Written Report.docx

de la Peña, Marjolaine L. Stat 125Soriano, Marie Lezith F. 3rd Machine Problem

ANALYZING THE BEHAVIOR OF UP DILIMAN STUDENTS IN SOCIAL NETWORKING SITES (SNS): A Written Report

A pilot study was conducted in UP Diliman with regard to the behavior of students in social networking sites. 276 students participated in the said study. The researchers were able to identify 10 factors which are related to the usage of SNS. In this report, only 5 of the 10 factors are considered. These are the Cloud Nine Effect, Functional Attributes, Freedom of Speech, Guerilla Marketing and Addiction Signals.

In this report, we summarized and analyzed the data using descriptives and hypothesis tests in SPSS with 5% level of significance. This report aims to accomplish three objectives. The first is to describe the characteristics of the students who responded to the survey using background checks. The second objective is to determine if there is a significant difference between the averages of factor scores between those who own a laptop and those who do not. The third and last objective is to determine if there is a significant difference between the averages of the five factors scores mentioned, among the five college clusters.

Before conducting statistical tests, the data was adjusted to homogenize the respondents. A subset of the respondents are newly composed of only those who are not beyond 22 years old, those who have an account either in Facebook and Twitter and those who belong to any college cluster. The respondents are now reduced to 265.

The respondents are composed of students from 15 to 22 years old, with 17 to 19 years old composing 22.3%, 25.3% and 21.1% respectively. They are those who entered UP from 2006 to 2012 with the bulk of the sample being on year 2010 to 2012. For the year levels, there are no large differences and are almost equally distributed. 228 or 86% of the respondents are single and the rest are not. The respondents are composed of 143 male students and 122 female students. 161 respondents live with their parents whereas 104 do not. Most of the students (53.2%) have an average daily allowance of 100 to 200 pesos. Lastly, for the academic standing, the respondents are mostly composed of those who belong to Cum Laude Standing (27.2%), Good But Not Honor Standing (36.6%) and Satisfactory Academic Standing (21.9%).

Respondents are also characterized through the possible contributions of academic behavior seen in studying for an upcoming exam, using SNS before an upcoming exam and visiting the library measured in number of hours in a week. Studying for an exam ranged from 0.50 to 24 hours. Before an upcoming exam, the students’ usage of SNS ranged from 0 to 25 hours in a week. Visiting the library has a mean with the value tagged as sometimes which is on the average of 1 to 5 or never to always. As for the behavioral factors, playing, going to parties, drinking/smoking, and retouching were considered. The respondents are on the average on having the habits of those mentioned. The means of the behavioral factors only range from rarely to sometimes.

There are only few students who own laptop which is only composes 10.2% of the total respondents, or more specifically, 238 of them own a laptop while only 27 do not. Independent-samples t test was used to test the differences between the average factor scores and of those who own a laptop or those who do not. The t test for the five factors tests the null hypothesis that the average factor scores of those who own a laptop and those who do not are equal (µ1 = µ2). For the alternative hypothesis, the averages of the factor scores of those who own a laptop and those who do not are not equal (µ1 <> µ2).

The means show that, on average, those who own a laptop appears to have altered by Cloud Nine Effect from about 0.022% to -0.026%, a change of 0.048%. The p-value is 0.713 > 0.05 and, therefore, the difference between the two means is not statistically significantly different from zero at the 5% level of significance. There is an estimated change of 0.048%. However, there is insufficient evidence (p = 0.713) to support the claim that those who own a laptop does change the mean of Cloud Nine Effect scores. We can therefore say that the factor for happiness is not associated to a student owning a laptop or not.

In Functional Attributes, a t-statistical value of 0.639 is computed with a p-value of 0.222. Since p-value (0.222) > 0.05, we can conclude that the mean scores of those who own a laptop is statistically larger than the mean scores of those who do not own a laptop. More formally, we do not reject the null hypothesis and therefore, there is no sufficient evidence to support the claim that there is a significant difference between the average scores for the Functional Attributes between those who own a laptop and those who do not. With these we can say that the usage of social networks on sharing photos, communicating, creating online groups, file sharing are not connected to owning a laptop. Moreover, using SNS practically cannot be predicted by a student owning a laptop or not.

For the Freedom of Speech, a t-statistical value of 0.930 is computed with the p-value of 0.652. Since p-value (0.652) > 0.05, we can conclude that the mean scores of those who own a laptop is statistically larger than the mean scores of those who do not own a laptop. More formally, we do not reject the null hypothesis and therefore, there is no sufficient evidence to support the claim that there is a significant difference between the average scores for the Freedom of Speech between those who own a laptop and those who do not.

