1. Last lecture summary Types of statistics Measures of central tendency Measures of variability Bias, Bessel's correction MAD Normal distribution Empirical rule Standard normal distribution, Z-distribution

2. Standard deviation – empirical rule

5. New stuff

6. Use Z-table

7. Quiz – height data

9. The nature of the normal distribution In laboratory experiments, results vary due to several factors: imprecise weighting of reagents, imprecise pipetting, nonhomogeneous suspensions of cells or membranes... Similarly, variation in a clinical value might be caused by many genetic and environmental factors. These random factors are independent and they tend to offset each other. Variation among values will approximate a Gaussian distribution when there are many independent sources of variation when individual sources add up to get the final result

10. DISTRIBUTION, DISTRIBUTION, ARE YOU NORMAL? http://www.nate-miller.org/blog/how-normal-is-normal-a-q-q-plot-approach

11. Life expectancy data – histogram life expectancy frequency

12. Making conclusions from a histogram What can you tell about life expectancy data? how many modes? where is the mode? symmetric, left skewed or right skewed? outliers – yes or no? life expectancy frequency

13. Making conclusions from a histogram Where is the mode, the median, the mean? life expectancy frequency

14. Min. Q1 Median Q3 Max. 47.79 64.67 73.24 76.65 83.39 Five numbers summary