Based on 2017 sales the six top selling compact cars are the...

Based on 2017 sales, the six top-selling compact cars are the Honda Civic, Toyota Corolla, Nissan Sentra, Hyundai Elantra, Chevrolet Cruze, and Ford Focus.† The 2017 market shares are: Honda Civic 20%, Toyota Corolla 17%, Nissan Sentra 12%, Hyundai Elantra 10%, Chevrolet Cruze 10%, and Ford Focus 8%, with other small car models making up the remaining 23%. Suppose a sample of 400 compact car sales in a certain large city showed the following number of vehicles sold. Honda Civic99Toyota Corolla73Nissan Sentra55Hyundai Elantra45Chevrolet Cruze41Ford Focus24Others63 Use a goodness of fit test to determine if the sample data indicate that the market shares for compact cars in the city are different than the market shares suggested by nationwide 2017 sales. Use a 0.05 level of significance.

Transcript

00:01 Hi, i'm david and i'm here to help you answer your question.

00:03 In the question here we are going to discuss about the high -partice testing.

00:07 I want to perform the goodness of fit test.

00:11 And here we want to test the known hypothesis that the proportion for the honda civic and we put it as a p1, it will equal to the 20%.

00:22 And then the p2 for the tudjetat kurala will be the 17%.

00:28 And for the nissan p3 equal to the 0 .12, the p4, it will be for the hyundai, 10%.

00:39 And the p5, it will be for the chevrette, equal to the 10%.

00:45 And the p6 for the fault, it will be the 8%.

00:51 And from the others, p7, it will equal to the 23%.

00:56 And then we're given the table of the frequency, so let me pick it up here, and let me make it bigger.

01:08 From the table of the frequency, i will call this column here will be the observed value.

01:14 And then the next time i will compute the expected value denoted by the e.

01:19 Now to find expected count, i need to find the total.

01:23 So if we add up everything, i will get this one equal to the 400.

01:29 And then we can find expected count for the honda civic.

01:32 I will tend the 200.

01:34 We time with the corresponding probability 0 .12.

01:38 Then we get equal to the 200 times 0 .12 equal to the 40.

01:44 The next one retent the 200 times under 0 .17.

01:49 Then we get 200 times 0 .17 equal to the 34.

01:55 This one will tend to 200, this one say 400, not the 200.

01:59 And make a mistake here.

02:01 So this one will be equal to the 80.

02:04 This isn't with 400 times under 0117 equal to the 68.

02:11 This isn't with the 400 times with the 0 .112 and then 400 times 112 equal to the 48.

02:21 400 times with the 011, then get equal to the 40, then 400 times with the 7 1 again.

02:30 Get equal to the 40 and then 400 times under 0108 then get the 400 times 0108 equal to the 32 and then 400 times under 0123 equal to the 92 and when we have that we should be able to find the test statistics denoted by the k square the formula will be the summation the observed value expected value so divided by the expected value.

03:08 So we have the first pair here...

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