42. Nylon bars were tested for brittleness (Bennett and Franklin 1954). Each of 280 bars was molded under similar conditions and was tested in five places. Assuming that each bar has uniform...


42. Nylon bars were tested for brittleness (Bennett and Franklin 1954). Each of 280<br>bars was molded under similar conditions and was tested in five places. Assuming<br>that each bar has uniform composition, the number of breaks on agiven bar should<br>be binomially distributed with five trials and an unknown probability p of failure.<br>If the bars are all of the same uniform strength, p should be the same for all of<br>them; if they are of different strengths, p should vary from bar to bar. Thus, the<br>null hypothesis is that the p's are all equal. The following table summarizes the<br>outcome of the experiment:<br>Breaks/Bar Freuency<br>157<br>69<br>35<br>17<br>0<br>4<br>a. Under the given assumption, the data in the table consist of 280 observations<br>of independent binomial random variables. Find the mle of p.<br>b. Pooling the last three cells, test the agreement of the observed frequency<br>distribution with the binomial distribution using Pearson's chi-square test.<br>

Extracted text: 42. Nylon bars were tested for brittleness (Bennett and Franklin 1954). Each of 280 bars was molded under similar conditions and was tested in five places. Assuming that each bar has uniform composition, the number of breaks on agiven bar should be binomially distributed with five trials and an unknown probability p of failure. If the bars are all of the same uniform strength, p should be the same for all of them; if they are of different strengths, p should vary from bar to bar. Thus, the null hypothesis is that the p's are all equal. The following table summarizes the outcome of the experiment: Breaks/Bar Freuency 157 69 35 17 0 4 a. Under the given assumption, the data in the table consist of 280 observations of independent binomial random variables. Find the mle of p. b. Pooling the last three cells, test the agreement of the observed frequency distribution with the binomial distribution using Pearson's chi-square test.

Jun 01, 2022
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