Answer:
x intercept 2
y intercept 1
Step-by-step explanation:
The x intercept is where it crosses the x axis( or horizontal axis) It crosses at x =2
The y intercept is where it crosses the y axis ( or vertical axis). It crosses at y =1
Hello!
The answer is C.
You can use a calculator or do it by hand and find that 6-1.455 is equal to 4.545.
Answer:
r(5)=3.05 t(5)=15
Step-by-step explanation:
x=5
r(5)=(1.25)^5
r(5)=3.05
t(5)=3(5)
t(5)=15
Answer:
d. Reject the claim that mean is 40 MPG when it is actually 40 MPG.
Step-by-step explanation:
The type 1 error could be said to have been made if the null hypothesis is erroneously rejected.
In the scenario above :
The null hypothesis (H0) : mean = 40
Hence, if the Null hypothesis defined above is rejected when in fact the hypothesis that the mean miles per gallon is actually 40.
On the other hand, the type 2 error occurs when a null which is false is not rejected.
Hence, when a true null is rejected, a type 1 error is committed. Similarly, when a false null isn't rejected, then a type 2 error has been committed.
Step-by-step explanation:
Regression analysis is used to infer about the relationship between two or more variables.
The line of best fit is a straight line representing the regression equation on a scatter plot. The may pass through either some point or all points or none of the points.
<u>Method 1:</u>
Using regression analysis the line of best fit is: 
Here <em>α </em>= intercept, <em>β</em> = slope and <em>e</em> = error.
The formula to compute the intercept is:
Here<em> </em>
and 
are mean of the <em>y</em> and <em>x</em> values respectively.
The formula to compute the slope is:
And the formula to compute the error is:
<u>Method 2:</u>
The regression line can be determined using the descriptive statistics mean, standard deviation and correlation.
The equation of the line of best fit is:
Here <em>r</em> = correlation coefficient = 
and 
are standard deviation of <em>x</em> and <em>y</em> respectively.
