Statistics

• Summarizes data → descriptive → cannot use to generalize

• Analyze + draw conclusions → inferential → generalize to large population (random sample)

• Common language

Measure of central tendency: mean, median, mode

• Outlier when one or more data points are very different from the others

  • Leads to a skewed distribution

  • Median will be the best measure of central tendency to use

    • median > mean → negative skew

    • mean > median → positive skew

Measures of variation

• Range = (largest number)-(lowest number)

• Standard deviation: measure of how dispersed the data is in relation to the mean

  • How spread out the data points are

Normal distribution/curve (bell curve)

• Symmetric (no skew)

• Most data in the middle, less towards extremes

• Median = mode = mean

• 68% → 1 SD

• 95% → 2 SD

• 99% → 3 SD

Inferential statistics: When can results be generalized?

• Sample is representative of population being studied (random sampling)

• More cases exist with those results (large sample size)

• Variability of the data is low

Are the results due to differences in the IV or due to chance?

Statistical significance

• Calculated using a variety of statistical tools (Chi-square, T-test)

• How likely results are due to chance or differences in the IV

• NOT how important the results are

• Reported as a p-value

  • p-values of 0.05 or less → statistically significant, indicate results are not likely due to chance → can generalize to larger population

    • The results are unlikely to be obtained if there is no difference between the control and experimental groups