What information is needed to test the hypothesis

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Reference no: EM133618410

Discussion Post: Practical Uses for Hypothesis Testing

A production manager can use hypothesis testing to test assumptions and theories. These assumptions are tested against evidence provided by actual, observed production data. A statistical hypothesis is a statement about the value of a population parameter that we are interested in. Hypothesis testing is a process followed to arrive at a decision between 2 competing, mutually exclusive, collective exhaustive statements about the parameter's value.

An industrial seller of grass seeds packages its product in 50-pound bags. The production manager is responsible for ensuring the packages contain the amount of product they are supposed to. As part of routine quality assurance, the production manager randomly samples a batch of 9 bags to determine if the bags of seed are properly filled or not.

Watch "Hypothesis Testing Basics" from LinkedIn Learning and "Defining Hypotheses" by Lori Seward in this week's learning activities before responding to this discussion.

Review the weight of the samples in the following table. You may also view the sample weights in Excel, if desired.

Sample Weight (pounds)
1 49.5
2 45.6
3 46.7
4 47.7
5 47.6
6 48.8
7 50.5
8 48.6
9 50.2

Respond to the following:

Question A. What is the null hypothesis and alternate hypothesis for this scenario?

Question B. Now, share a scenario where you could use hypothesis testing in your industry or organization. Explain why you might need to test a hypothesis.

Question C. What is your null hypothesis?

Question D. What is alternate hypothesis?

Question E. How does the critical value fit into this scenario?

Question F. What information is needed to test the hypothesis?

Reference no: EM133618410

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