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Bess [88]
4 years ago
14

Two teachers compared the mean absolute deviation of the scores from the semester exam they gave to their students. Mrs. Alvarez

's scores had a lower mean absolute deviation than Mr. Crawford's scores. What can we conclude? * 10 points A. Mrs. Alvarez's scores were lower than Mr. Crawford's scores. B. Mrs. Alvarez's scores were more spread out than Mr. Crawford's scores. C. Mrs. Alvarez's scores were less spread out than Mr. Crawford's scores. D. Mrs. Alvarez's scores were higher than Mr. Crawford's scores.
Mathematics
1 answer:
Monica [59]4 years ago
3 0

Answer:

C. Mrs. Alvarez's scores were less spread out than Mr. Crawford's scores.

Step-by-step explanation:

Mean Absolute Deviation is one of the Statistical measures which we can you to determine the variation that exist amongst a given set of data

Mean Absolute Deviation can be defined as how far or the distance between one set of data to another set of data.

The smaller the Mean Standard Deviation, the lower the degree of variation in the set of data. The data is less spread out

The larger the Mean Standard Deviation, the higher the degree of variation in the set of data. The data is Largely spread out

We are told in the question that:

Mrs. Alvarez's scores had a lower mean absolute deviation than Mr. Crawford's scores. Our conclusion would be that Mrs. Alvarez's scores were less spread out than Mr. Crawford's scores.

Option 2 is correct.

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A food distributor is being sued for racial discrimination because 12% of newly hired candidates are not white when 53% of all a
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Answer:

Check Explanation

Step-by-step explanation:

A) The null hypothesis would be that the proportion of newly hired candidates that are not white is not significantly different from the proportion of the applicants that are not white & there is no significant evidence that the company's hiring practices are discriminatory.

Mathematically,

H₀: μ₀ = 0.53

And the alternative hypothesis would be that there is a significant difference between the proportion of newly hired candidates that are not white is not significantly different from the proportion of the applicants that are not white. More specifically, that the proportion of newly hired candidates that are not white is significantly less than the proportion of applicants that are not white & there is significant evidence that the company's hiring practices are indeed discriminatory.

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B) The two errors that can come up in this hypothesis testing include -

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Type II error: We accept the null hypothesis (fail to reject the null hypothesis) because we obtained that there is no significant difference between the proportion of newly hired candidates that are not white & th proportion of applicants that are not white and conclude that there is no discrimination in the company's hiring practices when in reality, there is significant difference in the stated proportions above and significant evidence that there is indeed significant evidence that the company's hiring practices are discriminatory.

C) The power of the test increases as the significance level reduces. This is because t-statistic increases as significance level reduces.

D) The standard error of the mean used in computing the t-score is given as

σₓ = (σ/√n)

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Hope this Helps!!!

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