Please define the two definitions: 1. The level of significance needed to reject the null hypothesis. It is the maximum allowable probability of false negative, where the null hypothesis is rejected when it is in fact true. 2. This value is set by the investigator of the hypotheses. For example, if you want to be 95% confident in your statistical conclusions, you have a level of significance of 5%. A speculated value for the population average used in the null hypothesis. In a one-sample t-test this is the benchmark value that the sample mean is compared against.
Please define the two definitions: 1. The level of significance needed to reject the null hypothesis. It is the maximum allowable probability of false negative, where the null hypothesis is rejected when it is in fact true. 2. This value is set by the investigator of the hypotheses. For example, if you want to be 95% confident in your statistical conclusions, you have a level of significance of 5%. A speculated value for the population average used in the null hypothesis. In a one-sample t-test this is the benchmark value that the sample mean is compared against.
Chapter9: Sequences, Probability And Counting Theory
Section9.7: Probability
Problem 1SE: What term is used to express the likelihood of an event occurring? Are there restrictions on its...
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Please define the two definitions:
1. The level of significance needed to reject the null hypothesis. It is the maximum allowable probability of false negative, where the null hypothesis is rejected when it is in fact true.
2. This value is set by the investigator of the hypotheses. For example, if you want to be 95% confident in your statistical conclusions, you have a level of significance of 5%.
A speculated value for the population average used in the null hypothesis. In a one-sample t-test this is the benchmark value that the sample mean is compared against.
![Iselect]
e level of significance needed to reject the null hypothesis. It is the maximum allowable probability of false negative, where the null hypothesis is rejected when it is in fact true. This value is set by the
investigator of the hypotheses. For example, if you want to be 95% confident in your statistical conclusions, you have a level of significance of 5%.
0-
A speculated value for the population average used in the null hypothesis. In a one-sample t-test this is the benchmark value that the sample mean is compared against.
51 [select)
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54 null hypothesis
The default hypothesis to be tested. This hypothesis is rejected when the p-value is below the desired level of significance.
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57](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F68cc5e62-1f1e-447e-86e2-72966307f0c4%2Feda7f7b3-11e3-42d9-8e35-d35633b3b059%2Fo9azexb_processed.jpeg&w=3840&q=75)
Transcribed Image Text:Iselect]
e level of significance needed to reject the null hypothesis. It is the maximum allowable probability of false negative, where the null hypothesis is rejected when it is in fact true. This value is set by the
investigator of the hypotheses. For example, if you want to be 95% confident in your statistical conclusions, you have a level of significance of 5%.
0-
A speculated value for the population average used in the null hypothesis. In a one-sample t-test this is the benchmark value that the sample mean is compared against.
51 [select)
52
53
54 null hypothesis
The default hypothesis to be tested. This hypothesis is rejected when the p-value is below the desired level of significance.
55
56
57
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