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. Route 1 Route 2 Route 3 53 53 52 52 55 59 52 53 54 52 55 52 58 53 53 52 52 54 58 56 53 55 53 52 54 5B 53 52 53 52 53 52 52 53 53 52 53 52 52 51 55 55 53 54 55 A One-Way ANDVA test was conducted at a 0.01 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 5 UMMA RY Groups Route 1 20 Count Sum Average 1073 53.650 Variance 3. 502632 Route 2 10 541 54.100 3.433333 Route 3 1 5 AN OVA Source of 55 Variation Between 8.86111 Groups if 794 52.933 MS 4.43056 1.2712 3.495238 P-vaiue 0.29106 F crit 5.14914 Within 146.38333 Groups 42 348532 Total 1 55 .24444 Based on the Excel. output, what conclusion can the researcher arrive? 0 At the 0.01 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 At the 0.01 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 For 0.01 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 For 0.01 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 None of the above