what are all the statistical tests i can do for such data?

Question

i did an experiment testing out the inhibitory effect of 3 oils on a strain of bacteria to investigate their effectiveness. what are all the statistical tests i can run on the data now? i also did 5 trials per oil.

Answer 1

Hi Sarah! There are several statistical tests you can consider depending on the nature of your data and your research questions. Here are some options:

1. Analysis of Variance (ANOVA):
2. One-way ANOVA: This test compares the means of more than two groups (oils) to determine if there are statistically significant differences.
3. Post hoc Tests:
4. If the one-way ANOVA indicates significant differences, post hoc tests can be performed to identify which specific pairs of oils are different.
5. Common post hoc tests include Tukey's HSD (Honestly Significant Difference), Bonferroni correction, or Dunnett's test.
6. T-Tests:
7. Pairwise t-tests: If you are interested in comparing the effect of each oil to another, you can conduct pairwise t-tests. Be cautious about multiple testing corrections.
8. Repeated Measures ANOVA:
9. If your data involve repeated measures (e.g., the same strain of bacteria subjected to different oils in a repeated manner), a repeated measures ANOVA might be appropriate.
10. Non-parametric Tests:
11. If your data do not meet the assumptions of normality or homogeneity of variance, consider non-parametric tests such as the Kruskal-Wallis test (analogous to one-way ANOVA) or the Wilcoxon signed-rank test (analogous to a paired t-test).
12. Regression Analysis:
13. If you have additional variables that you believe influence the inhibitory effect (e.g., concentration of oils, time of exposure), regression analysis may be appropriate.
14. (and of course) Descriptive Statistics:
15. Consider calculating descriptive statistics such as mean, median, standard deviation, and confidence intervals for a comprehensive understanding of your data.

Remember to check assumptions, especially normality and homogeneity of variance, before conducting parametric tests. Also, it's crucial to adjust for multiple comparisons to control the overall Type I error rate if you are conducting multiple tests. The choice of statistical test depends on the specific characteristics of your data and the research questions you want to address.

I hope this helps, and let me know if you need any specific help with any of the tests!

Answer 2

Hi Sarah,

This sounds like either an ANOVA or a chi squared, depending on your data. How is inhibitory effect measured? If it’s numeric, go ANOVA. If categorical, chi-squared. Sorry I can’t help more—I don’t know any microbiology.