However because of the type of sampling conducted i

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However, because of the type of sampling conducted I cannot drawn causational statements. **Research quesion 3:** ```{r}How does living in college housing influence the amount of sleep one get?
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Does this influence their overall general health status? ```{r} facet <- ggplot(data=brfss2013, aes(x=colghous, y=sleptim1, color=genhlth)) + geom_point(aes(shape=genhlth), size=4.0) + geom_smooth(method="lm") + xlab("College Housing") + ylab("Sleep Time") + ggtitle("Living in College housing and One's Sleep Time on General Health") facet + facet_grid(. ~ genhlth) ``` Summary Statistics & Narrative: An interesting trend to observe: The proportion of people who report "very good health" on average do not sleep more than those with "fair" health IF they live in college housing. This leads me to hypothesize that college housing's potential influence on sleep time may not have an overall impact on someone's health. In summary, the analysis seems to indicate that: no, there are no noticeable relations between college housing's potential on sleep time and one's general health. But these relations cannot be used to infer causality. I am interested in expanding the sample size for this data because the number of individuals who lived in college housing was not substantial enough to be representative. ```
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