In: Statistics and Probability
The sample data below are the typing speeds (in words per
minute) and reading speeds (in words per minute) of nine randomly
selected secretaries. Here, x denotes typing speed, and y denotes
reading speed.
X | 60 | 56 | 52 | 63 | 70 | 58 | 44 | 79 | 62 |
Y | 587 | 551 | 528 | 607 | 645 | 531 | 503 | 652 | 571 |
At the 10% significance level, predict the reading speed for a
typing speed of 74 words per
minute.
X | Y | X * Y | X2 | Y2 | |
60 | 587 | 35220 | 3600 | 344569 | |
56 | 551 | 30856 | 3136 | 303601 | |
52 | 528 | 27456 | 2704 | 278784 | |
63 | 607 | 38241 | 3969 | 368449 | |
70 | 645 | 45150 | 4900 | 416025 | |
58 | 531 | 30798 | 3364 | 281961 | |
44 | 503 | 22132 | 1936 | 253009 | |
79 | 652 | 51508 | 6241 | 425104 | |
62 | 571 | 35402 | 3844 | 326041 | |
Total | 544 | 5175 | 316763 | 33694 | 2997543 |
Equation of regression line is Ŷ = a + bX
b = 4.879
a =( Σ Y - ( b * Σ X) ) / n
a =( 5175 - ( 4.8792 * 544 ) ) / 9
a = 280.079
Equation of regression line becomes Ŷ = 280.0791 + 4.8792
X
When X = 74
Ŷ = 280.079 + 4.879 X
Ŷ = 280.079 + ( 4.879 * 74 )
Ŷ = 641.12 ≈ 641