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.
Answer:
10
Step-by-step explanation:
ok so first you eat my poop then you eat your own poop and then you eat my dog poop
Answer:
Step-by-step explanation:
Since the line segment is only being translated and reflected it would still maintain its length. This is pretty much the only characteristic that would remain the same as te original line segment. It would not maintain the same x-axis positions for both endpoints of the line segment. This is because when it is translated 2 units up it is only moving on the y-axis and not the x-axis. But when it is reflected over the y-axis the endpoints flip and become the opposite values.
Answer:
169
Step-by-step explanation:
You need to use a Z-table for this.
There are different tables, in this table i searched for the probability of 97% because that equivalent to the top 3%.
for 0.97, Z = 1.88
The formula of Z is:

Solving x:
