12 % of the respondents who did not answer the questionnaire both intentionally and unintentionally but it did not stop the researchers from proceeding to the next step.

Using the numerical data, and the Chi-Square Test of Independence as the statistical tool, the researchers computed for the degrees of freedom (DF), expected frequencies (Er,c) and test statistics (X2) . Er,c and X2 were rounded off to the nearest hundredths.

The researchers used the Chi-Square Distribution table to find for the P-value which was found out to be 0.25. The null hypothesis, saying that the type of mobile phone has no significant effect on the frequency of texting, was accepted because the P-value was far higher than the significance level 0.05.

Appendices

  1. Raw Data
Mobile Phone Type Number of student texters
1-10 times 11-20 times Row Total
Smartphone 67 115 182
Regular phone 24 37 61
Column Total 91 152 243

*Students who have mobile phone: 243

*Students who did not answer: 33

*Total population: 276

B. Statistical Computations

Using the numerical data, the researchers computed for the degrees of freedom, expected frequencies, test statistic, and approximate P-value associated with the test statistic and degrees of freedom.

  1. Degrees of Freedom

DF = (r – 1) * (c – 1)

where r is the number of levels for one categorical variable, and c is the number of levels for the other categorical variable.

DF = (r – 1) * (c – 1)=(2-1)*(2-1) =1

  1. Expected Frequencies

Er,c= (nr* nc) / n

where Er,cis the expected frequency count for levelrof Variable A and levelcof Variable B, nris the total number of sample observations at level r of Variable A, ncis the total number of sample observations at levelcof Variable B, and n is the total sample size.

Er,c= (nr* nc) / n

E1,1=( 182*91)/243= 68.16 E1,2=( 182*152)/243=113.84

E2,1=( 61*91)/243=22.84 E2,2 =( 61*152)/243=38.16

  1. Test Statisitics

Χ2= Σ [ (Or,c– Er,c)2/ Er,c]

where Or,cis the observed frequency count at levelrof Variable A and levelcof Variable B, and Er,cis the expected frequency count at levelrof Variable A and levelcof Variable B.

Χ2= Σ [ (Or,c– Er,c)2/ Er,c]

=(67-68.16)2/68.16+(115-113.84)2/113.84+(24-22.84)2/22.84+(37-38.16)2/38.16

=0.10+0.01+0.06+0.34

=0.51

  1. P-value

Using the Chi-Square Distribution Table

E:chi-squared-table-neee.png

The first higher value than the Test Statistics, going to the right, row of 1 as the DF, was 1.32, so looking up to its P-value in the uppermost cell of its column was equal 0.25.

C. Questionnaire

To all the Juniors and Seniors,

This questionnaire is very much needed for the completion of our 3rd Grading Investigatory project. We ask for your active participation and honesty in answering the given questions. Thank you!

Yours Truly,

Group 2 of IV-2

Year and Section:

How many are you in your classroom?

Per column:

1. How many are you in your column?

2. Who are the students who own smartphones and non-smartphones?

For number 2, follow the format below.

Students with smartphones ( phones with access to internet, camera, etc.)

Name 1-5 times 6-10 times 11-15 times 16-20 times
Ex. Marielle
Name 1-5 times 6-10 times 11-15 times 16-20 times
Ex. Marielle

Students with regular phone (phone intended for messaging and calling, w/o access to internet and do not consist of downloadable applications.)

References

Central Intelligence Agency(2011).The worldfactbook. Retrieved Sept., 14, 2014, from https://www.cia.gov/library/publications/the-world-factbook/index.html

Chartered Institute of Personnel and Development. Pestle analysis. Retrieved from http://www.cipd.co.uk/hr-resources/factsheets/pestle-analysis.aspx

Kumar, Dinesh(March 2012). An empirical study of brand preference of mobile phones among college and university students.

Lenhart, Amanda (2012). Teens, smartphones &texting.Retrieved from http://www.pewinternet.org/2012/03/19/teens-smartphones-texting/

Mika Husso (2011). Analysis of competition in the mobile phone markets of the United States and Europehttp://epub.lib.aalto/ethesis/pdf/12638/hse_ethesis_12638.pdf.fi/en

Nurullah, A.S. (2009). The cell phone as an agent of social change. Retrieved from http://ualberta.academia.edu/AbuSadatNurullah/Papers/109273/The_Cell_Phone_as_an_Agent_of_Social_Change

Sharma, S., Gopal, V., Sharama, R., & Sharma, N.,(Eds.).(2012). Study on mobile phones brand pattern among the college students of Delhi-NCR.Retrieved from http://www.slideshare.net/monikakumari1971/a-study-on-mobile-phones-brand switching-pattern-among-the-college-students-of-delhincr-33612332631pb

The Carphone Warehouse (2006). The mobile life youth report 2006: The impact of the mobile phone on the lives of young people.Retrieved fromhttp://www.mobilelife2006.co. uk/

 



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