<span>Let the price (before tax) be x.
The tax is 7% of x, so it is 0.07x.
The price plus the tax add up to $45.
x + 0.07x = 45</span>
Answer:
the slope of the regression equation for predicting our Exam 2 scores from Exam 1 scores is 0.492
And the y-intercept of the regression equation for predicting our Exam 2 scores from Exam 1 is 33.688
Step-by-step explanation:
Given the data in the question;
mean X" = 86
SD σx = 10
Y" = 76
SD σy = 8.2
r = 0.6
Here, Exam 2 is dependent and Exam 1 is independent.
The Regression equation is
y - Y" = r × σy/σx ( x - x" )
we substitute
y - 76 = 0.6 × 8.2/10 ( x - 86 )
y - 76 = 0.492( x - 86 )
y - 76 = 0.492x - 42.312
y = 0.492x - 42.312 + 76
y = 0.492x + 33.688
Hence, the slope of the regression equation for predicting our Exam 2 scores from Exam 1 scores is 0.492
And the y-intercept of the regression equation for predicting our Exam 2 scores from Exam 1 is 33.688
Answer: 35 and 27
Step-by-step explanation:
We can solve this by using a system of equations
x will be the first number while y will be the second
This equation means the two numbers will add to get 62
This equation means when subtracted the two numbers will have the difference of 8.
Now I will solve by elimination
When adding the two equations why was eliminated so now we can find the value of x
Now sub in x into one of the original equations to find the value of y
