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.

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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)

1.1 Research Questions

    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)

    1.2 Meta-analysis

      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)

      1.3 Open Science

        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)

        2.1 Research fundamentals

          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)

          3.1 Descriptives

            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)

            3.2 More descriptives

              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)

              4.1 Normal distribution

                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)

                4.2 Sampling

                  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)

                  4.3 Central limit theorem

                    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)

                    5.1 Confidence intervals

                      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)

                      5.2 CIs and t distribution

                        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)

                        5.3 CI interpretation

                          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)

                          6.1 CIs and p

                            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)

                            6.2 Red flags

                              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)

                              7.1 Independent groups

                                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)

                                7.2 More independent groups

                                  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)

                                  7.3 CI overlap

                                    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)

                                    7.4 p values

                                      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)

                                      8.1 Paired design

                                        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)

                                        8.2 More paired design

                                          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)

                                          9.1 Meta-analysis

                                            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)

                                            9.2 More meta-analysis

                                              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)

                                              10.1 Open Science

                                                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)

                                                10.2 Precision for planning

                                                  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)

                                                  10.3 Power

                                                    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)

                                                    11.1 Correlation

                                                      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)

                                                      11.2 Correlation CI

                                                        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)

                                                        12.1 Regression

                                                          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)

                                                          12.2 Regression CIs

                                                            One proportion

                                                            Frequencies, percentages, proportions. ESCI intro chapters 10–16, One proportion. The asymmetric CI on a proportion.

                                                            (7:08)

                                                            13.1 One proportion

                                                              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)

                                                              13.2 Two proportions

                                                                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)

                                                                14.1 One-way independent groups

                                                                  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)

                                                                  14.2 More one-way independent groups

                                                                    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)

                                                                    14.3 One-way repeated measure

                                                                      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)

                                                                      15.1 Two-way independent groups

                                                                        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)

                                                                        15.2 More two-way designs

                                                                          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)

                                                                          16.1 Future directions

                                                                            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)

                                                                            16.2 More Future directions

                                                                              ESCI download

                                                                              ESCI (“ESS- key”) is Exploratory Software for Confidence Intervals. There are three ESCI intro files, each of which is a regular Microsoft Excel workbook.

                                                                              • Download and save to your local hard disk before opening in Excel
                                                                              • Make sure macros are enabled
                                                                              • See the Appendix in the book for further guidance
                                                                              • For news on updates, or any other ESCI issue, see the blog
                                                                              • At the first Intro tab, scroll down to see GNU license conditions

                                                                              ESCI Meta Analysis

                                                                              ESCI Intro Chapters 3-8

                                                                              ESCI Chapters 10-16

                                                                              Software Guide

                                                                              R Guide

                                                                              IBM SPSS Guide