Methodology
Question:
Discuss About The Journal Applied Mathematics And Statistics?
In this section, we present the methodology as well as the procedures that were employed to ensure that study became a success. The section is categorised into the following subsections: 1) sample selection, 2) survey instrument, 3) data collection, 4) data analysis, and 5) limitations.
The population in this study was college students in Australia. Due time and financial constraint, a small sample size of 20 was set for the survey. Questionnaires were administered to the students where they were given to fill in as the researcher watches from a distance. Once they had filled, the researcher took and just numbered. Ethical considerations of the research were adhered to and the participants were told they were at liberty to stop the study whenever they felt they needed to.
Questionnaires were used to collect data for this study. A closed ended questionnaire was prepared by the researcher for the purpose of the study. A copy of the questionnaire has been attached in appendix A1.
Since the sample required for this study was small, the researcher conducted this study alone without involving any research assistant. The participants were given questionnaires to fill by themselves. The total time taken to fill the questionnaire was estimated to be less than 7 minutes.
Once all the questionnaires had been filled up, data was entered into excel spreadsheet for analysis purposes. Statistical tests such as Chi-Square and t-test were used to test the hypothesis of the study.
The main limitation of this study is the fact that a small sample size was used. The population validity of a small sample is very low as such making it difficult to make generalizations out of this survey (Pearl, 2015).
We started by looking at the basic demographic profiles of the participants in the study.
There were 9 males (45%), and 11 females (55%) students participating in this study, as illustrated in figure 1.
From the 20 respondents, the ages of the students ranged from 18 to 25 years old. As can be seen, majority (20%, n = 4) of the participants were aged 23 years old. 5% (n = 1) was aged 21 years old.
Table 1: Age of the students interviewed
Row Labels |
Count of Age |
Percent |
18 |
2 |
10% |
19 |
3 |
15% |
20 |
3 |
15% |
21 |
1 |
5% |
22 |
2 |
10% |
23 |
4 |
20% |
24 |
3 |
15% |
25 |
2 |
10% |
Grand Total |
20 |
100% |
From a total of 20 respondents, majority (80%, n = 16) were Whites while 15% (n = 3) were Asian and 5% (n = 1) were Blacks.
Sample Selection
Table 2: Frequency table for the participants’ race
Row Labels |
Count of Race |
Percent |
Asian |
3 |
15% |
Black |
1 |
5% |
White |
16 |
80% |
Grand Total |
20 |
Participants were asked whether they use social media, apparently all of the participants said to be using social. The next question was for the participants to state their most preferred social media. Majority of the participants said to prefer Facebook (45%, n = 9) followed by Instagram (40%, n = 8). Twitter had a favourite following of 15% (n = 3).
Table 3: Most preferred social media
Row Labels |
Count of Most preferred SM |
Percent |
|
9 |
45% |
|
8 |
40% |
|
3 |
15% |
Grand Total |
20 |
100% |
Respondents were asked whether a thought of abandoning social media has ever criss-crossed their mind. 20% (n = 4) said yes while majority (80%, n = 16) said. Of those who said yes, they mainly mentioned wastage of time in the social media platform as the reason as to why they have thought of leaving social media.
Table 4: Preferred shopping method
Row Labels |
Frequency |
Percent |
Yes |
4 |
20% |
No |
16 |
80% |
Grand Total |
20 |
100% |
Participants were asked to state how much time they spend on social media. On average, students said to spend 3.15 hours a day in the social media. The most frequent time was 2 hours while the median time spent in social media was found to be 3 hours a day. See table 5 below.
Table 5: Descriptive statistics
Hours spent in Social Media in a day |
|
Mean |
3.15 |
Standard Error |
0.385766496 |
Median |
3 |
Mode |
2 |
Standard Deviation |
1.725200217 |
Sample Variance |
2.976315789 |
Kurtosis |
-1.30425839 |
Skewness |
0.290248521 |
Range |
5 |
Minimum |
1 |
Maximum |
6 |
Sum |
63 |
Count |
20 |
We tested three hypothesis in this study. The first hypothesis test was performed on the sample data to test whether there is significant association between gender of the student and the most preferred social media. A Chi-square test of association was performed to check the association between the two variables (Bagdonavicius & Nikulin, 2011).
