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For this survey project, our group had a focus on social media’s effects on people’s behaviors, moods, and desires to go out. In order to play around with this idea, we first started to analyze how the amount of followers grouped onto certain platforms might correlate with how long people spends time on their phones. The reason for this in theory was that may be those who have accumulated a lot of followers spend more time on social media because they may post more often. After collecting the results, we see that this is somewhat true as some of the people closer to 500 followers spend around 1 hour and the people closer to 1500 followers say they spend around 3 hours online. However, the one outlier actually spends one of the least amount of times on social media.
Next one of the biggest things we wanted to measure was people’s desire to go out and if the amount of followers and social media had influenced their decisions. For this, data we got 5 people who said yes, 5 people who said no, and 5 people who said maybe. The “Maybe” box plot seems to be positively skewed, “No” is negatively skewed, and “Yes” is more symmetric when measuring the distances from the median to the Minimum and Maximum. Also the amount of followers for “Yes” is a little bit higher than “No” and “Maybe” when not including the outlier.
For our misrepresented graph we chose to measure battery life percentage. Although this graph is pretty helpful, we think they way we collected the data should have been done differently since the results are not being displayed properly. The first reason being that this question was probably confusing for many. This table only shows 14 out of the 15 participants results because one of the participants named an app name instead of writing their percentage down. Another thing that should have been clarified was that we should have listed the apps people should include the amount of battery that should be measured because now people are listing down numbers far all different various apps which is probably swaying the data.
If we were to do this project all over again, one of the things we would probably do is ask for more specific numbers and specify some of the questions more. For instance, when we asked what time people went online usually, some people would answer “in the afternoon/whenever I feel like it” or “8-12pm”. So for some of the questions it wouldn’t make sense to graph these types of results. Another idea we might change is to ask whether people were using their mobile social media apps versus the desktop websites.