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Exhibit 13

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Exhibit 13.5 A police chief wants to determine if crime rates are different for four different areas of the city (East(1) ,West(2) ,North(3) ,and South(4) sides) ,and obtains data on the number of crimes per day in each area.The one-way ANOVA table and Tukey's confidence intervals are shown below. Exhibit 13.5 A police chief wants to determine if crime rates are different for four different areas of the city (East(1) ,West(2) ,North(3) ,and South(4) sides) ,and obtains data on the number of crimes per day in each area.The one-way ANOVA table and Tukey's confidence intervals are shown below.     Refer to Exhibit 13.5.At the 1% significance level,the conclusion for the hypothesis test is: A) Reject the null hypothesis,not all mean number of crimes are equal B) Do not reject the null hypothesis,not all mean number of crimes are equal C) Reject the null hypothesis,cannot conclude that not all mean number of crimes are equal D) Do not reject the null hypothesis,cannot conclude that not all mean number of crimes are equal Exhibit 13.5 A police chief wants to determine if crime rates are different for four different areas of the city (East(1) ,West(2) ,North(3) ,and South(4) sides) ,and obtains data on the number of crimes per day in each area.The one-way ANOVA table and Tukey's confidence intervals are shown below.     Refer to Exhibit 13.5.At the 1% significance level,the conclusion for the hypothesis test is: A) Reject the null hypothesis,not all mean number of crimes are equal B) Do not reject the null hypothesis,not all mean number of crimes are equal C) Reject the null hypothesis,cannot conclude that not all mean number of crimes are equal D) Do not reject the null hypothesis,cannot conclude that not all mean number of crimes are equal Refer to Exhibit 13.5.At the 1% significance level,the conclusion for the hypothesis test is:


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