Monthly Archives: November 2019

1. Inflated Type I error: For each test, there’s a α=5% probability that the difference between groups is not meaningful (i.e. due to chance). If we have n groups to compare, and we keep running t-tests, there will be 1-(1-α)n chance to make a Type I error! 2. To control for Type I error: MakeContinue reading “Class #21: ANOVA”

1. When the probability that your results are due to chance/sampling variation is small enough (p <.05), we reject the null, then these results are called statistically significant. We also mentioned statistically significance during Class #14 Correlation. 2. T-test: tells us the difference between the means of two groups, and an estimate of what differences areContinue reading “Class #20: Data analysis (t-test)”

1. Null Hypothesis (H0, pronounced as H-nought): The independent variable will not have an effect; there’s no difference between treatment group and control group. Alternative Hypothesis (H1): The independent variable has an effect. When we try to confirm the hypothesis, we are statistically testing the Null Hypothesis. We assume H0 is true (there is noContinue reading “Class #19: Thinking about Probabilities (Testing the Null Hypothesis)”

1. One-way design: manipulating only one independent variable 2. Factorial design: manipulating two or more independent variablesDescribing the size and structure of factorial designs: 2 × 2 factorial design: 2 IVs; 2 levels for each 3 × 3 factorial design: 2 IVs; 3 levels for each 2 × 2 × 4 factorial design: 3 IVs;Continue reading “Class #18: More on Experimental Design”

1. Again, group designs: Randomized Group Design (Between-subjects): each participant is only assigned to ONE condition Repeated Measures Design (Within-subjects): each participants gets to be in each condition 2. Repeated Measures (Within-subjects) Design: Strengths: Doesn’t need random assignment Has Initial Equivalence (because every subject is the same in each condition) More powerful than Between-subjects design,Continue reading “Class #17: Experimental Design”