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
First we have to rewrite this function.Instead of :^3 sqrt (...) we can write : (...)^(1/3).
f ( x ) = ( 27 x - 81 ) ^(1/3) - 5 = ( 27 * ( x - 3 ) ) ^(1/3) - 5 = = 3 * ( x - 3 )^(1/3) - 5 And this makes it easy to graph a translation.The parent function is y = x^(1/3). The zero of this function is ( 0, 0 ).
Then it will be stretched vertically by a factor of 2 and translated: 3 units right and 5 units down.
Answer:
Step-by-step explanation:
information given
represent the sample mean
represent the population standard deviation
sample size
represent the value that we want to test
represent the significance level for the hypothesis test.
z would represent the statistic
represent the p value for the test
Hypothesis to test
We want to test if the true mean is less than 12, the system of hypothesis would be:
Null hypothesis:
Alternative hypothesis:
The statistic is given by:
(1)
Replacing the info given we got:
We can replace in formula (1) the info given like this:
If you're using the app, try seeing this answer through your browser: brainly.com/question/2789579_______________
Solve the incomplete quadratic equation:
Solution set:
S = {0, 8}.
I hope this helps. =)
