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Social Media Impact on Students Relationships Report


Problem statement

Communication is vital in every environment such as business, work, family, or social life. Over the years, there has been significant advancement in the communication channels. This has improved the ability to communicate across the world. In the recent years, different media have been used to pass information, including social media. The main concern is whether social media has improved communication in the society today or whether it has pushed the people to be anti-social. The recent trend and studies indicate that many relationships such as kinship, dependence, alliances at work, home, and school among other places, are breaking up. Could the social media be the cause? Actually, most research studies on social media have examined its impact on relationships. However, none of the studies have narrowed down the analysis to examining its impact on relationship within a university set up. This research gap forms the rationale of this study. Thus, the reason for proposing to conduct this study.

Purpose of the report

The purpose of the proposed study is to find out the role of social media on relationships among the students in my campus.

Research Objectives

  1. To determine if social media has a negative effect on relationships
  2. To establish the frequency of social media contact

Variables

The key variables will be the number of hours spent on social media, the effectiveness of social media on relationships, and the frequency of quarrels. However, other variables will also be included in the analysis.

Methodology

This proposed study will be conducted by carrying out a survey. The information will be collected through the use of standardized procedures so that every participant is asked the same questions in a similar way. The target population consists of students in the campus. The campus has about 1500 students. A random sampling technique will be used to generate the sample (Zikmund, Babin, Carr, and Griffin 56). The study will target students in major meeting points such as cafeterias, classes, and libraries among others. The sample size will be 10% of the entire population, that is, 150 students. From the sample of 150, only 111 students responded.

The quantitative approach is the most appropriate design in situations where the objective is to cover a large number of cases. The objective is to cover a sample which is a representative of the larger population. A questionnaire will be used as a data collection instrument (Kothari 76). The questionnaire is presented in the appendices.

Statistical tests

In this case, both descriptive and inferential statistics will be used to analyze the data. The descriptive statistics that will be used are mean, variance, standard deviation, kurtosis, and skewness. The descriptive statistics are important because they will aid in summarizing the data in a meaningful way (Madura 87). For example, they can give information on a pattern that may emerge from the data. In the case of inferential statistics, a correlation analysis will be used to determine the relationship between various variables. Also, a regression analysis will be used to establish if the number of hours is a significant determinant of the effectiveness of social media on relationships (Field 57).

Data analysis

Descriptive statistics

The output in the appendix shows that the average age of respondents was 26 years with a standard deviation of 4. Further, the average number of hours the respondents spend on social media was 14.4. The number of hours had a high standard deviation of 8. Further, the mean shows that the effectiveness of social media in general communication and in relationships was average. Further, the statistics show that the use of social media has a low impact on depression, reduced socialization, and quarrels. The value of skewness and kurtosis are more than zero for all the variables. This implies that they do not follow a normal distribution (Verbeek 41).

Hypothesis

  • H0: There is no relationship between the hours spent on social media and effectiveness of social media on relationships and quarrels.
  • H1: There is a relationship between the hours spent on social media and effectiveness of social media on relationships and quarrels.

Justification

In this case, the correlation coefficient will be used to test the hypothesis. The statistical technique measures the degree of linear association between variables (Wang 17).

Results and interpretation

The results are presented in the appendices. The results show that there is a weak positive association between the number of hours spent on social media and effectiveness of social media on the relationship. Also, there is a weak negative association between the number of hours spent on social media and quarrels (Berk 24).

Regression analysis

Regression analysis will be used to model a linear relationship between the two variables. In this case, the dependent variable will be the effectiveness of social media on relationships while the independent variable will be the number of hours spent on social media. The regression will take the form Y = a + bX where Y is the effectiveness of social media on relationships while X is the number of hours spent on social media.

Results and interpretation

The resulting regression equation is Y = 2.6318 + 0.0011X. The coefficient of 0.0011 implies that if an additional hour is spent on social media, then the relationship will be most effective from 0.011. The R-square is 0.0000928. This is an indication of a weak regression model (Greene 72).

Test of significance

A two tailed t-test will be used to test the significance of the explanatory variable. The test will be carried out at 5% level of significance. The hypothesis is stated below.

  • Null hypothesis: Ho: Xi = 0
  • Alternative hypothesis: Ho: Xi ≠ 0

The null hypothesis implies that the variable is not a significant determinant of the explained relationship. The null hypothesis will be rejected if the value of t-calculated is greater than the value of t-tabulated or if the p-value is less than α=0.05 (Vinod 49). The t-statistics for the number of hours is 0.10058, while the p-value is 0.92006. Since the p-value is more than α=0.05, the null hypothesis will not be rejected. Again, there is no sufficient data to draw a conclusion that the number of hours spent on social media is not a significant determinant of the effectiveness of social media on relationships (Baltagi 10).

