Quant: Understanding Variance

If you looked at a measure of job performance resulting from 2 different manufacturing processes and found that the mean performance of process A was 82.5 and the mean performance of process B was 78.5, why can you not automatically assume that process A will consistently outperform process B?

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If a researcher were to look at a measure of job performance resulting from 2 different manufacturing processes and found that the mean performance of process A was 82.5, and the mean performance of process B was 78.5, they could not automatically assume that process A will consistently outperform process B.  The reason the researchers cannot come to a conclusion until an analysis of variance done to that data.  There could be variance between the types of the statement of work that is uniquely different and are required between process A and process B (within-group variance), and there could be variances between the groups of people conducting the statement of work (between group variance).  These two types of variances will feed into the F-statistic result which would allow the researcher to state then whether or not they can reject the null hypothesis that the means between both mean performances are the same.

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