2-Proportion Z-Test (Hypothesis Testing) (TI-83 & TI-84)

In this video we are going to see how to evaluate the Z-teststatistic and p-value for the 2 share Z-experiment. The instructional materials for theTI-eighty three and eighty four are equal. And we are going to with this example, the identical one we used for thetwo percentage Z-interval. Just to summarize the obstacle,we’ve got a current supplier and now we have a prospective provider. And we need to be aware of is there evidence that the potential supplier has a bigger rate of passing the inspection considering in the event that they can we’regoing to move with them. So our null hypothesis isthat the true proportions that might move inspection arethe same for the 2 businesses and our alternate hypothesis, the one we’re seeking to seeif there’s proof for, is that the prospectivesupplier has a bigger fee of passing inspectionthan the current provider. So, first we supply out the initial steps. We set our significance degree alpha, we must expect that there’s two unbiased,random samples here. And now, specific from when we did the 2 proportionZ-interval, we’re going to look at this quantity, which isthe pooled share, p-hat. And the intent for this isbecause now we have a null claim that says that the p1 equals p2.So in a similar fashion to when we didthe one proportion Z-experiment and we had a hypothesized price for p, we use that hypothesized valuein checking our conditions and in calculating the SE. So here what we’re going todo is use our pleasant estimate for what this percentage thatthese two equal perhaps. And so our great estimate for that’s to mix our two pattern proportions. And we do this with the aid of addingthe whole quantity of yeses over the total pattern size and here we get 0.9285. So this quantity we’ll use after we verify our conditionsand we’re additionally going to make use of it within the SE formula. So right here we’ve got ourn1[p-hat], n1[1 minus p-hat] n2[p-hat] and n2[1 minus p-hat] are all bigger than or equal to 10. And now when we calculate our SE, we have to go to the system sheet and we’re looking at thedifference of sample proportions and now we have this specialcase the place p1 equals p2.This is our null speculation. So due to the fact now we have this hypothesis right here, we will use thisstructure written right here for our SE. So we now have p-hat here, 1minus p-hat, et cetera. So we fill in the numbers, and now we’re competent tograb the calculator. So, we consistently begin with STAT, checks, and this time we’re goingto go to 2-PropZTest. So let’s go to STAT, exams,and to find 2-PropZTest. 2-PropZTest, here it is. So x1 is 899, n1 is thesample measurement of one thousand, x2 is 958, remember x1 andx2 must be integers. Of direction, n1 and n2 haveto be integers as well. So n2 can also be 1000. And now our alternate claimis that p1 is less than p2, so we are going to choose the lower than and now we are going to do Calculate. And we see we get a Z-ranking of -5.12 and a p-worth very, very small.Realize this also gives youp-hat, the pooled proportion. So here is our .9285, whichis what we calculated here and so they fit. So what’s our conclusion? Our p-price is way less than alpha, so we reject H sub zero,we’ve evidence that the prospective provider hasa bigger authentic pass inspection than the present provider, so we should go along with theprospective supplier. That is it for this video, when you liked it give it athumbs up and subscribe under. Thanks for staring at..

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