Based on your analysis, at a 10% level of significance, can the professor conclude that there is gender discrimination?

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BlackTom AI · Accepted Answer

Question restatement: Based on your analysis, at a 10% level of significance, can the professor conclude that there is gender discrimination?

Option analysis:
- Option presented: "yes". This single option asserts that there is evidence of gender discrimination when testing at the 0.10 significance level. To evaluate this claim properly, one would typically conduct a statistical hypothesis test with a null hypothesis that there is no gender discrimination (e.g., equal treatment across genders) and an alternative hypothesis that discrimination exists. If the p-value from the test is less than or equal to 0.10, we would reject the null hypothesis and conclude that there is evidence of discrimination at the 10% level; if the p-value is greater than 0.10, we would fail to reject the null. The key here is that the conclusion depends on the observed data and the specific test used (e.g., difference in means, proportions, regression-based analysis, etc.), as well as whether the test meets assumptions (sample size, independence, expected counts, etc.).

What about the lack of answer options? The provided information shows an answer of "yes" but no alternative choices to compare against, which prevents a complete evaluation of the question as a multiple-choice item. In multiple-choice reasoning, we typically weigh each alternative against the data and the statistical result. Without other options to contrast, we cannot assess potential distractors or the relative plausibility of each choice. This omission leaves a gap in understanding which factors might make "yes" the correct or incorrect choice (e.g., if the test statistic did not reach significance, or if multiple comparisons were not accounted for).

Assuming the test result indeed yielded a p-value ≤ 0.10 and the analysis was appropriate, the rationale for accepting "yes" would hinge on: (1) the null hypothesis being that there is no gender discrimination, (2) the alternative that discrimination exists, (3) the chosen test aligning with the data type (categorical vs. continuous outcomes), and (4) the data meeting test assumptions. Conversely, if any of these conditions fail (e.g., p-value > 0.10, mis-specified model, small sample size, or multiple testing without correction), the conclusion would be different.

Additional considerations to avoid misleading conclusions include: checking for practical significance in addition to statistical significance, considering confidence intervals around estimated effects, and ensuring the study design properly isolates gender as the factor of interest rather than confounding variables.

In summary, the core idea behind the option "yes" is that the observed evidence at the 10% level supports rejecting the no-discrimination null hypothesis, but this hinges on the actual data, the test performed, the model assumptions, and the presence of other competing choices in the original question, which are not provided here.

OMIS 2050 A & B OMIS 2050 Reinforcement Quiz 10 F25

Based on your analysis, at a 10% level of significance, can the professor conclude that there is gender discrimination?

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OMIS 2050 A & B OMIS 2050 Reinforcement Quiz 10 F25

Based on your analysis, at a 10% level of significance, can the professor conclude that there is gender discrimination?

查看解析

登录即可查看完整答案

类似问题

Which one is true?

For an upper-tail hypotheses about a population mean with σ known and α=5%, which one is the rejection region?

For a given sample, the P-value for upper tail test is x, and the P-value for two-tailed test is y, then

For a two-tailed hypothesis test with a test statistic value of z = 2.09, the p-value is _____.

For a sample size of 30, changing from using the t distribution to using the standard normal distribution in a hypothesis test _____.

Exhibit 9-5 n = 16 H0: μ ≥ 80 = 75.607 Ha: μ < 80 σ = 8.6 Assume the population is normally distributed. Refer to Exhibit 9-5. The p-value is equal to _____.

Exhibit 9-1 ​ ​ Refer to Exhibit 9-1. If the test is done at a .01 level of significance, the null hypothesis should _____.

What conclusion for a test would correctly detect a difference between the actual parameter and the hypothesized value for the parameter? c08.p089.q0008

更多留学生实用工具

希望你的学习变得更简单

Exhibit 9-1 Refer to Exhibit 9-1. If the test is done at a .01 level of significance, the null hypothesis should _____.