1. Sec 3 SMTP Research Module ADVANCED STATISTICS Mrs Goh Cheng Wai

2. Relation of data A correlation tells us whether two variables vary together Correlation coefficient [X: independent variable, Y: dependent variable] +1 (perfect correlation) X , Y  - 1 (perfect negative correlation) X , Y  0 (no correlation between X and Y)

3. Correlation  Cause and effect Correlations can only be used to estimate the relationship between two characteristics. Do not use them to establish cause and effect. E.g. A high correlation between intelligence and exposure to classical music DOES NOT MEAN listening to classical music causes one to become intelligent.

4. ANOVA (Analysis of variance) How many sets of data can each t-test compare? What if you must compare the means of 3 or more groups? ANOVA tells you whether there is an overall difference among the groups. However, ANOVA cannot identify where the difference lies or which pair is responsible for the difference.

5. Standard deviation & standard error Standard deviation (SD) tells you how scattered the measurements are. Standard error of the mean (SE) indicates the uncertainty around the estimate of the mean.

6. Link between error bars and statistical significance Standard error bars do not overlap. Difference may be significant or insignificant. Standard error bars overlap. Difference is insignificant (p  0.05)

7. Hands-on session 3S1 and 3P3 (first seven in the list): Comp Lab 1 3S2 and 3O3: Comp Lab 2 3A3: Comp Lab 3 3I3 + 3P3 (next seven in the list): Comp Lab 4 Deadline to submit 1 st draft of proposal to mentor: Monday 11 April