1. Making sense of data We got to deal with some Math here folks

2. Measures of Central Tendency

3. Measures of dispersion 3 types: Range, Interquartile Range & Standard Deviation

4. Interquartile Range Shows the middle 50% of a set of scores

5. Standard Deviation

6. Put your data into graphs Bar Graphs

7. Put your data into graphs Histograms are different from bar graphs because they are used for continuous data (test scores)

8. Put your data into graphs Frequency polygons is similar to a histogram as it shows continuous data but its advantage is that it can graph 2+ frequency distributions

9. Statistical Significance Probability (p) concerns the degree of certainty that an observed difference or relationship between 2 sets of data is a real difference rather than having occurred by chance. eg. If I flip a coin 100 times and it lands on heads 60 times A result is considered to be significant if it occurs 95% of the time, p 0.05 The lower the probability that it occurred by change the greater the significance