Table 6: Most Preferred Social Media * Gender Cross tabulation
Count |
||||
Gender |
Total |
|||
Male |
Female |
|||
Most Preferred Social Media |
|
6 |
3 |
9 |
|
2 |
6 |
8 |
|
|
1 |
2 |
3 |
|
Total |
9 |
11 |
20 |
Table 7: Chi-Square Tests
Value |
df |
Asymp. Sig. (2-sided) |
|
Pearson Chi-Square |
3.165a |
2 |
.205 |
Likelihood Ratio |
3.252 |
2 |
.197 |
N of Valid Cases |
20 |
||
a. 6 cells (100.0%) have expected count less than 5. The minimum expected count is 1.35. |
A chi-square test of independence was performed to examine the relation between gender and most preferred social media. The relation between these variables was insignificant, p > 0.05.
The second hypothesis test was conducted on the sample data to test whether the average amount of time spent on social media in a day varied between the males and the females.
Table 8: t-Test: Two-Sample Assuming Equal Variances
Female |
Male |
|
Mean |
4 |
2.111111 |
Variance |
2.4 |
1.861111 |
Observations |
11 |
9 |
Pooled Variance |
2.160494 |
|
Hypothesized Mean Difference |
0 |
|
df |
18 |
|
t Stat |
2.859121 |
|
P(T<=t) one-tail |
0.005213 |
|
t Critical one-tail |
1.734064 |
|
P(T<=t) two-tail |
0.010425 |
|
t Critical two-tail |
2.100922 |
An independent samples t-test was done to compare the mean amount of time spent on social media (David & Gunnink, 2007). Results showed that the males (M = 2.11, SD = 1.36, N = 9) had significant difference in terms of the mean amount of time spent on social media in a day when compared to the females (M = 4.00, SD = 1.55, N = 11), t (18) = 2.859, p < .05, two-tailed. The difference of 1.89 showed a significant difference. Essentially results showed the female participants on average spend more time on social media in any day as compared to the male participants.
Data Collection
The third and the last hypothesis sought to test whether there is significant difference in the amount of time spent on social media for the different types of social media. A one-way analysis of variance (ANOVA) was employed to test this.
Table 9: ANOVA Single Factor
SUMMARY |
||||
Groups |
Count |
Sum |
Average |
Variance |
|
9 |
25 |
2.777778 |
2.694444 |
|
8 |
22 |
2.75 |
2.5 |
|
3 |
16 |
5.333333 |
0.333333 |
Table 10: ANOVA
Source of Variation |
SS |
df |
MS |
F |
P-value |
F crit |
Between Groups |
16.82778 |
2 |
8.413889 |
3.600909 |
0.049672 |
3.591531 |
Within Groups |
39.72222 |
17 |
2.336601 |
|||
Total |
56.55 |
19 |
A one-way between subjects ANOVA was conducted to compare the effect of social media type on amount time spent in the social media. There was a significant effect of type of preferred social media on amount of time spent at the p < .05 level for the three conditions [F(2, 17) = 3.60, p = 0.0497]. Post hoc comparisons using the Tukey HSD test indicated that the mean amount of time spent on Twitter (M = 5.33, SD = 0.58) was significantly different than the Facebook (M = 2.78, SD = 1.64) and Instagram (M = 2.75, SD = 1.58). Specifically, our results suggest that twitter users spend longer time as compared to either Facebook or Instagram users.
Conclusion
In this study, we sought to understand the social media usage among college students. 20 students took part in the survey and ended up responding to the questionnaires they were given. Results showed that most preferred social media platform was Facebook, followed by Instagram and last was Twitter. In regard to whether there was association between gender and most preferred social media platform, it was noted that there was no significant association between the two variables. However, we noted that there was significant evidence that the female students spend more time on social media as compared to the male students.
The research described above focussed more on understanding the patterns in the social media usage among the college and specifically looking at how the time spent on social media compare between the male students and the female students. Overage, the students were found to spend about 3.15 hours on social media. The research however did not find out when exactly the students use the social media. It would be necessary to advise the students not to mix their class work with social media as this might have negative impact on their studies. The students should use social media when they are free and not when the classes are going on. Future research should focus on understanding the impact of social media use among the college students on their academic performance.
References
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