Answer: approximately 24
Step-by-step explanation:
We need to plot a regression line.
So we fit a model using the regression of Y on X, that an equation that predict Y for a given X using:
(Y -mean(Y ))= a(X-meanX)...........1
Where the formular of a is given the attachment.
N= the of individuals = 5
Y = amount of fat
X = time of exercise
mean(X )= sum of all X /N
= 131/5 = 26.2
mean(Y) = sum of all Y/N
= 104/5 = 20.8
a = N(SXY) - (SX)(SY)/ NS(X²) -(SX)²......2
SXY = Sum of Product X and Y
SX= sum of all X
SY = Sum of all Y
S(X²)= sum of all X²
(SX) = square of sum of X
a = -0.478
Hence we substitute into 1
Y-20.8 = -0.478 (X-26.2)
Y -20.8 = -0.478X - 12.524
Y = -0.478X + 33.324 or
Y = 33.324 - 0.478X (model)
When X = 20
Y = 33.324 - 0.478 × 20
Y = 33.324 - 9.56
Y = 23. 764
Y =24(approximately)
Carefully meaning of formula used in attachment to the solution they are the same.
1/9 x 12 is 4/3 or 1.333 repeated
Answer:

Step-by-step explanation:
The last one is also the answer
Using the rational exponet rule,
![\sqrt[n]{ {x}^{m} } = x {}^{ \frac{m}{n} }](https://tex.z-dn.net/?f=%20%5Csqrt%5Bn%5D%7B%20%7Bx%7D%5E%7Bm%7D%20%7D%20%20%3D%20x%20%7B%7D%5E%7B%20%5Cfrac%7Bm%7D%7Bn%7D%20%7D%20)
Using this number,

40 is the base so it will stay same. Remember this is a square root sign so our nth root is 2 so our denominator if the rational exponet is 2.

so our numerator is 1 so

Answer: 4%
Step-by-step explanation: 50 x 2 = 100
2x2=4 4/100 or 4%