Question

1. What are the six steps of hypothesis testing?
2. What does it mean if we reject the null hypothesis?
3. How does statistical significance differ from practical significance?
4. What is the difference between a one-tailed and a two-tailed test? Why is a two-tailed test preferred over a one-tailed test?

Answer 1

# six steps for testing hypothesis are given below :-

1)- first of we have to state null and alternative hypothesis .

2)- next step will be assumptions that include

measurement level of data,

distributions underlying the data,

knowledge or lack of about population characteristics

sample size and method,

sample characteristics necessary for applying the test statistic,

level of significance for testing

3)- and then we have find the value of  TEST STATISTIC (or Confidence Interval Structure)

4)- we inform about rejection region as to how the test will be used to reject of fail to reject the null hypothesis and the critical value for making the determination.

5)- CALCULATIONS of Actual test statistic measure

6)- CONCLUSIONS includes Statement of results or the acceptance, or rejection of the null hypothesis .

#  we reject the null hypothesis because the test statistic falls in the rejection region. generally we state null and alternative hypothesis in such a way that we want to prove alternative hypothesis true and we try to always reject null hypothesis. if null hypothesis is rejected this means our assumption or estimated result is true.

# Statistical significance refers to the unlikelihood that the result is obtained by chance, i.e., probability of relationship between two variables exists. and Practical significance is defined as the relationships between variables of the real-world applications.

# in one-tailed test , the critical area of a distribution is one-sided so that it is either greater than or less than a certain value, but not both.

and in two tailed test , region of rejection is on both sides of the sampling distribution .

one-tailed test is more powerful than a two-tailed test, as you aren't considering an effect in the opposite direction. we use two tailed test more preferably because  two-tailed test will test both if the mean is significantly greater than x and if the mean significantly less than x.

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