# Students

Welcome to the website for Introduction to the New Statistics 1e! Here you will find a multitude of resources that will allow you to further explore and test your understanding of the concepts covered in the text. You will also find on this site the ESCI download and a support guide for using SPSS and R with the new statistics.

### Videos

 Video topic Overview Length of video Research Questions Introduction. Research questions. Poll example. 95% confidence interval. Estimation. Point and interval estimates to answer research questions. The six-step research process. (9:29) Meta-analysis Meta-analysis to combine results from two or more similar studies. Forest plot and diamond. The new statistics: estimation and meta-analysis. (4:13) Open Science The replication crisis. Open Science techniques to increase the trustworthiness of science. Replication. Fully detailed reporting, without selection. Do we have the full story? (5:11) Research fundamentals Populations and random sampling. Population parameters and sample statistics. Nominal, ordinal, interval, and ratio levels of measurement. Planned and exploratory analysis. Full reporting, without selection. Pre-registration. Cherry picking, seeing faces in the clouds. Don’t fool yourself! (11:26) Descriptives Introduction to ESCI. ESCI intro chapters 3–8, Describe. Revealing pictures of data: frequency histogram and stacked dot plot. Loading a data set within ESCI. Measures of location: mean, median. Measures of spread: standard deviation, variance. z scores. (6:12) More descriptives ESCI intro chapters 3–8, Describe. Generate a data set. Positive and negative skew. Percentiles, quartiles, inter-quartile range. Loading data into ESCI. End of chapter Exercise 2. (5:45) Normal distribution A continuous distribution: the normal distribution. ESCI intro chapters 3–8, Normal. Areas, probabilities, and z scores; X scores; z = 1.96, z = 2.58. (5:08) Sampling Computer simulation of random sampling from a normal population of HEAT scores. ESCI intro chapters 3–8, CIjumping. Sampling variability. Dance of the means. Empirical and theoretical sampling distributions of the mean. Standard error. (7:35) Central limit theorem ESCI intro chapters 3-8, CIjumping. Sampling distribution of the sample mean, for normal, rectangular, skew populations. Central limit theorem. The normal distribution in nature. (8:10) Confidence intervals ESCI intro chapters 3–8, CIjumping. Sampling variability, mean heap, margin of error (MoE). M close to µ, so µ close to M. Confidence interval (CI). Dance of the CIs. Level of confidence, C, usually 95. 5% of CIs are red. (10:03) CIs and t distribution ESCI intro chapters 3–8, CIjumping. σ not known, t distribution, degrees of freedom, CIs of varying length. ESCI intro chapters 3–8, Normal and t. Normal and t distributions. Tail areas of the t distribution. (6:39) CI interpretation ESCI intro chapters 3–8, CIjumping. One from the dance, 5% of CIs are red. Interpret our interval, unless N is very small. Cat’s eye picture of a CI. MoE our measure of precision. 95% CI as an 83% prediction interval for a replication mean. (6:53) CIs and p Cat’s eye picture, plausibility, and the p value for different null hypothesis values. Hypothesis testing, NHST, p as a measure of strength of evidence against H0. Reading the approximate p value from a CI; eyeballing the CI from a p value. (13:31) Red flags The anti-aging product: a cautionary tale. Four red flags. Beware dichotomous thinking, prefer estimation thinking. Beware the “S” word (“significant”). Beware accepting the null hypothesis. Beware the p value. Effect sizes and CIs are more informative. (5:34) Independent groups Independent groups design, pen/laptop example. ESCI intro chapters 3–8, Data two. Difference between group means and CI on the difference. Figure with difference axis. Homogeneity of variance, pooled standard deviation, Welch-Satterthwaite. (7:11) More independent groups ESCI intro chapters 3–8, Data two. Cohen’s d and dunbiased. CI for δ. ESCI intro chapters 3–8, Summary two. End-of-chapter exercises, with ESCI. (5:57) CI overlap ESCI intro chapters 3–8, Data two. ESCI intro chapters 3–8, Summary two. Eyeballing the difference and CI on the difference, for independent groups. Overlap rule for independent CIs. (5:55) p values Thinking about p values, p as strength of evidence. Dance of the CIs, dance of the p values. Extreme sampling variability of the p value. (10:02) Paired design The paired design, Thomason 1 example. ESCI intro chapters 3–8, Data paired. Mean of the paired differences and CI on that mean. Loading a data set within ESCI. Correlation between the measures. (7:08) More paired design The paired design, Thomason 1 example. ESCI intro chapters 3–8, Data paired. Cohen’s d and dunbiased. Standardizer for the paired design. CI for δ. ESCI intro chapters 3–8, Summary paired. Thomason 2 example. No overlap rule for paired design. Comparing two designs. Carryover effects, counterbalancing, and parallel forms of a test. (12:13) Meta-analysis Meta-analysis, forest