Answer:
The statement, (1- <em>α</em>)% confidence interval for (μ₁ - μ₂) does not contain zero is TRUE.
Step-by-step explanation:
The hypothesis for a test is defined as follows:
<em>H</em>₀: μ₁ = μ₂ vs. <em>H</em>ₐ: μ₁ ≠ μ₂
It is provided that the test was rejected st the significance level <em>α</em>%.
If a decision is to made using the confidence interval the conditions are:
If the null hypothesis value is not included in the (1 - <em>α</em>)% confidence interval then the null hypothesis will be rejected and vice versa.
In this case the null hypothesis value is:
<em>H</em>₀: μ₁ - μ₂ = 0.
If the value 0 is not included in the (1 - <em>α</em>)% confidence interval for the difference between two means, then the null hypothesis will be rejected.
Thus the statement, (1- <em>α</em>)% confidence interval for (μ1- μ2) does not contain zero is TRUE.
Answer:
The function is 2 I believe
Step-by-step explanation:
Yea I can help:)! What is it???
Answer:
Number of flowers required = 1256
Step-by-step explanation:
Circumference of a circle is given by the formula,
Circumference = 2πr
Here, r = radius of the circle
For a circle with radius = 100 in.
Therefore, circumference = 2π(100)
= 200π
= 628.32 ft
Distance between each flower = 6 in
≈ 
= 0.5 ft
Number of flowers = 
= 
= 1256.63
≈ 1256
Therefore, number of flowers required = 1256
Answer:
Step-by-step explanation:
1) Previous concepts
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".
Let X the random variable that represent the scores, and for this case we know the distribution for X is given by:
And let
represent the sample mean, the distribution for the sample mean is given by:
On this case
2) Calculate the probability
We want this probability:
The best way to solve this problem is using the normal standard distribution and the z score given by:
If we apply this formula to our probability we got this: