We used a t-test to compare the mean Total Federal Aid and the mean of the non-Federal Aid during 1990-1995. We also used a t-test to compare the mean Total Federal and the mean of the non-Federal Aid during 2010-2015. In comparing each of these means we were looking for the variance in the difference between these two main sources of aid during each time period and how this mean difference has changed from the beginning to end of our data set time interval.
Our results were:
1990-1995
data: ninetyFederal and ninetynonFederal
t = -5.7375, df = 5.6606, p-value = 0.001488
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
-18925.763 -7493.037
sample estimates:
mean of x mean of y
17614.4 30823.8
2010-2015
data: TenFederal and TennonFederal
t = -11.471, df = 4.6212, p-value = 0.0001433
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
-40681.45 -25481.75
sample estimates:
mean of x mean of y
70472.6 103554.2
This shows us that there is a significant difference in the means of federal and non-federal aid for both sets of years. Additionally, the 95% confidence interval is shown to be between much greater mean differences in 2010-2015, and a p-value of 2010-2015 approximately one tenth of 1990-1995. The p-values listed above describe a respective .1488% and .01433% chance of these mean differences being produced by random error assuming even amounts of aid from Federal and non-Federal sources and as the p-value decreases there would be a smaller chance of that difference being produced by random error. Overall, this data describes a trend of more non-Federal aid than Federal aid during each set of five years with this disparity increasing between the time periods.
This is really neat, but I am curious as to why there is such a difference. I'm not sure if this is something you can investigate with data, but it would be cool to see.
ReplyDeleteYeah, it would be cool to see what the effect of this difference is. Also, was inflation factored in?
ReplyDeleteThis looks good, but I think you could make your analysis paragraph a little clearer. Maybe elaborate on the differences between the different T-Tests that you did.
ReplyDeleteThis is an interesting set of data. I like it and I like how you compared it!
ReplyDeleteIs the federal and non federal aid still different like this from 1995 to 2010? It would be cool to see the amount of money change over time
ReplyDeleteThe closing paragraph could be a bit more concise. Try explaining it as you would to a layman, not people wh understand this stuff in order to make things more clear.
ReplyDeleteI kind of got what you are trying to say. I like this data but I think you could be more concise in your closing paragraph and explain what you are looking for in the intro before diving right in. I was a little bit lost on what you were talking about for the first paragraph.
ReplyDeleteNot completely sure what your conclusion is based on the tests. Is there more to infer than just that more non federal aid is and has almost always been given out?
ReplyDeleteA clearer analysis would be very helpful, with maybe a little more insight as to what the numbers could mean.
ReplyDelete