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Overview

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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)

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 d_unbiased. 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 d_unbiased. 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 d_unbiased. 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)