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.

homozygous. one is homozygous, while two is heterozygous.

x =-.20752

step-by-step explanation:

4^(x+2)=12

4^(x+2)=12

take the log base 4 on each side

log 4 (4^(x+2) = log 4(12)

we know log b(a^y) = y log b (a)

(x+2) log 4(4) = log 4 (12)

x+2 = log 4 (12)

we know   logb c = loga c/loga b

we want to convert to base 10   so a = 10

by default, we do not write the 10   c = 4   and b = 10

log4 10 = log 12/log 4

log4 10 = log 12/ log 4

x+2 = log 12/ log 4

subtract 2 from each side

x +2 -2 = log 12/ log 4 -2

x = 1.79248125 -2

x =-.20752