Statistics

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

\