For the Guerilla Marketing, a t-statistical value of –1.142 is computed with the p-value of 0.353. And since p-value (0.353) > 0.05, we can conclude that the mean scores of those who do not own a laptop is statistically larger than the mean of those who own a laptop. More formally, we do not reject the null hypothesis and therefore, there is no sufficient evidence to support the claim that there is a significant difference between the average scores for the Guerilla Marketing between those who own a laptop and those who do not.

For the Addiction Signals, a t-statistical value of 0.850 is computed with the p-value of 0.262. And since p-value (0.262) > 0.05, we can conclude that the mean scores of those who own a laptop is statistically larger than the mean of those who do not own a laptop. More formally, we do not reject the null hypothesis and therefore, there is no sufficient evidence to support the claim that there is a significant difference between the average scores for the Addiction Signals between those who own a laptop and those who do not.

Generally, given those interpretations on five different factors we can therefore conclude that there is no statistically significant difference between the averages of factor scores between those who own a laptop and those who do not own a laptop. It is also safe to say that the usage of SNS are not associated to owning a laptop. It is widely known that a laptop is not the only gadget that can be used for the access to social networking sites.

Looking into the distribution of students based on their field of studies, the respondents of the study are composed of students from different clusters- the Arts and Letters, Science and Technology, Management Economics, and Social Sciences and Law. 44.9% of them are from Science and Technology. Analysis of variance test was used to determine if there is a significant difference between the averages of the five factors scores mentioned, among the five college clusters. For the five factors, it tests the null hypothesis that the average factor scores among five college clusters are equal (µ1 = µ2 = µ3 = µ4 = µ5). For

the alternative hypothesis, the averages of the factor scores among five college clusters are not equal (µ1

<> µ2 <> µ3 <> µ4 <> µ5).

For the Cloud Nine Effect, the p-value is 0.485 > 0.05 level of significance. Therefore, there is no sufficient evidence to support the claim that there is a significant difference between the averages of Cloud Nine Effect among the college clusters. Moreover, the happiness factor does not differ within college clusters.

For the Functional Attributes, the p-value is 0.016 < 0.05 level of significance. Therefore, there is sufficient evidence to support the claim that there is a significant difference between the averages of Functional Attributes among the college clusters. This can be explained by the different focus and concentrations in different field of studies which can therefore be reflected by how they use SNS practically and considering the functional features.

For the Freedom of Speech, the p-value is 0.085 > 0.05 level of significance. Because of this,

there is no sufficient evidence to support the claim that there is a significant difference between the averages of Freedom of Speech among the college clusters. Expressing feelings in SNS is not associated to belonging to a specific college cluster.

For the Guerilla Marketing, the p-value is 0.004 < 0.05 level of significance. Because of this, we

say that there sufficient evidence to support the claim that there is a significant difference between the averages of Guerilla Marketing among the college clusters. The usage of social networking site for business and marketing differs among college clusters probably because there are fields that require or need knowledge in businesses online.

For the Addiction Signals, the p-value is 0.625 > 0.05 level of significance. there is no sufficient evidence to support the claim that there is a significant difference between the averages of Addiction Signals among the college clusters. Addiction to a social networking site is not merely seen and cannot be concluded to a specific college field.

Social networking sites are powerful and flexible when it comes to its features and its uses. The usage of social networking varies among students and more generally, other users. As seen in statistical results, the usage of SNS is not determined by owning a laptop or not. It becomes an unnecessary factor now considering the vast availability of gadgets which are handy and those which support the use of social networking sites. In addition, usage of SNS is not also statistically determined by the field of studies of students. As seen, those features that are used generally by users are not linked to a college field. Nonetheless, there are also features that can be connected to the field of studies and this can be explained by the academic activities needed for the course or field. The usage of SNS varies among different personalities and this can be further examined in the future.

APPENDIX1

SPS Data Set

APPENDIX 2

SPSS Output

Descriptives

[DataSet1] C:\Users\dmarj_000\Desktop\MP.sav

Descriptive Statistics

N Range Minimum Maximum Mean Std. Deviation Variance

Age 265 7.00 15.00 22.00 18.3019 1.58813 2.522

How much time (hours) do you

spend (in a week) on studying

for an upcoming exam?

