YOU WENT TO THE GYM LAST WEEK AND SPENT THE FOLLOWING AMOUNT OF YOUR TIME ON THE RUNNING MACHINE.
2 answers:
Answer: On Friday, he spend the least amount of time on the running machine.
Step-by-step explanation:
Since we have given that
Monday 0.3 =
Tuesday = 15%
Wednesday =
Thursday =
Friday =
Hence, we can compare all the days, and we get that
On Friday, he spend the least amount of time on the running machine.
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Answer:
Because z is higher than any given value in the chart we come to the conclusion To reject null hypothesis
Step-by-step explanation:
Sample proportion = p= 531/648 = 0.8194
This is the proportion of men that were hit by lightening
Null hypothesis: H0: p = 0.5
Alternate hypothesis: H1: p ≠ 0.5
Test statistics z = 0.8194-0.5/(√0.5x0.5/648)
= 0.8194-0.5/√0.0003858
= 0.3194/0.019642
= 16.26
Since the z > 1.96 (at 5% significance) we reject the null hypothesis.
Therefore in conclusion we say z is higher than given values in the chart so we reject null hypothesis.
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Answer:
The degrees of freedom are given by:
Since is a two-sided test the p value would be:
Since the p value is a very low value we have enough evidence to conclude that true mean is significantly different from 1.35 in/year at any significance level commonly used for example ().
Step-by-step explanation:
Data given and notation
represent the sample mean
represent the sample deviation
sample size
represent the value that we want to test
represent the significance level for the hypothesis test.
t would represent the statistic (variable of interest)
represent the p value for the test (variable of interest)
State the null and alternative hypotheses.
We need to conduct a hypothesis in order to check if the true mean is different from 1.35 in/year, the system of hypothesis would be:
Null hypothesis:
Alternative hypothesis:
The statistic is given by:
(1)
Calculate the statistic
We can replace in formula (1) the info given like this:
P-value
The degrees of freedom are given by:
Since is a two-sided test the p value would be:
Since the p value is a very low value we have enough evidence to conclude that true mean is significantly different from 1.35 in/year at any significance level commonly used for example ().