Lab 7

• What is the simplest two-factor between-participants design?

  A 2 × 2 factorial design

  
• How many conditions are there in a 2 × 2 factorial design?

  Four conditions
• How many scores does each participant contribute in a 2 × 2 factorial design?

  One score to one condition
• What can we ask about the main effects in a factorial design?

  Whether either of the main effects is significant
• How is an interaction interpreted in a factorial design?

  In terms of the simple main effects

  
• What are the two ways simple main effects may differ in trends?

  1. One has a significant difference, the other does not.
  2. Both are significant but in opposite directions.
• What is the first stage of analysis in a 2 × 2 factorial design?

  To uncover significant main effects and interactions
• What happens if the interaction is significant in a factorial design analysis?

  A simple main effects analysis is performed

  
• How many F ratios are there in a 2 × 2 between-participants design?

  Three F ratios
• What does within-group variance measure in a factorial design?

  The extent of behavior differences within groups
• How is the error term calculated in a 2 × 2 between-participants design?

  By combining Sums of Squares and degrees of freedom

  
• What does the between-group Sum of Squares measure?

  Variability due to various experimental treatments

  
• How is the total Sum of Squares calculated?

  As a measure of total variability in the data
• How many between-group sums of squares are required for the two main effects?

  Two sums of squares
• How is the Sums of Squares for the interaction calculated?

  As variability not accounted for by main effects

  
• What do simple main effects involve in a 2 × 2 design?

  Pairwise comparisons, like four t-tests

  
• How is the significance of simple main effects evaluated?

  Using the same error term from ANOVA

  
• What is the formula for calculating a between-group Sum of Squares?

  Group totals minus the total of these totals

  
• How are degrees of freedom calculated for simple main effects?

  Equal to the number of levels minus one
• What are the degrees of freedom for the two simple main effects of factor A?

  (a - 1), where a is the number of levels

  
• What are the degrees of freedom for the two simple main effects of factor B?

  (b - 1), where b is the number of levels

  
• SSinteraction(SSAxB)

  [AB] - A - B + T
• Sum Sqs for A (SSA)

  A - T
• Sum sqs for B (SSB)

  B - T
• Basic ratio of the grand total(T)

  grand total squared divided by number of scores that make up the grand total

  
• Basic ratio of the level totals (same for both levels)- (A), (B), ETC

  Level total of A1 squared added with Level total of A2 squared then divided by number of scores that make up each level

  
• Basic ratio of individual scores(Y)

  score 1 squared added by score 2 squared added by score 3 squared (and so on) divided by 1 (as only one number makes up each individual score)

  
• Basic ratio of cells total [AB]

  total of all scores divided by number of scores in each cell

  
• SSwithin (SSs/AB)


  [Y] - [AB]
• SSbetween (SSAB)


  [AB] - [T]
• SStotal


  [Y] - [T]
• degrees of freedom for factor A (dfA) - same for factor B(dfB)

  (numbers of levels in factor A - 1)
• degrees of freedom for interaction (dfAxB)

  dfA x dfB
• degrees of freedom for within-group variance (error term) (dfS/AB)

  (number of cells) x (number of scores in cell - 1) --> ab(s - 1)
• degrees of freedom for total degrees of freedom (dftotal)

  (total number of scores - 1) --> (abs) - 1 or [dfA + dfB + dfAxB +dfS/AB]