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Sauron [17]
3 years ago
8

In a job interview, the interviewer is not the only one who should ask

Social Studies
1 answer:
Digiron [165]3 years ago
3 0

I would say b, 6-8 ><

I hope this helped ^^

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Is sulfur dioxide ionic or molecular
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Molecular because sulfur and oxygen are both nonmetals

Explanation:

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<span>The term used when union workers refuse to work due to contractual disagreements is B. Strike. Labor strikes are often organized protests against contractual disagreements between employees and employers. Strikes involve mass refusal to work to makea bigger impact. Employees usually stop their strikes when an agreement or compromise has been met.</span>
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When one changes the significance level of a hypothesis test from 0.01 to 0.05, which of the following will happen? Check all th
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Answer:

B) The chance of committing a Type I error changes from 0.01 to 0.05., E) The test becomes less stringent to reject the null hypothesis (i.e., it becomes easier to reject the null hypothesis), therefore. C) It becomes harder to prove that the null hypothesis is true and G) The chance that the null hypothesis is true changes from 0.01 to 0.05 are all correct answers

Explanation:

The alfa error or type I, refers to the probability error of rejecting the null hypothesis, when it is true, it is the chance of mistake when affirming that an association exists between two variables tested as a cause of an effect on something. i.e: H1: fast food is responsible for diabetes (this is working hypothesis), H0: red hair is responsible for diabetes (this is the null hypothesis). The beta error or type II is related to the size of the sample, it is the chance of accepting something (the null hypothesis) when it is false, depends mostly on having enough measures (or persons under study) so your hypothesis can be proven and be a real representation of the population under study. The statistical significance, namely the p value, can be narrow (p=0.01) or wide (p=0.05), it can be easily understand if we explain it in terms of percentage: you can have 99% (p=0.01) of certainty to affirm that the null hypothesis (the one that you do not believe is true, in the example, red hair as cause of diabetes) is actually wrong or 95% (p=0.05) of certainty to affirm that the null hypothesis (again, the one that you do not believe is true) is actually wrong.

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