f(x) increase by a factor of 3
Explanation:
Given that f(x)= 3* and the interval is x=4 to x=57
Now we put the value for x is 4 to 57 then value of f(x) increase with the multiply of 3.
Because the x is multiplied with 3 i.e., 3*
So f(x) increase by a factor of 3.
If we put x=4, then f(x)= 12 (∵ 3×4=12)
If we put x=5, the f(x)= 15 (∵ 3×5=15)
If we put x=6,the f(x)= 18 (∵ 3×6=18)
similarly., values of x= 7,8,9,...155.
Then,
If we put x=56, the f(x)=168
This process will continue until f(x)=171 for x=57.
Answer:
The artist can make six batches of orange paint and it remains one cup of yellow paint
Step-by-step explanation:
1. Let's review the information given to us to answer the question correctly:
Amount of red paint for one batch of orange paint = 1/3 of a cup
Amount of yellow paint for one batch of orange paint= 1/3 of a cup
Amount of red paint available = 2 cups
Amount of yellow paint available = 3 cups
2. How many batches of orange paint can she make?
2 cups of red paint = 6/3 = 6 batches of orange paint
3 cups of yellow paint = 9/3 = 6 batches and it remains one cup of yellow paint
The artist can make six batches of orange paint and it remains one cup of yellow paint
Step-by-step explanation:
Answer:
Step-by-step explanation:
Hello!
You need to test the hypothesis that the slope of the regression is cero.
I've run in the statistic software the given data for Y and X and estimated the regression line:
Yi= 7.82 -1.60Xi
Where
a= 7.82
b=-1.60
Sb= 3.38
The hypothesis is:
H₀: β = 0
H₁: β ≠ 0
α: 0.05
This is a two-tailed test, the null hypothesis states that the slope of the regression is cero, this means that if the null hypothesis is true, there is no linear regression between Y and X.
The statistic for this test is a Student-t
t= <u> b - β </u> ~t
Sb
The critical values are:
Left: 
Right: 
t= <u>-1.60 - 0 </u>= -0.47
3.38
the p-value is also two-tailed, you can calculate it by hand:
P(t ≤ -0.47) + (1 - P(t ≤ 0.47) = 0.3423 + (1 - 0.6603) =0.6820
With the level of significance of 5%, the decision is to not reject the null hypothesis. This means that the slope of the regression is equal to cero, i.e. there is no linear regression between the two variables.
I hope this helps!