265 23.50 .50 24.00 4.9151 3.34836 11.212

How much time (hours) do you

spend (in a week) on SNS

before an upcoming exam?

265 25.00 .00 25.00 3.0149 3.01941 9.117

How often do you visit the

library?

265 4.00 1.00 5.00 3.3774 1.10485 1.221

How often do you play sports or

exercise?

265 4.00 1.00 5.00 2.9811 1.04248 1.087

How often do you go to parties? 265 4.00 1.00 5.00 2.4943 .92981 .865

How often do you drink/smoke? 265 4.00 1.00 5.00 1.8226 1.06006 1.124

How often do you retouch/fix

yourself up?

265 4.00 1.00 5.00 2.8075 1.10985 1.232

Valid N (listwise) 265

DESCRIPTIVES VARIABLES=age study_exam sns_exam library active party vice vanity /STATISTICS=MEAN STDDEV VARIANCE RANGE MIN MAX.

Frequencies


Statistics

Sex Year of entry in UP Marital Status

(Single or Not)

College Cluster or

Field of Studies

Do you own a

laptop?

Do you live with

your parents?

Do you have a

Facebook

account?

Do you have a

Twitter account?

NValid 265 265 265 265 265 265 265 265

Missing 0 0 0 0 0 0 0 0

Mean .5396 2010.3925 .1396 2.3358 .8981 .6075 1.0000 .6151

Minimum .00 2006.00 .00 1.00 .00 .00 1.00 .00

Maximum 1.00 2012.00 1.00 4.00 1.00 1.00 1.00 1.00

DESCRIPTIVES VARIABLES=sex entry status Field withparents laptop facebook twitter allowance age gwa yrlvl /STATISTICS=MIN MAX.

Frequency Table

Sex

Frequency Percent Valid Percent Cumulative

Percent

Valid

Female 122 46.0 46.0 46.0

Male 143 54.0 54.0 100.0

Total 265 100.0 100.0

Year of entry in UP


Percent

Valid

2006.00 4 1.5 1.5 1.5

2007.00 9 3.4 3.4 4.9

2008.00 11 4.2 4.2 9.1

2009.00 39 14.7 14.7 23.8

2010.00 66 24.9 24.9 48.7

2011.00 64 24.2 24.2 72.8

2012.00 72 27.2 27.2 100.0

Total 265 100.0 100.0

Marital Status (Single or Not)


Percent

Valid

Single 228 86.0 86.0 86.0

Not Single 37 14.0 14.0 100.0

Total 265 100.0 100.0

College Cluster or Field of Studies


Percent

Valid

Arts and Letters 46 17.4 17.4 17.4

Science and Technology 119 44.9 44.9 62.3

Management and Economics 65 24.5 24.5 86.8

Social Sciences and Law 35 13.2 13.2 100.0

Total 265 100.0 100.0

Do you own a laptop?


Percent

Valid

No 27 10.2 10.2 10.2

Yes 238 89.8 89.8 100.0

Total 265 100.0 100.0

Do you live with your parents?


Percent

Valid

No 104 39.2 39.2 39.2

Yes 161 60.8 60.8 100.0

Total 265 100.0 100.0

Do you have a Facebook account?


Percent

Valid Yes 265 100.0 100.0 100.0

Do you have a Twitter account?


Percent

Valid No 102 38.5 38.5 38.5

Yes 163 61.5 61.5 100.0

Total 265 100.0 100.0

Average Daily Allowance


Percent

Valid

Below P100 50 18.9 18.9 18.9

P100-P200 141 53.2 53.2 72.1

P200-P300 45 17.0 17.0 89.1

Above P300 29 10.9 10.9 100.0

Total 265 100.0 100.0

Age


Percent

Valid

15.00 3 1.1 1.1 1.1

16.00 27 10.2 10.2 11.3

17.00 59 22.3 22.3 33.6

18.00 67 25.3 25.3 58.9

19.00 56 21.1 21.1 80.0

20.00 27 10.2 10.2 90.2

21.00 12 4.5 4.5 94.7

22.00 14 5.3 5.3 100.0

Total 265 100.0 100.0

Current GWA standing


Percent

Valid

Summa Cum Laude Standing 4 1.5 1.5 1.5

Magna Cum Laude Standing 29 10.9 10.9 12.5

Cum Laude Standing 72 27.2 27.2 39.6

Good But Not Honor Standing 97 36.6 36.6 76.2

Satisfactory Academic Standing 58 21.9 21.9 98.1

Poor Academic Standing 5 1.9 1.9 100.0

Total 265 100.0 100.0

Year Level


Percent

Valid

1.00 72 27.2 27.2 27.2

2.00 64 24.2 24.2 51.3

3.00 66 24.9 24.9 76.2

4.00 63 23.8 23.8 100.0

Total 265 100.0 100.0

FREQUENCIES VARIABLES=sex entry status Field laptop withparents facebook twitter allowance age gwa yrlvl /STATISTICS=RANGE MINIMUM MAXIMUM MEAN MEDIAN /ORDER=ANALYSIS.

