Question

To state:The null and alternative hypothesis.

Significance tests
ANSWERED
asked 2021-03-05
To state:The null and alternative hypothesis.

Answers (1)

2021-03-06
Justification:
Here, the claim is that there is a difference between the median tenures for male workers and female workers. In the given experiment, the alternative hypothesis indicates the claim. The test hypotheses are given below:
Null hypothesis: There is no difference between the median tenures for the male workers and female workers.
Alternative hypothesis (Claim): There is a difference between the median tenures for the male workers and female workers.
0
 
Best answer

expert advice

Need a better answer?

Relevant Questions

asked 2020-12-07
Hypothesis Testing Review
For each problem below, simply identify the null and alternative hypotheses. Use appropriate notation/symbols. You do not have to run any hypothesis tests, although it's good practice and I'll post answers for all of them.
1) A simple random sample of 44 men from a normally distributed population results in a standard deviation of 10.7 beats per minute. The normal range of pulse rates of adults is typically given as 60 to 100 beats per minute. If the range rule of thumb is applied to that normal range, the result is a standard deviation of 10 beats per minute. Use the sample results with a 0.10 significance level to test the claim that pulse rates of men have a standard deviation equal to 10 beats per minute.
2) In 1997, a survey of 880 households showed that 145 of them use e-mail. Use those sample results to test the claim that more than 15% of households use e-mail. Use a 0.05 significance level.
asked 2021-01-19

Identify the null and alternative hypothesis in the following scenario.
To determine if battery 1 lasts longer than battery 2, the mean lasting times, of the two competing batteries are compared. Twenty batteries of each type are randomly sampled and tested. Both populations have normal distributions with unknown standard deviations.
Select the correct answer below: \(H_{0}:\mu_{1}\geq\mu_{2}, H_{a}:\mu_{1}<\mu_{2}\)
\(H_{0}:\mu_{1}\leq −\mu_{2}, H_{a}:\mu_{1}>−\mu_{2}\)
\(H_{0}:\mu_{1}\geq −\mu_{2}, H_{a}:\mu_{1}<−\mu_{2}\)
\(H_{0}:\mu_{1}=\mu_{2}, H_{a}:\mu_{1}\neq \mu_{2}\)
\(H_{0}:\mu_{1}\leq \mu_{2}, H_{a}:\mu_{1}>\mu_{2}\)

asked 2021-02-24
To state:The null and alternative hypotheses.
asked 2021-01-10
A company is marketing a new product they say works better than the traditional test tube. There is so much interest in the product that 30 different labs around the world are testing the claim that this product is actually better. If each study uses an alpha level (alpha) of .10, and if the null hypothesis is true (that the test tube isn't any better that the traditional one), how many of the hypothesis tests would we expect to incorrectly find statistical significance (that is, conclude that the new test tube is better, when it actually isn't)?
asked 2020-12-24
For the same data, null hypothesis, and level of significance, if the conclusion is to reject \(H_{0}\) based on a two-tailed test, do you also reject Ho based on a one-tailed test? Explain.
asked 2020-12-30
For the same data, null hypothesis, and level of significance, is it possible that a one-tailed test results in the conclusion to reject Hg while a two tilled test results in the conclusion to fail to reject Ho? Explain.
asked 2020-12-24
In there a relationship between confidence intervals and two-tailed hypothesis tests? The answer is yes. Let c be the level of confidence used to construct a confidence interval from sample data. Let * be the level of significance for a two-tailed hypothesis test. The following statement applies to hypothesis tests of the mean: For a two-tailed hypothesis test with level of significance a and null hypothesis H_0 : mu = k we reject Ho whenever k falls outside the c = 1 — alpha confidence interval for mu based on the sample data. When A falls within the c = 1 — alpha confidence interval. we do reject H_0. For a one-tailed hypothesis test with level of significance Ho : mu = k and null hypothesiswe reject Ho whenever A falls outsidethe c = 1 — 2alpha confidence interval for p based on the sample data. When A falls within thec = 1 — 2alpha confidence interval, we do not reject H_0. A corresponding relationship between confidence intervals and two-tailed hypothesis tests is also valid for other parameters, such as p,mu1 — mu_2, and p_1, - p_2. (b) Consider the hypotheses H_0 : p_1 — p_2 = O and H_1 : p_1 — p_2 != Suppose a 98% confidence interval for p_1 — p_2 contains only positive numbers. Should you reject the null hypothesis when alpha = 0.05? Why or why not?
asked 2021-01-31
In there a relationship between confidence intervals and two-tailed hypothesis tests? The answer is yes. Let c be the level of confidence used to construct a confidence interval from sample data. Let * be the level of significance for a two-tailed hypothesis test. The following statement applies to hypothesis tests of the mean:
For a two-tailed hypothesis test with level of significance a and null hypothesis \(H_{0} : \mu = k\) we reject Ho whenever k falls outside the \(c = 1 — \alpha\) confidence interval for \(\mu\) based on the sample data. When A falls within the \(c = 1 — \alpha\) confidence interval. we do reject \(H_{0}\).
For a one-tailed hypothesis test with level of significance Ho : \(\mu = k\) and null hypothesiswe reject Ho whenever A falls outsidethe \(c = 1 — 2\alpha\) confidence interval for p based on the sample data. When A falls within the \(c = 1 — 2\alpha\) confidence interval, we do not reject \(H_{0}\).
A corresponding relationship between confidence intervals and two-tailed hypothesis tests is also valid for other parameters, such as p, \(\mu1 — \mu_2,\ and\ p_{1}, - p_{2}\).
(a) Consider the hypotheses \(H_{0} : \mu_{1} — \mu_{2} = O\ and\ H_{1} : \mu_{1} — \mu_{2} \neq\) Suppose a 95% confidence interval for \(\mu_{1} — \mu_{2}\) contains only positive numbers. Should you reject the null hypothesis when \(\alpha = 0.05\)? Why or why not?
asked 2020-11-02
As access to computers becomes more and more prevalent, we see the P-value reported in hypothesis testing more frequently. Review the use of the P-value in hypothesis testing. What is the difference between the level of significance of a test and the P-value? Considering both the P-value and level of significance. under what conditions do we reject or fail to reject the null hypothesis?
asked 2020-12-28
A. Look for the definitions of the following terms related to hypothesis testing.
1. Null Hypothesis
2. Level of Significance
3. Type I error

You might be interested in

...