## Advanced Statistics - Biology 6030 |

## Bowling Green State University, Fall 2017 |

**Statistical inference**from**sample**to**population**: Sample Statistics and Population Parameters- Stats in
**hypothesis testing**,**decision making**, and experimental design - What are the odds of getting this outcome
**by chance alone**?**Statistics tables**: calculate or look-up*P* **Alpha error**(falsely rejecting the null hypothesis),**Statistical signficance**and what is so magical about*P*=0.05 anyway ...?- A Tale of two tails:
**one-tailed**vs.**two-tailed**rejection region in directional and non-directional null hypotheses **Beta error**(failing to reject the null hypothesis when it actually should be rejected):**Power**of a test is the probability that we reject the null hypothesis when the null hypothesis should be rejected.- With a (biological) reason we can compare a sample distribution to a particular
**null distribution**(e.g., testing for randomness in a spatial or temporal distribution) **comparison-wise error rate**and**experiment-wise error rate**: "... we then used t-tests to compare the 6 treatments with each other ..."**Dunn-Sedak**: a'=1-(1-a)^{1/k}**a-priori**set of comparisons: orthogonal comparisons (non-overlapping variances)**a-posteriori**set of comparisons:**Parametric**vs.**nonparametric**

**Houdini the Statistician - not**: Stats as an afterthought and the statistician as pathologist: You can only assess what the experiment died of ...**Percentages**- What are you trying to hide?

last modified: 01/11/05

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