Maths Expert Needed - 1 page report - Due in 5 hours.

This graph shows the percentage of U.S civilians enlisted in the military after the year 1954. The linear equation of this graph is y1=-0.313x+19.308. The R2 value is 0.7133.

The units for this slope is the percentage of civilians enlisting in the military per year (after the year 1954). This means that according to our graph the number of civilians enlisted in the military after the year 1954 is decreasing by 0.3134 per year.

We used excel to find the average rate of change which turned out to be -0.427. This means that it is less than the rate of change in y1 which was -0.3134.

Using the average slope that we got from excel and the first data point in our set we created a new linear equation, in order to find the y-intercept we used the equation, y-y0=m(x-x0). After substituting (1,29.1) into our equation we got, y-29.1=-0.427(x-1), this resulted in; y2=-0.427x+29.427.

When comparing y1 to the fifth data set, 21, we get, y1=-0.313(21)+19.308, y1=-6.573+19.308, y1=12.735. This means that, in the year in terms of y1, 12.735% of US civilians will be enlisted in the military in the year 1975. This is a somewhat close to the actual data table which was 9.6%.

When evaluating y2 to the fifth data point we get, y2=-0.427(21)+29.427, y2=-8.967+29.427, y2=20.46. This means that, according to y2, 20.46% of U.S civilians will be enlisted in the military in the year 1975. This is far off from the actual data table, which was 9.6%.

When comparing y1 to the last data set which is 61 we get, y1=-0.313(61)+19.308, y1=-19.093+19.308, y1=0.215%. This means that according to y1 only 0.215% of U.S civilians will be enlisted in the military by the year 2015. This is a little inaccurate to the actual data table, which was 3.5%. When evaluating y2 to the last data point we get, y2=-0.427x+29.427, y2=-0.427(61)+29.427, y2=-26.047+29.427, y2=3.38. This is almost exactly like the last data point, which was 3.5%.

When plotting both y1 and y2 in our graphing calculators we noticed that y1 is more accurate because it’s line it touching almost all the points while y2’s line is not touching most of the points except the last x value (61).

I do not think that this data is linear because both y1 and y2 are not changing at a constant rate, meaning that the rate of change from 1-21 is not the as 22,61.