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:
f(g(h(x))) = (sqrt(x) - 1)^4 + 4
Step-by-step explanation:
f(x) = x^4 + 4
g(x) = x - 1
h(x) = sqrt(x)
g(h(x)) = sqrt(x) - 1
f(g(h(x))) = (sqrt(x) - 1)^4 + 4
Answer: The simplified form by combining like terms is given by
Step-by-step explanation:
Since we have given that
Now, we combine the like terms :
1) First we collect m terms :
2) Combine n terms and constant terms :
Hence, the simplified form by combining like terms is given by
n² - 4n = 0
n(n) - n(4) = 0
n(n - 4) = 0
n = 0 or n - 4 = 0
+ 4 + 4
n = 4
Solution Set: {0, 4}
Answer:
First one: function and linear
Second one: function and non-linear
Third one: not a function and linear
Step-by-step explanation:
• The first one is set in the linear function formula y=mx+b, so it is a linear function.
• The second one is a non-linear because functions with exponents have different shapes and can intersect more than once unline linear functions.
• The third one isn't a function but it is linear because it isn't set equal to a variable and it would become a linear if you simply it to isolate a variable.
I hope this helps!!!
