Posted: August 3rd, 2022

Research analysis

Interpretation of results

Task

· You have collected your data and analyzed the results. Go back to the original research questions

 

of the items you analyzed and evaluate each one with our results. (See attached research questions)

· Consider why the results came out as they did and what the implications of the results are.

· For each research question, provide your interpretation of the results. Include limitations and generalizability in your discussion. Also, include references for any citations.

Data analysis

Demographics

I utilized SPSS to conduct a descriptive statistics analysis. For race, education and marital status I utilized frequencies and for age I utilized descriptive stats. I also picked the community service questions and utilized frequency stats.

For the demographic race. 64.1% identified as Caucasian, 23.9% African American, 6% Hispanic, 1.3% Asian American, 0.7 American Indian, 3.3 % Pacific Islander, and 0.7% declined to disclose their race. Looking at this I would say that the participant pool was not that diverse. This also makes me wonder when it comes to the actual community service question, would there be one or more races that were more active in community services than other races.

The next demographic is education. 6.6% of the respondents held a Doctorate, 43.2% held a master’s degree, 21.9% held a bachelor’s degree, 19.9% held an associate degree, 7.6% completed high school and 0.7% chose other but unsure what other options were available. This data is important because at first glance it appears that the respondents with higher degrees were more willing to take part in the research than those without.

The last demographic is marital status. 59.5% of the respondents were married, 28.6% were single, 9.3% divorced, 1% widowed and 1.7% chose not to answer. This makes me wonder since the marital status percent was higher was it due to partner influence by chance.

Lastly when looking at age, I ran descriptive statistics, and the mean age was 43.34. 18 years old was the minimum and 76 was the maximum.

Community Service Questions

In the past year, did you participate in community service (e.g., for nonprofit)?

For this question 43.5% of the respondents made donations and contributions while 39.5% went out and volunteered their time. The other 16.9% made a social media post about community service but did not engage in the actual activity. This shows that more individuals were willing to make monetary contributions instead of going out in the community and engaging in the activity.

How often do you post about a community or nonprofit issue?

Some of the respondents (24.4%) reported that they rarely post about a community issue and next are 17.8% who post several times a year and 13.3% that post more than once a week. I am somewhat surprised with the popularity of social media that the percentage of those who rarely post was higher among the respondents.

How often did you participate in community service in the past year?

31.7% of the respondents reported that they participate several times a year, followed by 18.6% that reported they rarely participate and 12.4% that reported that they participate weekly. This is intriguing because this plays into the question about the type of contribution that is being made, whether it’s a financial contribution or if they are contributing their time.

So far it looks as though more respondents want to contribute money, rather than going out and engaging in community service. Also it shows that even though social media is a popular avenue for communication it is rarely being used to bring light to some community issues or service.

The first RQ I analyzed utilizing a correlation for is RQ3, “What is the relationship between community service and social media”? The two variables that were analyzed were how often do you post about community or nonprofit issues and how often did you participate in community service in the past year. When looking at the correlation matrix, the Pearson correlation is 499 which shows that there is a strong correlation and also indicates that there is a relationship between the variables. This also tells us that there is a relationship between community service and social media because those individuals that post about community issues are more likely to participate in community service and those who may actively participate in community service are more likely to post community issues to their social media accounts. I can conclude that there is a relationship between community service and social media. 

The second RQ I analyzed utilizing a correlation for is RQ4, “What is the relationship between political participation and social media”? The two variables that were analyzed were how often do you post about a political issue and how often did you participate in political service in the past year? This one was unable to produce any analysis because one of the variables is constant. I think this means that there is no correlation or not a strong correlation between the two variables. I conclude that there is no relationship between political participation and social media.

 

The RQ I analyzed utilizing a multiple regression for is RQ5, “What are predictors of use of social media related to community service: Demographics: age, gender, race/ethnicity, education”? My dependent variable is “how often do you post about a community or nonprofit issue” and the independent variables are age, gender, race/ethnicity and education. When looking at the Anova box the sig. it is 0.729 which is higher than 0.05 conventional threshold so the model overall does not have statistical significance. Next we will look at the coefficients table. If the sig. is >0.05 then the null hypothesis is not rejected and this means that there is no impact to the dependent variable (Warner, 2013).For the demographic predictor of age the sig. it is 0.373 which is higher than 0.05 conventional threshold so this means that there is no relationship between age and how often an individual posts a community issue on social media. For the demographic predictor of gender the sig. it is 0.791 which is higher than 0.05 conventional threshold so this means that there is no relationship between gender and how often an individual posts a community issue on social media. For the demographic predictor of race/ethnicity the sig. it is 0.459 which is higher than 0.05 conventional threshold so this means that there is no relationship between race/ethnicity and how often an individual posts a community issue on social media. For the demographic predictor of education the sig. it is 0.882 which is higher than 0.05 conventional threshold so this means that there is no relationship between education and how often an individual posts a community issue on social media. What I would conclude from this data analysis is that there are no demographic predictors for use of social media related to community service. 

The RQ8 that I utilized for the coding was “what is the experience of engaging in community service participation?

First, I created coding categories of rewarding, sense of community, personal satisfaction, meeting like-minded people and other. This first thing did was run a frequency on my coding variable. This resulted in showing that 12.5 % of the respondents described the experience of engaging in community service as rewarding, 45.8 % of the respondents described the experience of engaging in community service as feeling a sense of community, 20.8 % of the respondents described the experience of engaging in community service as having a sense of personal satisfaction, 4.2 % of the respondents described the experience of engaging in community service as positive due to meeting like-minded people and 16.7 % of the respondents described the experience of engaging in community service as other reasons that were not coded.

When looking at the pearson correlation, which in .111, this shows that there is a weak correlation between the variables. The data suggests that social media use doesn’t play a role in whether an individual chose to engage in community service.

RQ1: What are participants’ attitudes towards community service, as measured by the Community Service Attitude Subscales (CSAS)?

H10: There is no relationship between the CSAS subscales

H1A: There is a relationship between the CSAS subscales

Analysis: Correlation between the CSAS Subscales: Awareness, Connectedness, Normative Helping Behavior, Costs, Benefits, Career Benefits, Seriousness, Intention, Future Plans

RQ2: What are some predictors of attitudes to community service (as measured by CSAS subscales): Demographics: age, gender, race/ethnicity, education?

H10: There are no demographic predictors of community service (using CSAS subscales)

H1A: There are demographic predictors of community service (using CSAS subscales)

Analysis: Multiple regressions with subscales and demographics

RQ3: What is the relationship between community service and social media?

H10: There is no relationship between community service and social media

H1A: There is a relationship between community service and social media

Analysis: Correlation between community service and social media

RQ4: What is the relationship between political participation and social media?

H10: There is no relationship between political participation and social media

H1A: There is a relationship between political participation and social media

Analysis: Correlation between political participation and social media

RQ5: What are predictors of use of social media related to community service: Demographics: age, gender, race/ethnicity, education?

H10: There are no demographic predictors for use of social media related to community service

H1A: There are demographic predictors for use of social media related to community service

Analysis: Multiple regressions with use of social media related to community service

RQ6: What are predictors of use of social media related to political service: Demographics: age, gender, race/ethnicity, education?

H10: There are no demographic predictors for use of social media related to political service

H1A: There are demographic predictors for use of social media related to political service

Analysis: Multiple regressions with use of social media related to political service

RQ7: What is the relationship between attitudes toward community service (as measured by the CSAS) and use of social media?

H10: There is no relationship between CSAS subscales and social media

H1A: There is a relationship between CSAS subscales and social media

Analysis: Correlation between CSAS subscales and social media

RQ8 Open ended question: What is the experience of engaging in community service participation?

Analysis: coding and correlation with community service

RQ9 Open ended question: What is the experience of engaging in political participation?

Analysis: coding and correlation with political service

RQ10 Open ended question: What are the reasons given for people not to participate in community service?

Analysis: coding and correlation with community service

RQ11 Open ended question: What are the reasons given for people not to participate in political service?

Analysis: coding and correlation with political service

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