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
Not a function because of the vertical line test.
Domain is [-2,∞] since the left most point is -2 and the right is unbounded.
Range is (-∞,∞) since it is not bounded in terms of y.
Answer:
see explanation
Step-by-step explanation:
The equation of a line in slope- intercept form is
y = mx + c ( m is the slope and c the y- intercept )
here m = -
, hence
y = -
x + c ← is the partial equation
To find c substitute (- 3, - 1) into the partial equation
- 1 = 2 + c ⇒ c = - 1 - 2 = - 3
y = -
x - 3 ← is the equation of the line
Answer:
y = x^2 + 9x + 6 No remainder.
Step-by-step explanation:
The divisor will be 3 The sign on the divisor switches.
3 || 1 + 6 - 21 - 18 ||
3 27 + 18
================================
1 9 6 0
The answser is x^2 + 9x + 6