In: Statistics and Probability
The table below shows primary school enrollment for a certain country. Here, xx represents the number of years after 18201820, and yy represents the enrollment percentage. Use Excel to find the best fit linear regression equation. Round the slope and intercept to two decimal places.
x   y
0   0.1
5   0.1
10   0.1
15   0.2
20   0.2
25   0.3
30   0.4
35   0.5
40   0.6
45   1.1
50   1.5
55   3.0
60   4.5
65   5.5
70   6.1
75   6.8
80   7.0
85   8.0
90   9.3
95   10.7
100   12.4
105   14.1
110   16.6
115   17.5
120   19.7
125   19.4
130   32.7
135   40.9
140   47.6
145   57.8
150   57.0
155   61.7
160   63.2
165   75.0
170   76.5
175   96.0
180   92.0
185   100.0
190   100.0
Provide your answer below:
y = x -
| X - Mx | Y - My | (X - Mx)2 | (X - Mx)(Y - My) | 
| -95 | -27.2359 | 9025 | 2587.4103 | 
| -90 | -27.2359 | 8100 | 2451.2308 | 
| -85 | -27.2359 | 7225 | 2315.0513 | 
| -80 | -27.1359 | 6400 | 2170.8718 | 
| -75 | -27.1359 | 5625 | 2035.1923 | 
| -70 | -27.0359 | 4900 | 1892.5128 | 
| -65 | -26.9359 | 4225 | 1750.8333 | 
| -60 | -26.8359 | 3600 | 1610.1538 | 
| -55 | -26.7359 | 3025 | 1470.4744 | 
| -50 | -26.2359 | 2500 | 1311.7949 | 
| -45 | -25.8359 | 2025 | 1162.6154 | 
| -40 | -24.3359 | 1600 | 973.4359 | 
| -35 | -22.8359 | 1225 | 799.2564 | 
| -30 | -21.8359 | 900 | 655.0769 | 
| -25 | -21.2359 | 625 | 530.8974 | 
| -20 | -20.5359 | 400 | 410.7179 | 
| -15 | -20.3359 | 225 | 305.0385 | 
| -10 | -19.3359 | 100 | 193.359 | 
| -5 | -18.0359 | 25 | 90.1795 | 
| 0 | -16.6359 | 0 | 0 | 
| 5 | -14.9359 | 25 | -74.6795 | 
| 10 | -13.2359 | 100 | -132.359 | 
| 15 | -10.7359 | 225 | -161.0385 | 
| 20 | -9.8359 | 400 | -196.7179 | 
| 25 | -7.6359 | 625 | -190.8974 | 
| 30 | -7.9359 | 900 | -238.0769 | 
| 35 | 5.3641 | 1225 | 187.7436 | 
| 40 | 13.5641 | 1600 | 542.5641 | 
| 45 | 20.2641 | 2025 | 911.8846 | 
| 50 | 30.4641 | 2500 | 1523.2051 | 
| 55 | 29.6641 | 3025 | 1631.5256 | 
| 60 | 34.3641 | 3600 | 2061.8462 | 
| 65 | 35.8641 | 4225 | 2331.1667 | 
| 70 | 47.6641 | 4900 | 3336.4872 | 
| 75 | 49.1641 | 5625 | 3687.3077 | 
| 80 | 68.6641 | 6400 | 5493.1282 | 
| 85 | 64.6641 | 7225 | 5496.4487 | 
| 90 | 72.6641 | 8100 | 6539.7692 | 
| 95 | 72.6641 | 9025 | 6903.0897 | 
| SS: 123500 | SP: 64368.5 | 
Sum of X = 3705
Sum of Y = 1066.1
Mean X = 95
Mean Y = 27.3359
Sum of squares (SSX) = 123500
Sum of products (SP) = 64368.5
Regression Equation = ŷ = bX + a
b = SP/SSX = 64368.5/123500 =
0.52
a = MY - bMX = 27.34 -
(0.52*95) = -22.18
ŷ = 0.52X - 22.18