The following data represent the results from an independent-measures experiment comparing three treatment conditions. Use a spreadsheet to conduct an analysis of variance with $\alpha=0.05$ to determine whether these data are sufficient to conclude that there are significant differences between the treatments. \begin{tabular}{|c|c|c|} \hline Treatment A & Treatment B & Treatment C \\ \hline 16 & 15 & 17 \\ \hline 15 & 18 & 21 \\ \hline 16 & 16 & 23 \\ \hline 14 & 14 & 19 \\ \hline 14 & 17 & 20 \\ \hline \end{tabular} $F$-ratio $=$

Step 1 ：The given data represents the results from an independent-measures experiment comparing three treatment conditions. We are asked to conduct an analysis of variance with a significance level of \( \alpha = 0.05 \) to determine whether these data are sufficient to conclude that there are significant differences between the treatments.

Step 2 ：The test statistic for ANOVA is the F-ratio, which is calculated by dividing the variance between the groups by the variance within the groups.

Step 3 ：To calculate the F-ratio, we first need to calculate the sum of squares between (SSB), sum of squares within (SSW), and the total sum of squares (SST).

Step 4 ：Then, we calculate the degrees of freedom for between groups (dfB), within groups (dfW), and total (dfT).

Step 5 ：The mean square between (MSB) is calculated by dividing SSB by dfB, and the mean square within (MSW) is calculated by dividing SSW by dfW.

Step 6 ：Finally, the F-ratio is calculated by dividing MSB by MSW.

Step 7 ：The data for the three treatments are as follows: Treatment A: [16, 15, 16, 14, 14], Treatment B: [15, 18, 16, 14, 17], Treatment C: [17, 21, 23, 19, 20].

Step 8 ：After calculating, we get the F-ratio and the p-value. The F-ratio is the test statistic for the ANOVA test, and the p-value is the probability of obtaining a result as extreme as the one that was actually observed, assuming that the null hypothesis is true.

Step 9 ：If the p-value is less than the significance level (in this case, 0.05), we reject the null hypothesis and conclude that there are significant differences between the treatments. If the p-value is greater than the significance level, we fail to reject the null hypothesis and conclude that there are no significant differences between the treatments.

Step 10 ：The final answer is the F-ratio, which is \(\boxed{F}\).