The line of best fit to model the data in the table is y = 5.2x – 0.4. what is the residual for 5? –1.6 –0.6 0.6 1.6

The residual for 5 is -1.6

Step-by-step explanation:

A residual value is the difference between the observed y-value and the predicted y-value( from the regression equation ) .

Here, the given regression equation of the line,

y = 5.2 x - 0.4

Thus, for x = 5, the predicted value of y = 5.2 × 5 - 0.4 = 26.0 - 0.4 = 25.6,

Now, by the given table,

For x = 5, the observed value of y = 24,

Hence, the residual for 5 = Observed value of y for 5 - Predicted value of y for 5

= 24 - 25.6 = - 1.6

⇒ First option is correct.

a² + b²= c²

24² + 7² = c²

c= 25

answer: it's upside down and i can't read it

step-by-step explanation: