The American Society for Quality (ASQ) conducted a salary survey of all its members. ASQ members work in all areas of manufacturing and service-related institutions, with a common theme of an interest in quality. Two job titles are black belt and green belt. These titles are used in a company following a Six Sigma quality improvement initiative approach.) Descriptive statistics concerning salaries for these two job titles are given in the following table: Job Title Sample Size Mean Standard Deviation Black Belt 219 87,342 20,955 Green Belt 34 65,679 18,137 a. Assume a 0.05 level of significance. Is there an evidence of a difference in the variability of salaries between black belts and green belts? b. Based on the result of (a), which t test defined in the Section for 2-sample tests Comparing the Means of Independent Populations is appropriate for comparing mean salaries? c. Using a 0.05 level of significance, is there a difference between the mean salary of black belts and green belts?

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Q: How do I solve this?

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Q: How do you solve this problem?

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Q: can you solve g, h, and j too please?

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Q: How do I solve this ?

A: GIVEN: 6 - x - x2  if x ≤ 32x - 5         if x > 3

Q: what is the solution

A: The series diverges.

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A: Basic concept of discrete probability distribution are used

Q: Hey can you show the solution in a piece of paper or some sort of visual?

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Q: How do I solve this ?

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Q: how about part D, how to solve that?

A: The information provided in the question are as follows :-…

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Q: how do i solve this?

A: Given that: The table ,

Q: could you solve the second question as well

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A: It's a platform where students ask questions regarding their homework.

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Q: could you please work the solution out on paper please?

A: The given integral is cos4x.

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Types of Bias

Statistics is the study of data collection, organization, analysis, interpretation, and presentation. Statistical bias is a characteristic of a statistical technique or its findings in which the expected value deviates from the actual root quantitative parameter being estimated. According to the actual definition of bias, it refers to the tendency of a statistic to overestimate or underestimate a parameter.