Effect of Phone Type on Texting Frequency

Effect of Phone Type on Texting FrequencyTexting and rambling Phones among Fourth Year High domesticate Students in Saint Augustines SchoolB eacho stinkpotag, Brian EmilDungan, DonElliseFrancisco, Ralph VincentJacinto, Arvin JhayJavillionar, Kevin JaysonLaplana, Clifford SeanLite, GwynetteManzano, AixelNicolas, RinalynTacho, Mariella Stephanie LyneAbstractThis reputation was concluded to give an answer to the line if there is re everyy a epochal offspring of the causaof wide awake call offs to the frequency of texting. The researchers distributed 24 copies of questionnaire to the Junior and Senior students of Saint Augustines School, 2014-2015, to know if how many generation do they text daily using the type of meandering(a) knells that they stick. The Chi-Squ atomic subprogram 18 Test of In count onence was used to foot race the nonentity hypothesis. The researchers accepted the nonentity hypothesis since the P- take to be was more(prenominal) than the significat ion aim 0.05. Thus, it was concluded that the frequency of texting is non dependent on the type of wandering headphone.IntroductionMobile Phones atomic number 18 capacious for talking to someone without seeing his/her face. But theyre also great for messaging especially text messaging, to get in touch with our love ones and even some strangers without having a phone call which really requires cost.Often, we blink our uns confuse phones simply because they are smartphones and were manufactured by some of the renowned companies in the field of gadgets. We care less the phones that are locally-made and classical. Some generation, we are cordial of using the popular-branded smartphones because they are being advertised in the television and we have ont 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 electric cell phone companies utter that their produc ts are better than their competitors 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 some specific reason is that, we text more when using them than when using the old-branded and conventionality mobile phones.Is there really a relationship amidst texting and the type of mobile phone?Teenagers from the wealthier mansion and who own the brands of the top five mobile phone manufacturer smart phones use text message somewhat 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 betwixt texting and the type of mobile phone.This study did non 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 course students of Saint Augustines School, year 2014-2015, were the ones who were interviewed.Mobile PhonesSmartphonesSmartphone, refers to mobile phone which works like personal computers, has an freelance operating system. Users can install software and games provided by the third political party service providers, in order to extend the function of the mobile phone. And it can connect to mobile Internet through mobile communication interlock followed (Kumar, March 2012).TextingFrequencyThe volume of texting among teens has risen from 50 texts a daylight 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 textingThe 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. S ome 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.MethodologyParticipantsThe 243 out of 276 Junior and Senior students of Saint Augustines School (SAS) who have mobile phones who answered the questionnaire, computer with access to lucre 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.ProcedureThe 24 copies of questionnaire were distributed to every pillar of each classroom of the Juniors and Seniors last November 24, 2014.Through the questionnaire, the rese archers asked for the total number of the students who have smartphones and those who have tied(p) 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 24 table but later simplified to a 22 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 gift the solution to the problem less complicated.Data AnalysisA chi-square test of independence was performed to test the null hypothesis of no association between type of mobile phone and frequency of texting.ResultsThe P-value, 0.25, which was more than the significance level 0.05 provided a very strong evidence that the frequency of texting doesnt depend on the type of mobile phone. Thus, the researchers accepted the null hypothesis and it was kosher to conclude that the type of mobile phone, smartphone and regular phone, has no significant effect on the frequency of texting.DiscussionsAll the textual data were based on online articles. They were borrowed, read, analyzed, and summarized. The quantitative data, which were gathered through a questionnaire, were summed up in a 22 table for a more concise and apprehensible look. However, they were primarily summarized in a 24 table but to make it easier and express 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 twain 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 stoppage 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 rounde d off to the near 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.AppendicesRaw Data*Students who have mobile phone 243*Students who did not answer 33*Total population 276B. Statistical ComputationsUsing 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.Degrees of FreedomDF = (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) =1Expected FrequenciesEr,c= (nr* nc) / nwhere Er,cis the expected frequency count for levelrof multivariate A and levelcof varying 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) / nE1,1=( 182*91)/243= 68.16 E1,2=( 182*152)/243=113.84E2,1=( 61*91)/243=22.84 E2,2 =( 61*152)/243=38.16Test Statisitics2= (Or,c Er,c)2/ Er,cwhere 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.2= (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=0.51P-valueUsing the Chi-Square Distribution TableThe first higher value than the Test Statistics, going to the right, row of 1 as the DF, was 1.32, so looking at up to its P-value in the uppermost cell of its column was equal 0.25.C. QuestionnaireTo all the Juniors and Seniors,This questionnaire is very much needed for the completion of our 3rd Grading investigator y project. We ask for your active participation and honesty in answering the given(p) questions. Thank youYours Truly,Group 2 of IV-2Year and SectionHow many are you in your classroom?Per column1. 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.)Students with regular phone (phone intended for messaging and calling, w/o access to internet and do not consist of downloadable applications.)ReferencesCentral Intelligence Agency(2011).The worldfactbook. Retrieved Sept., 14, 2014, fromhttps//www.cia.gov/library/publications/the-world-factbook/index.html contract Institute of Personnel and Development.Pestle analysis. 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