During the first 13 weeks of the television season, the Saturday evening 8:00 P.M. to 9:00 P.M. audience proportions were recorded as ABC 29% , CBS 27%, NBC 25% , and Independents 19% . A sample of homes two weeks after a Saturday night schedule revision yielded the following viewing audience data: ABC 95 homes, CBS 63 homes, NBC 86 homes, and Independents 56 homes. Test with to determine whether the viewing audience proportions changed.Find the test statistic (Round your test statistic to two decimal places. Use Table 3 of Appendix B.)&nbsp;Test statistic =&nbsp;&nbsp;

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During the first 13 weeks of the television season, the Saturday evening 8:00 P.M. to 9:00 P.M. audience proportions were recorded as ABC 29% , CBS 27%, NBC 25% , and Independents 19% . A sample of homes two weeks after a Saturday night schedule revision yielded the following viewing audience data: ABC 95 homes, CBS 63 homes, NBC 86 homes, and Independents 56 homes. Test with to determine whether the viewing audience proportions changed.Find the test statistic (Round your test statistic to two decimal places. Use Table 3 of Appendix B.)&amp;nbsp;Test statistic =&amp;nbsp;&amp;nbsp;

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We can use a chi-squared goodness-of-fit test to determine whether the viewing audience proportions have changed after the schedule revision. The null hypothesis is that the proportions have not changed, while the alternative hypothesis is that they have changed.First, we need to calculate the expected number of homes for each network based on the proportions during the first 13 weeks. The total number of homes in the sample is 95 + 63 + 86 + 56 = 300.- Expected number of homes for ABC: 0.29 * 300 = 87- Expected number of homes for CBS: 0.27 * 300 = 81- Expected number of homes for NBC: 0.25 * 300 = 75- Expected number of homes for Independents: 0.19 * 300 = 57Next, we can calculate the chi-squared test statistic using the formula:χ2=∑i=1k(Oi−Ei)2Eiwhere Oi is the observed number of homes for network i, Ei is the expected number of homes for network i, and k is the number of networks (4 in this case).Plugging in the values, we get:χ2=(95−87)287+(63−81)281+(86−75)275+(56−57)257=7.31Using Table 3 of Appendix B with k−1=3 degrees of freedom and a significance level of 0.05, the critical value is 7.815.Since the test statistic of 7.31 is less than the critical value of 7.815, we fail to reject the null hypothesis. We can conclude that there is not enough evidence to suggest that the viewing audience proportions have changed after the schedule revision.

During the first 13 weeks of the

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