In: Statistics and Probability
The medical community unanimously agrees on the health benefits of regular exercise, but are adults listening? during each of the past 15 years, a polling organization has surveyed Americans about their exercise habits. in the most recent of these polls, slightly over half of all American adults reported that they exercise for 30 or more minutes at least three times per week. The following data show the percentages of adults who reported that they exercise for 30 or more minutes at least three times per week during each of the 15 years of this study
Year |
Percentage of Adults Who Reported That They Exercise for 30 or More Minutes at Least Three Times per Week |
1 |
41.0 |
2 |
44.9 |
3 |
47.1 |
4 |
45.7 |
5 |
46.6 |
6 |
44.5 |
7 |
47.6 |
8 |
49.8 |
9 |
48.1 |
10 |
48.9 |
11 |
49.9 |
12 |
52.1 |
13 |
50.6 |
14 |
54.6 |
15 |
52.4 |
a time series plot. does a linear trend appear to be present?
simple linear regression to find the parameters for the line that minimizes MSE for this time series.
the trend equation from part (b) to forecast the percentage of adults next year (year 16 of the study) who will report that they exercise for 30 or more minutes at least three times per week.
use the trend equation from part (b) to forecast the percentage of adults three years from now (year 18 of the study) who will report that they exercise for 30 or more minutes at least three times per week?
(a) To check if there is a linear relation between time and % of people exercising we can use a scatter plot for it.
The x-axis will have the year values and the y-axis will have the %.
We can see that the trends follow a linear pattern along the years. The points are also close to each other indicating that there is a linear relation between time and percent of people exercisng.
Sr. No. | Year (x) | Percentage (y) | * | ||||
1 | 1 | 41 | -7 | -7.253 | 49.000 | 52.611 | 50.773 |
2 | 2 | 44.9 | -6 | -3.353 | 36.000 | 11.245 | 20.12 |
3 | 3 | 47.1 | -5 | -1.153 | 25.000 | 1.330 | 5.7667 |
4 | 4 | 45.7 | -4 | -2.553 | 16.000 | 6.520 | 10.213 |
5 | 5 | 46.6 | -3 | -1.653 | 9.000 | 2.734 | 4.96 |
6 | 6 | 44.5 | -2 | -3.753 | 4.000 | 14.088 | 7.5067 |
7 | 7 | 47.6 | -1 | -0.653 | 1.000 | 0.427 | 0.6533 |
8 | 8 | 49.8 | 0 | 1.547 | 0.000 | 2.392 | 0 |
9 | 9 | 48.1 | 1 | -0.153 | 1.000 | 0.024 | -0.153 |
10 | 10 | 48.9 | 2 | 0.647 | 4.000 | 0.418 | 1.2933 |
11 | 11 | 49.9 | 3 | 1.647 | 9.000 | 2.712 | 4.94 |
12 | 12 | 52.1 | 4 | 3.847 | 16.000 | 14.797 | 15.387 |
13 | 13 | 50.6 | 5 | 2.347 | 25.000 | 5.507 | 11.733 |
14 | 14 | 54.6 | 6 | 6.347 | 36.000 | 40.280 | 38.08 |
15 | 15 | 52.4 | 7 | 4.147 | 49.000 | 17.195 | 29.027 |
Total | 120 | 723.8 | 0 | 0.000 | 280.000 | 172.277 | 200.3 |
Mean | 8 | 48.253 |
The regression equation is given by
Where slope
= 200.3 / 280.00
= 0.715
intercept
= 48.253 - 0.715 * 8
= 42.53
The regression eq therefore is
(b) To forecast percentage of people we just substitute years in place of 'x'
When x = 16 we have
(c) when x = 18
(c)