see the attachment

Suppose a researcher is interested determining whether on average, driving times on the major traffic routes are approximately the same. The following data are randomly collected from three major traffic routes.The entries in the table are drivings times in minutes on the these routes. A One-Way ANOVA test was conducted at a 0.05 level of significance. The results are shown below. Note that some values in the table might be in scientific notation. Say, 1.65E-07 means 1.65x10'7 or 0.000000165. ANOVA: Single Factor S UMMARY Groups Count Sum Average Variance Route 1 20 1073 53.650 3.502632 Route 2 10 541 54.100 3.433333 Route 3 15 794 52.933 3.495238 ANOVA Source of SS df MS F P-value F crit Variation Between 8.86111 2 4.43056 1.2712 0.291064 3.21994 Groups Within 146.38333 42 3.48532 Groups Total 155.24444 44 Based on the Excel output, what conclusion can the researcher arrive? 0 At the 0.05 level of significance,there is not sufficient sample evidence to support the claim that there is a difference in the average driving times. On average, the driving times are approximately the same. 0 For 0.05 level of significance the ANOVA test shows the sample means and the sample variances, but fails to answer the question whether different traffic routes affect the average driving times. Probably, the researcher should increase the sample sizes. 0 For 0.05 level of significance the ANOVA test is unable to give positive or a negative answer to the question whether different traffic routes affect the average driving times. The question needs futher investigation. 0 At the 0.05 level of significance, the sample data support the claim that there is a difference in the average driving times. On average,the driving times on the major traffic routes are not the same. 0 None of the above