1. Research Project Statistical Analysis

2. What type of statistical analysis will I use to analyze my data? SEM (does not tell you level of significance) Paired t-Test Linear Regression Used less often: Chi Square Test ANOVA (Analysis of Variance for comparing more than 2 groups) The most common analyses we will use:

3. Standard Error of the Mean (SEM) Standard error of the mean tells you how accurate your sample estimate of the mean is likely to be compared to the actual mean (parametric mean). SEM takes sample size into consideration. The larger your sample size, the closer your sample mean will be to the actual (parametric) mean. The larger the sample size, the smaller your SEM.

4. Standard Error of the Mean You will probably represent your data with 2 standard errors (which 95 of your data will fall into). If the standard error bars do not overlap, the sample groups are likely to be significantly different.

5. t-Test A t-Test will be useful in determining if there is a significant different between your two groups (each group can be compared to a standard or control). One of two types of t-Tests will most likely be used:- Paired t-Test - Two-way t-Test

6. t-Test A 2-sample t-Test will determine whether there is a significant difference between two unrelated groups by comparing MEANS. – Ex: if you were testing the difference between two different populations of bacteria with different treatments. – Excel or Google Spreadsheets can be used to do this (click on a box, f(x)=tTest(range 1, range2)

7. Paired t-Test Excel can be used to do a paired t-Test. This would be used when you have the same test subjects under different treatments, assuming equal variance. ALL DATA POINTS (not means) are taken into account for this. – Ex: Looking at the effect of music on blood pressure in the SAME individuals with data points before and after listening to music. – Excel or Google Spreadsheets can be used to do this (click on a box, f=tTest(range 1, range2)

8. t-Test The P value you find should be less than.05 to assume significance. (Whether you use a 1- tailed or 2-tailed t-test depends on your hypothesis.) – 1 tailed is if you expect your data to vary in one direction – 2-tailed is if you want to see if ANY difference exists.

9. t-Test You may do multiple t-tests to compare between data sets (this type of test takes variance into account so it is not performed on means. All data points are taken into consideration for this test).

10. Linear Regression A linear regression would be used to determine if a relationship exists between two variables. Use a scatter plot of your data. Excel can be used to do this too (see me if you have trouble). Gives you an R 2 value with a maximum value of 1. This tells you how closely your data points fall on the line.

11. Chi – Square Test Chi-Square test would be performed to determine whether observed values vary from predicted values (do the data “fit” the predicted values). Most of our experiments are not determining whether data falls into an expected category.

12. ANOVA An ANOVA is used to determine whether significant differences exist between more than 2 data sets This can be done using excel, but it’s complicated.