T-TEST GROUPS=laptop(1 0) /MISSING=ANALYSIS /VARIABLES=cloudnine /CRITERIA=CI(.95).

T-Test


Group Statistics

Do you own a laptop? N Mean Std. Deviation Std. Error Mean

Cloud Nine EffectYes 238 .0220679 .93554917 .06064265

No 27 -.0264093 .90664737 .17448437

Independent Samples Test

Levene's Test for Equality of Variances t-test for Equality of Means

F Sig. t df Sig. (2-tailed) Mean Difference Std. Error

Difference

Cloud Nine EffectEqual variances assumed .135 .713 .256 263 .798 .04847718 .18941283

Equal variances not assumed .262 32.608 .795 .04847718 .18472229

T-TEST GROUPS=laptop(1 0) /MISSING=ANALYSIS /VARIABLES=functional /CRITERIA=CI(.95).

T-Test


Group Statistics


Functional AttributeYes 238 .0242670 .90845875 .05888663

No 27 -.0960576 1.08140881 .20811722




Difference

Functional AttributeEqual variances assumed 1.497 .222 .639 263 .523 .12032454 .18824780


T-TEST GROUPS=laptop(1 0) /MISSING=ANALYSIS /VARIABLES=freedom /CRITERIA=CI(.95).

T-Test


Group Statistics


Freedom of SpeechYes 238 .0169535 .89007902 .05769525

No 27 -.1503505 .84679217 .16296523




Difference

Freedom of SpeechEqual variances assumed .204 .652 .930 263 .353 .16730400 .17990130


T-TEST GROUPS=laptop(1 0) /MISSING=ANALYSIS /VARIABLES=guerilla /CRITERIA=CI(.95).

T-Test


Group Statistics


Guerilla MarketingYes 238 -.0315341 .84012136 .05445698

No 27 .1654185 .92900027 .17878619




Difference

Guerilla MarketingEqual variances assumed .867 .353 -1.142 263 .255 -.19695260 .17247457

Equal variances not assumed -1.054 31.019 .300 -.19695260 .18689586

T-TEST GROUPS=laptop(1 0) /MISSING=ANALYSIS /VARIABLES=addict /CRITERIA=CI(.95).

T-Test


Group Statistics


Addiction SignalsYes 238 .0221646 .86469895 .05605011

No 27 -.1293189 .98910648 .19035363




Difference

Addiction SignalsEqual variances assumed 1.265 .262 .850 263 .396 .15148357 .17825430


ONEWAY cloudnine BY Field /MISSING ANALYSIS.

Oneway[DataSet2] C:\Users\dmarj_000\Desktop\MP.sav

ANOVA

Cloud Nine Effect

Sum of Squares df Mean Square F Sig.

Between Groups 2.130 3 .710 .817 .485

Within Groups 226.734 261 .869

Total 228.864 264

ONEWAY functional BY Field /MISSING ANALYSIS.

Oneway


ANOVA

Functional Attribute


Between Groups 8.815 3 2.938 3.525 .016


Total 226.352 264

ONEWAY freedom BY Field /MISSING ANALYSIS.

Oneway


ANOVA

Freedom of Speech


Between Groups 5.187 3 1.729 2.235 .085


Total 207.083 264

ONEWAY guerilla BY Field /MISSING ANALYSIS.

Oneway[DataSet2] C:\Users\dmarj_000\Desktop\MP.sav

ANOVA

Guerilla Marketing


Between Groups 9.514 3 3.171 4.569 .004


Total 190.655 264

ONEWAY addict BY Field /MISSING ANALYSIS.

Oneway


ANOVA

Addiction Signals


Between Groups 1.359 3 .453 .586 .625


Total 203.199 264

DATASET ACTIVATE DataSet2.

SAVE OUTFILE='C:\Users\dmarj_000\Desktop\MP.sav' /COMPRESSED.

Written Report.docx

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