Answer:
b. Hannah is likely to be incorrect because 9 is not contained in the interval.
Step-by-step explanation:
Hello!
Hannah estimated per CI the difference between the average time that people spend outside in southern states and the average time people spend outside in northern states.
The CI is a method of estimation of population parameters that propose a range of possible values for them. The confidence level you use to construct the interval can be interpreted as, if you were to calculate 100 confidence interval, you'd expect that 99 of them will contain the true value of the parameter of interest.
In this example, the 99%CI resulted [0.4;8.0]hs
Meaning that with a 99% confidence level you'd expect the value of the difference between the average time people from southern states spend outside than the average time people from northern states spend outside is included in the interval [0.4;8.0]hs.
Now, she claims that people living in southern states spend 9 more hours outside than people living in northern states, symbolized μ₁ - μ₂ > 9
Keep in mind that if you were to test her claim, the resulting hypothesis test would be one-tailed
H₀: μ₁ - μ₂ ≤ 9
H₁: μ₁ - μ₂ > 9
And that the calculated Ci is tow-tailed, so it is not valid to use it to decide over the hypotheses pair. This said, considering that the calculated interval doesn't contain 9, it is most likely that Hannah's claim is incorrect.
I hope this helps!
Answer:
25
Step-by-step explanation:
180-90-65 = 25
Opposite angles are same
Answer:
Omar could invite 19 friends.
Step-by-step explanation:
the equation for this word problem would be
5x+30=125
subract 30 from both sides
5x=95
divide both sides by 5
x=19
As a rule of thumb, the sampling distribution of the sample proportion can be approximated by a normal probability distribution whenever the sample size is large.
<h3>What is the Central limit theorem?</h3>
- The Central limit theorem says that the normal probability distribution is used to approximate the sampling distribution of the sample proportions and sample means whenever the sample size is large.
- Approximation of the distribution occurs when the sample size is greater than or equal to 30 and n(1 - p) ≥ 5.
Thus, as a rule of thumb, the sampling distribution of the sample proportions can be approximated by a normal probability distribution when the sample size is large and each element is selected independently from the same population.
Learn more about the central limit theorem here:
brainly.com/question/13652429
#SPJ4
Answer:
1.9x10^-2
hope this helps
Step-by-step explanation:
