The following data were obtained in a study using three separate samples to compare three different treatments. Conduct an analysis of variance (ANOVA) with α=0.05 to determine whether these data are sufficient to conclude that there are significant differences between the treatments. Treatment A Treatment B Treatment C 16 16 17 18 16 19 17 14 21 17 14 19 F-ratio = _______  (3 decimal places) p-value = _________  (3 decimal places

3.18. A manufacturer of television sets is interested in the effect on tube conductivity of four different types of coating for color picture tubes. A completely randomized experiment is conducted and the following conductivity data are obtained: Coating Type 1 234 2 4 143 152 134 129 Conductivity 150 137 132 132 141 149 136 127 146 143 127 129 (a) Is there a difference in conductivity due to coating type? Use a = 0.05. (b) Estimate the overall mean and the treatment effects. (c) Compute a 95 percent confidence interval estimate of the mean of coating type 4. Compute a 99 percent confidence interval estimate of the mean difference between coating types 1 and 4.

The following data represent the results from an independent-measures experiment comparing three treatment conditions. Use StatCrunch to conduct an analysis of variance with a = 0.05 to determine whether these data are sufficient to conclude that there are significant differences between the treatments. Treatment A Treatment B 6 F-ratio= p-value = 4 5 LO 5 5 8 6 7 4 Treatment C 9 7 11 10 13

The following data represent the results from an independent-measures study comparing two treatment conditions. Treatment   I II 10 7 N = 16 8 4 G = 120 7 9 ∑X² = 1036 9 3   13 7   7 6   6 10   12 2   M = 9.000 M = 6.000   T = 72 T = 48   SS = 44 SS = 56     Use an independent-measures t test with α = .05 to determine whether there is a significant mean difference between the two treatments. (Use three decimal places; subtract MIIII from MII.) t-critical = ±   t =       t Distribution Degrees of Freedom = 21             -3.0-2.0-1.00.01.02.03.0t   Conclusion: Fail to reject the null hypothesis; there are significant differences between the two treatments.   Reject the null hypothesis; there are significant differences between the two treatments.   Fail to reject the null hypothesis; there are no significant differences between the two treatments.   Reject the null hypothesis; there are…

The following data represent the results from an independent-measures experiment comparing three treatment conditions. Conduct an analysis of variance with α=0.05α=0.05 to determine whether these data are sufficient to conclude that there are significant differences in the means for the treatments. Treatment A Treatment B Treatment C 16 16 17 15 16 21 15 15 19 15 19 23 14 14 20 F-ratio (F-test statistic) = p-value = Conclusion: There is a significant correlation in the treatments I was able to show the treatments are independent The data does not provide evidence of a significant correlation for the treatments The data does not provide evidence of a significant difference in the means for the treatments I was unable to show the treatments are independent There is a significant difference in the means for the treatments   The results obtained above were primarily due to the mean for the third treatment being noticeably different from the other two sample means.…

The following data represent the results from an independent-measures experiment comparing three treatment conditions. Conduct an analysis of variance with α=0.05 to determine whether these data are sufficient to conclude that there are significant differences between the treatments. Treatment A Treatment B Treatment C 8 10 16 10 9 12 9 10 14 9 8 15 9 13 13 F-ratio = p-value = Conclusion: There is a significant difference between treatments These data do not provide evidence of a difference between the treatments   The results obtained above were primarily due to the mean for the third treatment being noticeably different from the other two sample means. For the following data, the scores are the same as above except that the difference between treatments was reduced by moving the third treatment closer to the other two samples. In particular, 3 points have been subtracted from each score in the third sample.Before you begin the calculation, predict how the…

Refer to the below table. Using an alpha = 0.05, test the claim that IQ scores are the same for children in three different blood lead level groups: low lead level, medium lead level, and high lead level).   One-Way Analysis of Variance Summary Table for IQ Measurements for Children among Three Blood Lead Level Groups: Low Lead Level, Medium Lead Level, and High Lead Level. Source df SS MS F p             Between-group (treatment) 2   469.1827 2677.864 2.30 0.104 Within-group (error)       118    203.6918 11745.05     Total       120

The following data represent the results from an independent-measures experiment comparing three treatment conditions. Conduct an analysis of variance with α=0.05α=0.05 to determine whether these data are sufficient to conclude that there are significant differences in the means for the treatments. Treatment A Treatment B Treatment C 6 4 13 4 6 11 4 9 7 6 6 10 5 5 9 F-ratio (F-test statistic) = p-value = Conclusion: The data does not provide evidence of a significant difference in the means for the treatments There is a significant difference in the means for the treatments I was unable to show the treatments are independent The data does not provide evidence of a significant correlation for the treatments I was able to show the treatments are independent There is a significant correlation in the treatments   The results obtained above were primarily due to the mean for the third treatment being noticeably different from the other two sample means. For the…