In this chapter you will learn how to perform statistical inference on a single parameter that describes categorical data. This includes both resampling based methods and approximation based methods for a single proportion.

The General Social Survey

Exploring consci

Generating via bootstrap

Constructing a CI

Why more bootstraps?

Interpreting a Confidence Interval

CIs and confidence level

SE with less data

SE with different p

The approximation shortcut

CI via approximation

Methods compared

Inference for a single parameter

This chapter dives deeper into performing hypothesis tests and creating confidence intervals for a single parameter. Then, you'll learn how to perform inference on a difference between two proportions. Finally, this chapter wraps up with an exploration of what happens when you know the null hypothesis is true.

Test d'ipotesi per una proporzione

Vita dopo la morte

Generare da H0

Verificare un'affermazione

Prendere una decisione

Intervalli per le differenze

Pena di morte e sesso

Test d'ipotesi sulla differenza tra proporzioni

Interpretare il test

Test d’ipotesi e intervalli di confidenza

Errori statistici

Quando l'ipotesi nulla è vera

Quando l’ipotesi nulla è vera: decisione

Proportions: testing and power

This part of the course will teach you how to use both resampling methods and classical methods to test for the indepence of two categorical variables. This chapter covers how to perform a Chi-squared test.

Contingency tables

Politics and Space

Understanding contingency tables

From tidy to table to tidy

Chi-squared test statistic

A single permuted Chi-sq

Building two null distributions

Is the data consistent with the model?

Alternate method: the chi-squared distribution

Checking conditions

The geography of happiness

A p-value two ways

Intervals for the chi-squared distribution

Comparing many parameters: independence

The course wraps up with two case studies using election data. Here, you'll learn how to use a Chi-squared test to check goodness-of-fit. You'll study election results from Iran and Iowa and test if Benford's law applies to these datasets.

Case study: election fraud

Getting to know the Iran data

Who won?

Breaking it down by province

Extracting the first digit I

Goodness of fit

Goodness of fit test

A p-value, two ways

Is this evidence of fraud?

And now to US

Getting to know the Iowa data

Extracting the first digit II

Testing Iowa

Fraud in Iowa?

Election fraud in Iran and Iowa: debrief

Comparing many parameters: goodness of fit

GSS data

Iowa election data

Iran election data

I dati categorici sono ovunque: nei più recenti sondaggi d’opinione, nei dati che portano a nuove scoperte nella genomica e nelle enormi quantità di informazioni che le aziende internet raccolgono per venderti prodotti. In questo corso imparerai tecniche per distinguere il segnale dal rumore; strumenti per capire quando la struttura nei dati rappresenta fenomeni interessanti e quando è solo rumore casuale.

Foundations of Inference in R

In questo corso imparerai a utilizzare tecniche statistiche per gestire dati categorici.

Inferenza per dati categorici in R

In questo corso imparerai come usare le tecniche statistiche per lavorare con i dati categoriali.

Inferenza statistica in R

Interpretare il test

Inferenza per dati categorici in R

Esercizio pratico interattivo