Friday, June 14, 2019

Minitab work Assignment Example | Topics and Well Written Essays - 500 words

Minitab work - Assignment ExampleReport your conclusion clearly.In an look into to investigate the effect of fertiliser on mean yield of an arable crop, 20 different eyepatchs were employ. Fertiliser A was applied to 10 randomly plot and B was applied to the remaining plots .After a specified time, the yield (in coded units) for each plot was measured giving the following datai)Perform an F shew to chew the fat whether assumption of equal variances in the two fertiliser yield group is bonny .To three decimal places, what is the p value from this F leaven? is it reasonable to assume that the two fertiliser yields have equal varianceii)Assuming that the F test suggest that we can pool the variances ,perform a hypothesis test to test whether in that location is significant difference in fertiliser mean yields (using a two sample t test with pooled variance). What is the value of the t-statistic? What is the value of the pooled variance used in this test ?To three decimal places, what is the p value from the test? Is there evidence to reject the null hypothesis of no difference in means at 5% significance level?iii)Suppose that instead of the data arising from 20 different plots, there were in fact only 10 plots ,each of which was dual-lane into 2 subplots. For each plot, Fertliser A was applied to randomly selected subplot and fertiliser B was applied to other subplot.Perform an appropriate hypothesis test to see whether there is evidence that the average difference between the yield from Fertiliser A and B is not zero .To three decimal places, what is the p value from the test? Is there evidence to reject the null hypothesis that the average of the differences is zero, t the 5%signifcance level?Condition x is a medical condition from which 70% of people recover within 7 days if left untreated. The health service would like to increase this proportion by treating sufferers .An experiment was, therefore, conducted to test a new drug

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