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.

Hypothesis test for a proportion

Life after death

Generating from H0

Testing a claim

Making a decision

Intervals for differences

Death penalty and sex

Hypothesis test on the difference in proportions

Interpreting the test

Hypothesis tests and confidence intervals

Statistical errors

When the null is true

When the null is true: decision

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.

Studi kasus: kecurangan pemilu

Mengenal data Iran

Siapa yang menang?

Menguraikan menurut provinsi

Mengekstrak digit pertama I

Kesesuaian (goodness of fit)

Uji kesesuaian (goodness of fit)

Satu p-value, dua cara

Apakah ini bukti kecurangan?

Dan sekarang ke AS

Mengenal data Iowa

Mengekstrak digit pertama II

Menguji Iowa

Kecurangan di Iowa?

Kecurangan pemilu di Iran dan Iowa: ringkasan

Comparing many parameters: goodness of fit

GSS data

Iowa election data

Iran election data

Data kategorik ada di mana-mana. Data ini muncul dalam angka jajak pendapat terbaru, dalam data yang mendorong terobosan baru di genomik, dan dalam tumpukan data yang dikumpulkan perusahaan internet untuk menjual produk kepada Anda. Dalam kursus ini, Anda akan mempelajari teknik untuk memilah sinyal dari derau; seperangkat alat untuk mengidentifikasi kapan struktur dalam data ini merepresentasikan fenomena menarik dan kapan itu hanya derau acak.

Foundations of Inference in R

Dalam kursus ini, Anda akan belajar teknik statistik untuk mengolah data kategorikal.

Inferensi untuk Data Kategorik di R

Dalam kursus ini, Anda akan belajar cara memanfaatkan teknik statistik untuk bekerja dengan data kategorikal.

Penarikan Kesimpulan Statistik di R

Kecurangan di Iowa?

Inferensi untuk Data Kategorik di R

Latihan interaktif praktis