Statistics, testing hypothesis

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SUMMARY

The discussion focuses on hypothesis testing in statistics, specifically addressing the scenario where the sample mean (Xaverage) equals the population mean (MUo). When Xaverage is 0.1 and MUo is also 0.1, the test statistic equals zero, leading to a p-value of 1 in a two-tailed test. This indicates that the null hypothesis should not be rejected, as the p-value exceeds the common alpha level of 0.05, confirming the null hypothesis.

PREREQUISITES
  • Understanding of hypothesis testing concepts
  • Familiarity with p-values and alpha levels
  • Knowledge of null and alternative hypotheses
  • Ability to interpret Z-scores and statistical charts
NEXT STEPS
  • Study the implications of p-values in hypothesis testing
  • Learn about the significance levels and their impact on hypothesis acceptance
  • Explore the use of Z-scores in different statistical tests
  • Investigate two-tailed vs. one-tailed tests in hypothesis testing
USEFUL FOR

Students in statistics courses, researchers conducting hypothesis testing, and professionals analyzing data for decision-making will benefit from this discussion.

the_man
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Homework Statement


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Homework Equations


In statistics, when testing hypothesis for both sides (left and right), is it possible that Xaverage - MUo = 0 (upper part of the equation I provided)? If so how to solve this kind of task?

The Attempt at a Solution


If I get Xaverage = 0.1 (exactly) and MUo = 0.1 then test result is equal to 0. How to proceed with this? What is the conclusion? Do we accept Zero Hypothesis or do we reject it?
 
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Of course it is possible. When this happens, it seems to confirm your null hypothesis, doesn't it? Look up the Z value of 0 on the chart, it should be right around .5. That means for a 2-tailed test, there is a p value of 1. Most tests say to let the null hypothesis stand when p < alpha using alpha of .05 or so. 1 is not less than .05.
 

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