Answer:
See below
Step-by-step explanation:
It looks like
- AB⟂CD
- AB and CD bisect each other.
9r=3r+6
Subtract 3r from both sides
6r=6
Divide both sides by 6
r=1
Answer:
0.0623 ± ( 2.056 )( 0.0224 ) can be used to compute a 95% confidence interval for the slope of the population regression line of y on x
Step-by-step explanation:
Given the data in the question;
sample size n = 28
slope of the least squares regression line of y on x or sample estimate = 0.0623
standard error = 0.0224
95% confidence interval
level of significance ∝ = 1 - 95% = 1 - 0.95 = 0.05
degree of freedom df = n - 2 = 28 - 2 = 26
∴ the equation will be;
⇒ sample estimate ± ( t-test) ( standard error )
⇒ sample estimate ± (
) ( standard error )
⇒ sample estimate ± (
) ( standard error )
⇒ sample estimate ± (
) ( standard error )
{ from t table; (
) = 2.055529 = 2.056
so we substitute
⇒ 0.0623 ± ( 2.056 )( 0.0224 )
Therefore, 0.0623 ± ( 2.056 )( 0.0224 ) can be used to compute a 95% confidence interval for the slope of the population regression line of y on x
Answer:
Let x = the charge in 1st city before taxes
Let y = the charge in 2nd city before taxes
Set up equation before taxes.
y = x - 1500 eq1
Set up equation for total tax paid.
0.065x + 0.06y = 378.75 eq2
Substitute eq1 into eq2.
0.065x + 0.06(x - 1500) = 378.75
0.065x + 0.06x - 90 = 378.75
0.125x - 90 = 378.75
0.125x = 468.75
x = 3750
Substitute this value of x into eq1.
y = 3750 - 1500
y = 2250
The hotel charge in city one is $3750 and the hotel charge in city two is $2250
To get the answer, divide 55 by 610. the answer would be 11.09 i’m pretty sure