A manufacturing company produces part 2205 for the aerospace industry. This particular part can be manufactured using 3 different production processes. The management wants to know if the quality of the units of part 2205 is the same for all three processes. The producion supervisor obtained the following data: The Process 1 had 29 defective units in 240 items; Process 2 produced 12 defective units in 180 items and Process 3 manufactured 9 defective units in 150 items. Chi-square Contingency Table Test for Independence                                              Col 1           Col 2           Col 3           Total         Row 1 Observed     29                12                9                  50                        Expected      21.05           15.79           13.16           50.00                   (O - E)² / E  3.00             0.91             1.31             5.22          Row 2 Observed     211              168              141              520                      Expected      218.95         164.21         136.84         520.00                             (O - E)² / E  0.29             0.09             0.13             0.50          Total   Observed     240              180              150              570                      Expected      240.00         180.00         150.00         570.00                             (O - E)² / E  3.29             1.00             1.44             5.73                                                                                                                                         5.73             chi-square                                                            .0571           p-value  At a significance level of .05, the management wants to perform a hypothesis test to determine if the quality of the items produced appears to be independent of the production process used. Based on the results summarized in the  output provided in the table above, we:     Reject H0 and conclude that the quality of the product is not the same for all processes.     Reject H0 and conclude that the quality of the product is dependent on the manufacturing process.     Fail to reject H0 and conclude that the quality of the product does not significantly differ among the three processes.     Fail to reject H0 and conclude that the quality of the product is not the same for all processes.     Reject H0 and conclude that the quality of the product is independent of the manufacturing process used.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.6: Summarizing Categorical Data
Problem 27PPS
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1. A manufacturing company produces part 2205 for the aerospace industry. This particular part can be manufactured using 3 different production processes. The management wants to know if the quality of the units of part 2205 is the same for all three processes. The producion supervisor obtained the following data: The Process 1 had 29 defective units in 240 items; Process 2 produced 12 defective units in 180 items and Process 3 manufactured 9 defective units in 150 items.


Chi-square Contingency Table Test for Independence         

                                    Col 1           Col 2           Col 3           Total    

    Row 1 Observed     29                12                9                  50        

               Expected      21.05           15.79           13.16           50.00   

               (O - E)² / E  3.00             0.91             1.31             5.22     

    Row 2 Observed     211              168              141              520      

               Expected      218.95         164.21         136.84         520.00             

               (O - E)² / E  0.29             0.09             0.13             0.50     

    Total   Observed     240              180              150              570      

               Expected      240.00         180.00         150.00         570.00             

               (O - E)² / E  3.29             1.00             1.44             5.73     

                                                                                              

                                    5.73             chi-square                       

                                    .0571           p-value 

At a significance level of .05, the management wants to perform a hypothesis test to determine if the quality of the items produced appears to be independent of the production process used. Based on the results summarized in the  output provided in the table above, we:

   

Reject H0 and conclude that the quality of the product is not the same for all processes.

   

Reject H0 and conclude that the quality of the product is dependent on the manufacturing process.

   

Fail to reject H0 and conclude that the quality of the product does not significantly differ among the three processes.

   

Fail to reject H0 and conclude that the quality of the product is not the same for all processes.

   

Reject H0 and conclude that the quality of the product is independent of the manufacturing process used.

 

2. A real estate company is analyzing the selling prices of residential homes in a given community. 140 homes that have been solved in the past month are randomly selected and their selling prices are recorded. The statistician working on the project has stated that in order to perform various statistical tests, the data must be distributed according to normal distribution. In order to determine whether the selling prices of homes included in the random sample are normally distributed, the data is divided into 6 classes of equal size and the number of observations in each class is recorded. The chi-square goodness of fit test for normal distribution is performed and the results are summarized in the following table:

 

Goodness of Fit Test

 

     Observed     expected      O - E             (O - E)² / E    % of chisq

    10                  3.192             6.808             14.520           64.81        

    23                  19.026           3.974             0.830             3.70          

    37                  47.782           -10.782          2.433             10.86        

    40                  47.782           -7.782            1.267             5.66          

    27                  19.026           7.974             3.342             14.92        

    3                    3.192             -0.192            0.012             0.05          

    140                140.000         0.000             22.404           100.00      

                                                                                               

            22.40   Chi-square

            .0001   p-value

What is the appropriate null hypothesis?

   

H0: The residential home selling prices are distributed according to normal distribution.

   

H0: The residential home selling prices are not distributed according to normal distribution.

   

H0: The distribution of residential home selling prices is either right or left skewed.

   

H0: The distribution of the residential home selling prices is symmetric.

   

None of the above is correct.

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