36 and 64
How about: 36+64 = 100
62 + 82 = 36 + 64 = 100
The sum of the squares of the first 100 natural numbers [1..100] is 338350, while the sum of the first 100 natural numbers squared is 25502500.
64 and 36.
It is: 62+82 = 100
The only squares of perfect squares in that range are 1, 16, and 81.
1166650
36 and 64
If a question says solve the sum of the squares of 3 and 10, you would multiply 3 by 3 to get 9 and 10 by 10 to get 100, and add the two numbers to get 109. 32 + 102 = 9 + 100 = 109
The sum of their squares is 10.
If the regression sum of squares is the explained sum of squares. That is, the sum of squares generated by the regression line. Then you would want the regression sum of squares to be as big as possible since, then the regression line would explain the dispersion of the data well. Alternatively, use the R^2 ratio, which is the ratio of the explained sum of squares to the total sum of squares. (which ranges from 0 to 1) and hence a large number (0.9) would be preferred to (0.2).
There is a calculation error.