I. Basic concepts.
- Hypothesis testing (I). Null hypothesis. Alternative hypothesis.
It all spins around the null hypothesis.
- Hypothesis testing (II). Alpha. Beta. Power. Sample size.
Size and power.
- Hypothesis testing. Fragility index.
The fragility of the EmPress.
- Confidence intervals.
Always look for aninterval, but of confidence.
- Confidence intervals. Prediction intervals. Tolerance intervals.
The poor relations.
- Hypothesis contrast. Statistical significance. Tipo 1 error. Tipo 2 error.
To p or not to p…is that the question?
- Statistical significance. Clinical relevance.
Even non-significant ps have a little soul.
- The meaning of p-value.
Worshipped, but misunderstood.
- Confidence intervals. Statistical significance. Clinical relevance.
Life is not rosy.
- Inverse fallacy. Conditionals’ transposition fallacy.
The fallacy of small p.
- Sample size.
Size does matter.
- Sample size in surveys.
With very little we fine-tune a lot.
- Sample size and precision.
Having a large n, who needs a samll p?.
- Study of qualitative variable dispersion.
Like a forgotten clock.
- Location parameters. Arithmetic mean. Median. Mode. Geometric mean. Harmonic mean.
Virtue is the happy medium between two extremes, but…
- Choosing between mean and median.
Fish or meat?
- Robust location parameters.
A very robust family.
- Robust scale parameters.
Do not be misled by the outliers.
- Biased and unbiased estimators.
Why spare one?
- Dispersion parameters. Variance. Standard deviation.
Not all deviations are perverse.
- Dispersion parameters. Minimum. Maximum. Quartile. Decile. Percentile. Interquartile range.
The most wished statistical for a mother.
- Standardization. z score. Frequiency distribution. Probability density curves. Histograms.
Give me a bar and I’ll move the earth.
- Simmetry measures. Mean deviation. Distribution bias. Kurtosis.
Playing with powers.
- Degrees of freedom. Sample size. Power.
Freedom in degrees.
- Regression to the mean.
- Independency of variables. Paired data.
- Transforming data. Logaruthm transformation. Inverse transformation.
- Graphic representation of qualitative variable. Pie chart. Bar chart. Pareto’s graph.
Columns, sectors, and an illustrious italian.
- Histogram. Bar graph.
As and egg to a chestnut.
- Box plot.
A box with whiskers.
- Quantile graph. q-q plot.
Some comparisons are not odious.
- Circle graph.
Do not eat too many pies.
- Frequentist vs Bayesian’s statistics.
Rioja vs Ribera?
- Normal distribution. Standardization.
The most famous of bells.
- Stdent’s t distribution. Chi-squared distribution. Snédecor’s F distribution.
The big family.
- Binomial probability (I). Binomial distribution. Bernouilli’s events.
The cooker and his cake.
- Binomial probability (II). Survey errors. Lie. Obfuscation factor.
Lie to me.
- Binomial probability (III). Calculating number of successes.
Do not gamble.
- Conditioned probability. Bayes’ rule.
The stigma of guilt.
- Conditioned probability. Bayes’ theorem.
A case of misleadind probability.
- Conditioned probability (II). Bayes’ rule.
Another about coins.
- The problem of birthday.
The deception of intuition.
- Probabilitu value when numerator equals zero.
When nothing bad happens, is everything okay?
III. Statistic tests.
- Hypothesis testing. One-tailed test. Two-tailed test.
The tails of p.
- Statistical significance. Power. Type I error. Type II error.
The false coin.
- Multiple comparisons. Type I error.
Even a blind donkey…
- Statistical test by variable type.
Brown or blond, all bald.
- Contingency tables. Residuals. Pearson’s residuals. Standardized residuals. Adjusted residuals. Chi-square.
- Chi-square test (I). Goodness of fit.
- Chi-square test (II). Homogeneity test.
- Chi-square test (III). Dependent variables.
Studying or working?.
- Chi-squared-test (IV). Calulating expected values.
The why and wherefores.
- Comparison of two proportions. Chki-square.
All road lead to Rome.
- Confidence interval for a mean.
The error of confidence.
- Concordance. kappa’s interobserver concordance coeficient.
A good agreement?.
- Concordance. Bland-Altaman’s method.
Another stone with which nor to trip over.
- Stratification. Mantel-Haenszel’s test. Confusion. Adjusted measures of association.
Dividing to conquer.
- Choosing the statistical test.
- Comparison of two means. Student’s t test.
The same old story.
- Analysis of variance of one factor. ANOVA.
More than two is a crowd.
- Bonferroni’s correction.
When the zeroes of p are important.
- Lineal correlation. Pearson’s lineal correlation coefficient. Covariance. Independence.
An open relationship.
- Missing data. Imputation.
…there are not all those who are.
- Management of non-normal data.
Everything is not normal.
- Non-parametric tests. Sign test.
At a rough guess.
- Survival analysis. Survival tables. Censored data.
- Simple regression. Lineal regression. Logistic regression. Cox regression.
A simple relationship.
- The least squares method.
The shortest distance.
- Collinearity. Multiple lineal regression.
Three feet of a cat.
- Discontinuity regression. Multiple lineal regression.
In search of causality.
- Resampling techniques. Bootstrapping.
An impossible task.
- Propensity score.
You can’t make a silk purse…
- Meta-analysis (I). Heterogeneity. Metaregression.
Apples and pears.
- Meta-analysis (II). Publication bias. Forest plot.
Achilles and Effects Forest.
- Effect size based in differences between means.
I am Spartacus.
- Incorrect uses of statistics.
The cheaters detector.