Help pls I really need this. Do I need to add or multiply and also I need the answer? Will get brainlist and 10 points
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Answer:
a) Null and alternative hypothesis
b) Test statistic t=-1.565
P-value = 0.0612
NOTE: the sample size is n=65.
c) Do not reject H0. We cannot conclude that the price in Providence for a bottle of red wine that scores 4.0 or higher on the Vivino Rating System is less than the population mean of $32.48.
d) Null and alternative hypothesis
Test statistic t=-1.565
Critical value tc=-1.669
t>tc --> Do not reject H0
Do not reject H0. We cannot conclude that the price in Providence for a bottle of red wine that scores 4.0 or higher on the Vivino Rating System is less than the population mean of $32.48.
Step-by-step explanation:
This is a hypothesis test for the population mean.
The claim is that the mean price in Providence for a bottle of red wine that scores 4.0 or higher on the Vivino Rating System is less than the population mean of $32.48.
Then, the null and alternative hypothesis are:
The significance level is 0.05.
The sample has a size n=65.
The sample mean is M=30.15.
As the standard deviation of the population is not known, we estimate it with the sample standard deviation, that has a value of s=12.
The estimated standard error of the mean is computed using the formula:
Then, we can calculate the t-statistic as:
The degrees of freedom for this sample size are:
This test is a left-tailed test, with 64 degrees of freedom and t=-1.565, so the P-value for this test is calculated as (using a t-table):
As the P-value (0.0612) is bigger than the significance level (0.05), the effect is not significant.
The null hypothesis failed to be rejected.
At a significance level of 0.05, there is not enough evidence to support the claim that the mean price in Providence for a bottle of red wine that scores 4.0 or higher on the Vivino Rating System is less than the population mean of $32.48.
<u>Critical value approach</u>
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At a significance level of 0.05, for a left-tailed test, with 64 degrees of freedom, the critical value is t=-1.669.
As the test statistic is greater than the critical value, it falls in the acceptance region.
The null hypothesis failed to be rejected.
Step-by-step explanation:
this is the anwser it is inverse trigonometry
Answer:
Step-by-step explanation:
Hello!
The objective is to test if people with less social contact get more colds than people who are involved in a variety of social activities.
For this, a sample of 276 healthy men and women was taken.
n₁= 96 had few social outlets
n₂= 105 had six or more activities
These two groups were exposed to the cold virus and the following proportions of individuals that got sick were obtained:
p'₁= 0.62 (62% of the people with few social outlets got sick)
p'₂= 0.35 (35% of the people with six or more activities got sick)
The study variables are X₁: number of people with few social outlets that got sick after being exposed to the cold virus, in a sample of 96, and X₂: number of people with six or more activities that got sick after being exposed to the cold virus, in a sample of 105.
You have to construct a 99% CI for the difference these two populations since there is no specific order given I'll estimate: p₁ - p₂
(p'₁ - p'₂) ±
(0.62-0.35) ± 2.586
[0.094; 0.045]
With a 99% confidence level, you'd expect that the difference between the proportion of people with few social outlets that got sick and the proportion of people with six or more social activities that got sick after being exposed to the cold virus.
I hope it helps!