1. MARCH 18, 2014 DATA ANALYSIS

2. WHAT TO DO WITH DATA Take a look at your data Histogram Descriptive statistics Mean, mode, range, standard deviation/standard error Statistical analysis Depends on the data T-test, chi-square, regression, correlation, ANOVA

3. LOOK AT YOUR DATA: HISTOGRAM Plot Show underlying frequency distribution Percentage, proportion, # of individuals Shape Continuous data

4. HISTOGRAM Data is split into intervals Bins

5. HISTOGRAM Define bin Look at your data Age data:

6. 150- 155- 160 - 165- 170- 175- 180 - 154.9 159.9 164.9 169.9 174.9 179.9 184.9 Height (cm) [or other “bins”] This is a FREQUENCY DISTRIBUTION or HISTOGRAM Frequency (percentage, proportion, or number)

7. 150.1- 155.1- 160.1- 165.1- 170.1- 175.1- 180.1- 155.0 160.0 165.0 170.0 175.0 180.0 185.0 Height (cm) [or other “bins”] Shifting bins can change shape of histogram for same data Frequency (percentage, proportion, or number)

8. DESCRIPTIVE STATISTICS Common descriptive statistics? Mean Range Variance, standard deviation, standard error Measure of spread Deviation from the mean? How frequently do data deviate? Data set 1: 10, 9,10, 8, 9 Data set 2: 12, 8, 9, 4, 14

9. INTERPRETING GRAPHS

10. T-TEST Statistical comparison Hypothesis: Means are different Null hypothesis: Means are not different p-value Probability Reject the null when it is actually true