1. 1-way ANOVA assumes that observations within each group are normally distributed. It is particularly sensitive to deviations from this assumption, and there are no possibilities for adjustments.

2. For a paired t-test, if there are a moderate number of pairs, you could either visualize each individual value using a bar graph or visualize the mean differences.

3. 2-way ANOVA without replication and only two groupings may be analyzed using a paired t-test.

4. If you reject the null hypothesis that all the means are equal in a 1-way ANOVA, you can utilize a two-sample t-test for pairwise comparisons.

5. The two-sample t-test gets larger as the means gets closer, the variances get larger, or the sample sizes decreases.

6. When using two-sample t-test and you have a group with a small sample size but a disproportionately large standard deviation, it is most likely that you will encounter a false positive result.