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Question

(Use Excel) Color coding is often used in manufacturing operations to display production status or to identify/prioritize materials. For example, suppose "green" status indicates that an assembly line is operating normally, "yellow" indicates it is down waiting on personnel for set up or repair, "blue" indicates it is down waiting on materials to be delivered, and "red" indicates an emergency condition. Management has set realistic goals whereby the assembly line should be operating normally 80% of the time, waiting on personnel 9% of the time, waiting on materials 9%9 \% of the time, and in an emergency condition 2% of the time. Based on 250250 recent status records, the status was green 185185 times, yellow 2424 times, blue 3232 times, and red 99 times.

a. State the appropriate null and alternative hypotheses to test if the proportions of assembly line statuses differ from the goals set by management.

b. Calculate the value of the test statistic.

c. Use Excel's CHISQ.DIST.RT function to calculate the pp-value.

d. Are management's goals being met at α=0.05\alpha=0.05 ? Will your conclusion change at α=0.01\alpha=0.01 ?

Solution

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a.)\bold{a.)} The null hypothesis states that

H0:The assembly line status proportions don’t differ from the management goals.H_0:\text{The assembly line status proportions don't differ from the management goals.}

so the alternative hypothesis will be the opposite.

HA:The assembly line status proportions differ from the management goals.H_A:\text{The assembly line status proportions differ from the management goals.}

The predicted values is equal to the proportion multiplied to nn. So in Mathematical terms, the null hypotheses is

H0:p1=0.80,p2=0.09,p3=0.09,p4=0.02.H_0: p_1=0.80, p_2=0.09, p_3=0.09, p_4=0.02.

and the Alternative hypotheses is

Ha:p10.80 or p20.09 or p30.09 or p30.02.H_a: p_1\ne0.80 \text{ or } p_2\ne0.09 \text{ or } p_3\ne0.09 \text{ or } p_3\ne0.02.

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