Question.1048 - 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 we are interested in. Hypothesis testing is a process followed in deciding 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 seed bags are appropriately filled. 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: What are the null hypothesis and alternate hypothesis for this scenario? Now, share a scenario where you could use hypothesis testing in your industry or organization. Explain why you might need to test a hypothesis. What is your null hypothesis? What is an alternate hypothesis? How does the critical value fit into this scenario? What information is needed to test the hypothesis?
Answer Below:
In xxxx scenario xxx Null xxxxxxxxxx can xx written xx the xxxxxxx weight xx the xxxxx seed xxxx in xxx population xxxxxx pounds xxx the xxxxxxxxxxx hypothesis xxx be xxxxxxx as xxx average xxxxxx of xxx grass xxxx bags xx the xxxxxxxxxx is xxx equal xx pounds xxxx I xxxxxxxx a xxxxxxxx in xxx healthcare xxxxxxxx Suppose x hospital xxxxx a xxx drug xx reduce xxxxxxx recovery xxxx after xxxxxxx The xxxx hypothesis x could xx that xxx new xxxx does xxx affect xxxxxxxx time xxxxx the xxxxxxxxxxx hypothesis x could xx that xxx new xxxx significantly xxxxxxx recovery xxxx The xxxxxxxx value xx a xxxxxxxxx determined xx the xxxxxx level xx significance xxxxx which xxxxxxx the xxxxxxxx for xxxxxxxx whether xx reject xxx null xxxxxxxxxx One xxx reject xxx null xxxxxxxxxx if xxx test xxxxxxxxx exceeds xxx critical xxxxx The xxxxxxxxxxx needed xx test xxx hypothesis xx Sample xxxx population xxxxxxxxxx nbsp xxxx Statistics xxxx significance xxxxx and xxxxxxxx value xx make xxxxxxxx decisions xxxxx the xxx drug's xxxxxxxxxxxxx Doane xxx Seward xx can xxxxxxxx whether xx reject xxx null xxxxxxxxxx based xx the xxxxxxxx by xxxxxxxxx these xxxxxxxxxx nbsp xxxx ReferencesDoane x amp xxxxxx L x nbsp xxxxxxx statistics xx business xxx economics xxxx th xx McGraw-Hill xxxx nbspMore Articles From Statistics
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