lesson 5 (expepsych)

• Population


  A set of people, animals, or objects that share at least one characteristic in common
• Sample


  A subset of the population that we use to draw inferences about the population
• Statistical inference


  The process by which we make statements about a population based on a sample
• Null hypothesis (H0)


  A type of statistical hypothesis that proposes that no statistical significance exists in a set of given observations
• Alternative hypothesis (H1)


  It claims that there's an effect in the population
• Significance level (alpha level)

  Our criterion for deciding whether to accept or reject the null hypothesis
• Significance levels and error types

  • 0.01 (1% error, 99% confidence)
  • 0.05 (5% error, 95% confidence)
• Type 1 error (α)


  Rejecting the null hypothesis when it is correct
• Type 2 error (β)


  Accepting the null hypothesis when it is false
• Critical region


  A region of distribution of a test statistic sufficiently extreme to reject the null hypothesis
• Measures of central tendency

  • Mean
  • Median
  • Mode
• Measures of variability


  • Range
  • Variance
  • Standard deviation
• Levels of measurement


  • Nominal
  • Ordinal
  • Interval
  • Ratio
• Chi-square test


  Used when the data are nominal and the groups are independent
• 1. test


  A statistical test used to compare the means of two groups
• Steps in interpreting a t-test result

  1. Compute the t-statistic

  2. Determine if the p-value is lower or greater than 0.05

  3. Check the descriptive statistics to know the mean and standard deviation of the two groups
• 1. value


  The exact probability that the observed results would occur by chance if the null hypothesis is true
• Independent t-test


  Tests whether the means of two independent groups are different
• Matched t-test


  Tests whether the means of two matched groups are different
• One-way ANOVA


  Suitable for experiments with only one independent variable (factor) with two or more levels
• Two-way ANOVA


  Evaluates the effect of two different independent variables on one dependent variable
• Repeated measures ANOVA


  Used when the same subjects are used for each treatment (i.e., repeated observations for each subject)
• MANOVA


  Enables the examination of multiple dependent variables simultaneously
• Post hoc tests


  Performed when an overall ANOVA is significant and no specific predictions have been made, to examine all pairs of treatment groups
• In reporting statistical results, report the descriptive statistics (mean and standard deviation), test statistic, degrees of freedom, obtained value of the test, and the probability of the result occurring by chance (p value)
• All statistical symbols that are not Greek should be italicised (M, SD, N, t, p, etc.)