Summary

The analysis above shows that there is a weak positive association between the number of hours spent on social media and effectiveness of social media on relationships and a weak negative association between number of hours spent on social media and quarrels. Also, the number of hours spent on social media is not a significant determinant of the effectiveness of social media on relationships. Thus, there is a slight possibility that the social media has a negative impact on relationships.

Works Cited

Baltagi, Badi. Econometrics, New York: Springer Publisher, 2011. Print.

Berk, Richard. Regression Analysis: A Constructive Critique, New York, USA: SAGE Publishers, 2004. Print.

Field, Andy. Discovering Statistics Using IBM SPSS Statistics, London: SAGE Publication, 2009. Print.

Greene, William. Econometric Analysis, NJ, USA: Pearson Education, 2011. Print.

Kothari, Jaipur. Research Methodology: Methods and Techniques, New Delhi: New Age International (P) Limited Publishers, 2004. Print.

Madura, Jeff. International Financial Management, USA: Cengage Learning, 2014. Print.

Verbeek, Marno. A Guide to Modern Econometrics, England: John Wiley & Sons, 2008. Print.

Vinod, Hrishikesh. Hands on Intermediate Econometrics Using R: Templates for Extending Dozens of Practical Examples, New Jersey: World Scientific Publishers, 2008. Print.

Wang, Jue. Business Intelligence in Economic Forecasting: Technologies and Techniques, USA: IGI Global, 2010. Print.

Zikmund, William, Barry Babin, Jon Carr, and Mitch Griffin. Business Research Methods, USA: Cengage Learning, 2012. Print.

Appendices

Appendix 1

SECTION ONE

Please tick where appropriate in the brackets provided and/or gives details as may be requested.

Personal Details

Sex

  • Male
  • Female

What is your age bracket?

  • 19 – 23
  • 29 – 33
  • 24 – 28
  • 34 and above

What major are you pursuing? ……………………………………………………………

How long have you been a student at the institution?

  • Less than a year
  • 2 – 4 Years
  • Above four years

SECTION TWO

Main Questions

What type of social media network do you frequently use?

  • Whats app
  • Twitter
  • Face book
  • Instagram

Why do you mostly prefer the above network?

  • Cost
  • Speed
  • Ratings
  • Features

Where do you rank the effectiveness of social media?

  • Very high
  • High
  • Low
  • Ineffective

How effective is social media in your relationship?

  • Very high
  • Low
  • High
  • Ineffective

Has social media ever made you feel anti-social at some point?

  • Yes
  • No
  • Not sure

How depressing is it when you cannot access the above media networks?

  • Highly depressing
  • Not depressing
  • Slightly depressing
  • Not so sure

Have you ever had a quarrel with your partner as a result of social media?

  • Yes
  • No

If yes, did you stop using the social media?

  • Yes
  • No

What action did you take to ensure that you avoid such quarrels in future?

  • Nothing
  • Stopped using social media
  • Limited/ reduced use of Social Media
  • Gave partner access to my Social Media accounts

Results

Correlations
numberofhours effectivenessinsocialmedia quarrels
numberofhours Pearson Correlation 1 .010 -.040
Sig. (2-tailed) .920 .677
N 111 111 111
effectivenessinsocialmedia Pearson Correlation .010 1 -.204*
Sig. (2-tailed) .920 .032
N 111 111 111
quarrels Pearson Correlation -.040 -.204* 1
Sig. (2-tailed) .677 .032
N 111 111 111
*. Correlation is significant at the 0.05 level (2-tailed).

Regression

Regression Statistics
Multiple R 0.00963339
R Square 9.28022E-05
Adjusted R Square -0.009080658
Standard Error 1.046120953
Observations 111
ANOVA
df SS MS F Significance F
Regression 1 0.011071 0.011071 0.010116 0.92006848
Residual 109 119.2862 1.094369
Total 110 119.2973
Coefficients Standard Error t Stat P-value Lower 95%
Intercept 2.631863845 0.194186 13.55334 3.99E-25 2.246994313
Number of hour spent 0.001163718 0.01157 0.10058 0.920068 -0.021767753
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IvyPanda. (2020, July 16). Social Media Impact on Students Relationships. Retrieved from https://ivypanda.com/essays/social-media-impact-on-students-relationships/

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"Social Media Impact on Students Relationships." IvyPanda, 16 July 2020, ivypanda.com/essays/social-media-impact-on-students-relationships/.

1. IvyPanda. "Social Media Impact on Students Relationships." July 16, 2020. https://ivypanda.com/essays/social-media-impact-on-students-relationships/.


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IvyPanda. "Social Media Impact on Students Relationships." July 16, 2020. https://ivypanda.com/essays/social-media-impact-on-students-relationships/.

References

IvyPanda. 2020. "Social Media Impact on Students Relationships." July 16, 2020. https://ivypanda.com/essays/social-media-impact-on-students-relationships/.

References

IvyPanda. (2020) 'Social Media Impact on Students Relationships'. 16 July.

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