3 is the smallest integer that cannot be written as the sum of two squares. This is easy to see, since the only squares less than or equal to 3 are 0 and 1.
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
There is a calculation error.
The question is ambiguous.Does it want the sum of the squares, or the square of the sum ? They're different.Here are both:1). Sum of the squares: . (1)2 + (2)2 + (3)2 + (4)2 + (5)2 = 1 + 4 + 9 + 16 + 25 = 552). Square of the sum: . (1 + 2 + 3 + 4 + 5 )2 = (15)2 = 225
36+37=73
sum of squares: 32 + 52 = 9 + 25 = 34 square of sum (3 + 5)2 = 82 = 64 This is a version of the Cauchy-Schwarz inequality.
xy=24 (x^2)+(y^2)=73
70* 2/3 = 46 and 2/3 squares.
3 is the smallest integer that cannot be written as the sum of two squares. This is easy to see, since the only squares less than or equal to 3 are 0 and 1.
The sum of their squares is 10.
The sum of the two prime numbers 3 and 73 is 76.
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
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).
67 + 3 + 3 = 73
2
There is a calculation error.
3 and 5