Here is what I got:
•Mean is 49.13
•Standard deviation is 1.74
•Null hypothesis is PM = 50 bags
over filled
•Alternative hypothesis is < 50 bags over filled significance level a = 0.05 = 1.729133 test statistic -2.232 From what the statistics are showing I would state that bags are being underfilled. With the product being underfilled, the grass feed are not meeting the fifty-pound weight requirement as they should be. The first thing I would do is recalibrate the machinery since there is an inconsistency of bags underfilled and seesaw type effect of below fifty and over fifty pounds. If we look at the mean, 49.13, the mean shows the bags were not being filled correctly as well.


Doane, D. P., Seward, L. E. (2019). Applied Statistics in Business and Economics. McGraw Hill Education (6).

Kalya wrote

Hello class,

Here is what I got:
•Mean is 49.13
•Standard deviation is 1.74
•Null hypothesis is PM = 50 bags over filled
•Alternative hypothesis is < 50 bags over filled significance level a = 0.05 = 1.729133 test statistic -2.232 · What is the decision rule? In statistics, a decision rule is mainly known as a statement in which tells or shows the right circumstances to basically reject the null hypothesis. When setting up the decision rule, the first step is most certainly stating the hypothesis and next you have to figure basically if is a one-tailed or a two tailed test and also the test statistic must be calculated as well. · Should machinery be recalibrated? I think that it is important to recalibrate equipment and mainly because it can most certainly be helpful or useful when it comes to definitely knowing the main accurate measurements and even production of quality products with both reduced errors and even the recalls as well. On another note, the machinery should most certainly be calibrated at least every two weeks.




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