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
.1.Scale Factor of Triangle STU to Triangle PQR= 1.5
2.Scale Factor of Trapezoid EFGH to Trapezoid JKLM =2
3. about 90 armadillo
1.Side ST: 15 ÷ Side PQ: 10 = 1.5
2.Side JM: 14 ÷Side EH: 7 = 2
3.843/7=120.428571429
843/4=210.75
210.75-120.428571429=90.321428571
This rounds to 90 armadillo
Hope this helps :3 ❤
Answer:
-21/4
Step-by-step explanation:
slope = y2-y1/ x2-x1
-18 - 3 / 17-13 = -21/4
Answer:
y = -3/4x + 1
Step-by-step explanation: