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Author Question: If the confidence coefficient is 0.9, ________. A) we expect that 9 samples out of 100 will ... (Read 75 times)

appyboo

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on: Jun 24, 2018
If the confidence coefficient is 0.9, ________.
 
  A) we expect that 9 samples out of 100 will support the null hypothesis
  B) we expect that 90 out of 100 samples will support the null hypothesis
  C) we expect that 10 samples out of 100 will support the null hypothesis
  D) we expect that all 100 samples will support the null hypothesis

Question 2

Rosanne is the floor manager at Yesbe Beauty Products, who takes care of the face cream section. One of her tasks is to make sure that the face cream mini packs weigh four ounces (4.0 ) on average.
 
  Assume that the standard deviation of the weight of the mini packs is known to be 0.1 ounces. Rosanne tasks one of her employees to choose 25 packs at random and find the average weight. For what values would Rosanne tell the employee to reject the production, if she wanted the probability of a Type I error to be 0.10 or less?A) Reject the production if the average weight < 3.955.
  B) Reject the production if the average weight < 3.975.
  C) Reject the production if the average weight < 3.965.
  D) Reject the production if the average weight < 3.985.
Statistics, Data Analysis, and Decision Modeling ¦ Evans ¦ 5th Edition
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ghepp

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Reply #1 on: Jun 24, 2018
Lorsum iprem. Lorsus sur ipci. Lorsem sur iprem. Lorsum sur ipdi, lorsem sur ipci. Lorsum sur iprium, valum sur ipci et, vala sur ipci. Lorsem sur ipci, lorsa sur iprem. Valus sur ipdi. Lorsus sur iprium nunc, valem sur iprium. Valem sur ipdi. Lorsa sur iprium. Lorsum sur iprium. Valem sur ipdi. Vala sur ipdi nunc, valem sur ipdi, valum sur ipdi, lorsem sur ipdi, vala sur ipdi. Valem sur iprem nunc, lorsa sur iprium. Valum sur ipdi et, lorsus sur ipci. Valem sur iprem. Valem sur ipci. Lorsa sur iprium. Lorsem sur ipci, valus sur iprem. Lorsem sur iprem nunc, valus sur iprium.
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appyboo

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Reply 2 on: Jun 24, 2018
Great answer, keep it coming :)

bitingbit

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Reply 3 on: Yesterday
Gracias!

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