So all you have to do to solve these problems is substitute the y coordinate and the x coordinate into the equation.
So question 1 would be true because when you substitute the numbers in it equals the y value.
Question 2 is (4, -7)
Question 3 is False
Question 4 is true
Question 5 is true
See if you can do the rest!
Answer:
Linear correlation exists
Step-by-step explanation:
Given the data :
X : | 2 4 5 6
Y : | 6 9 8 10
Using technology to fit the data and obtain the correlation Coefficient of the regression model,
The Correlation Coefficient, r is 0.886
To test if there exists a linear correlation :
Test statistic :
T = r / √(1 - r²) / (n - 2)
n = number of observations
T = 0.886 / √(1 - 0.886²) / (4 - 2)
T = 0.866 / 0.3535845
T = 2.449
Comparing Pvalue with α
If Pvalue < α ; Reject H0
Pvalue = 0.1143
α = 0.05
Pvalue > α ; We reject the null and conclude that linear correlation exists
Answer:
<u>There</u><u> </u><u>is</u><u> </u><u>no</u><u> </u><u>solution</u>
The number 12 would work because subtracting 2 from 12 is ten and that's basically like adding 12 to -2 :)