plot, diamond. ESCI intro Meta-Analysis, Original two groups. McCabe and Michael brain picture example. Study weights, fixed effect and random effects models, diamond ratio, heterogeneity. (8:10) More meta-analysis Meta-analysis with Cohen’s d and dunbiased. ESCI intro Meta-Analysis, d subsets. Damisch and Calin luck example. Subsets analysis, dichotomous moderator. Statistical significance and selective publication, file drawer effect. Loading data into ESCI. End-of-chapter flag-priming exercise. Cochrane Collaboration. Open Science, replication, and meta-analysis. (13:48) Open Science Replication crisis, three Ioannidis problems, the p < .05 imperative. Questionable research practices, p hacking. Psychological Science, Open Science policies, badges, the new statistics. Pre-registration. Center for Open Science, Open Science Framework. (10:31) Precision for planning Pilot testing, planning research. Precision for planning. ESCI intro chapters 10–16, Precision two. Target MoE. Independent groups. MoE distribution. Planning with assurance. ESCI intro chapters 10–16, Precision paired. Paired design, correlation between the measures. (11:07) Power Statistical power, α, target δ, N. Power for planning, independent groups, values of power. Paired design, correlation between the measures, power for planning, values of power. Post hoc power: a bad idea. (9:55) Correlation ESCI intro chapters 10–16, Scatterplots. Scatterplots, loading data within ESCI. ESCI intro chapters 10–16, See r. Pearson’s correlation, r. Eyeballing r from scatterplots, tightness to the line, cross through the means, matched and mismatched quadrants. (9:28) Correlation CI Bivariate normal distribution. ESCI intro chapters 10–16, See r. Dance of the r values. The asymmetric CI on r, ESCI intro chapters 10–16, One correlation. CI on the difference between two independent r values, ESCI intro chapters 10–16, Two correlations. (13:09) Regression Linear regression of Y (predicted variable) on X (predictor variable). ESCI intro chapters 10–16, Scatterplots. Thomason 1 example. Residuals, equation of the line, intercept and slope. Standard scores, regression of ZY against ZX, with slope r. Regression for making predictions. (9:26) Regression CIs Regression and inference. ESCI intro chapters 10–16, Scatterplots. Thomason 1 example. CI on slope, b. CI for mean Y at a particular X, curves for those CIs. Prediction interval for a single value of Y at a particular X, curves for those PIs. (8:52) One proportion Frequencies, percentages, proportions. ESCI intro chapters 10–16, One proportion. The asymmetric CI on a proportion. (7:08) Two proportions The difference between two independent proportions. ESCI intro chapters 10–16, Two proportions. CI on the difference. Chi square, an alternative approach to analyzing a 2 × 2 frequency table. Phi coefficient. (7:52) One-way independent groups One-way independent groups design. Bushman example of advertising effectiveness. ESCI intro chapters 10–16, Ind groups comparisons. Planned comparisons, CI on a comparison. Rattan student motivation example. ESCI intro chapters 10–16, Ind groups contrasts. Planned contrasts of subset means, CI on a contrast. (12:03) More one-way independent groups Halagappa Alzheimer’s example with mice. ESCI intro chapters 10–16, Ind groups contrasts. Planned contrasts of subset means, CI on a contrast. Planned and exploratory analysis, cherry picking. (7:51) One-way repeated measure Independent groups and repeated measure designs. Comparisons, contrasts, and their CIs. One-way repeated measure design. Donohue critical thinking example. ANOVA, an alternative approach to analyzing extended designs. Main effect of the one IV. (10:58) Two-way independent groups Two-way independent groups design. Frenda 2 × 2 false memory example. ESCI intro chapters 10–16, Ind groups 2 × 2. Main effects, simple main effects, with CIs. Interaction as difference of differences, with CI. (10:27) More two-way designs Main effects and interaction. Rock/Classical, Party/Church example. Patterns of means, interaction as non-parallel lines. One IV as moderator of the effect of the other IV. RCT, two-way factorial design with one repeated measure, Hölzel meditation example. Two-way design with two repeated measures, Weisberg quality of explanation example. Two-way 3 × 2 mixed design, McDaniel study technique example. Two-way 3 × 5 mixed design, Chaix restricted feeding example with mice. General analysis strategy for extended designs. (14:36) Future directions Open Science, the new statistics, the ten-step plan for research. Replicability of research in psychology, Many Labs 1, Reproducibility Project: Psychology. Preregistered review. Student participation in replication research. (12:23) Future directions Non-normal data, robust statistical techniques. Robust analysis for independent groups, trimming, and trimmed means. ESCI intro chapters 10–16, Robust two. N sex partners example. Archival and longitudinal data. Numerous DVs. Big data. Open Science and careful critical thought. (7:16)