Answer:
Step-by-step explanation:
slope intercept form is
y-mx+b where m is the slope, b-is the y-intercept
y=3x-2
Answer:
91
/125
Step-by-step explanation:
Answer:
Step-by-step explanation:
Move all terms to one side
Simplify
Split the second term
Factor out common terms in the first two terms, then in the last two terms.
Factor out the common term
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:
line
x-intercept | 0
f-intercept | 0
normal vector | (-3072/sqrt(9437185), 1/sqrt(9437185))≈(-1., 0.000325521)
slope | 3072
curvature | 0
Step-by-step explanation: