In this chapter you'll use bootstrapping techniques to estimate a single parameter from a numerical distribution.

Selamat datang di kursus ini!

Bangun distribusi bootstrap untuk median

Tinjau kembali metode persentil dan galat baku

Hitung interval bootstrap menggunakan kedua metode

Metode mana yang lebih tepat: persentil atau SE?

Kunjungan dokter selama kehamilan

Rata-rata jumlah kunjungan dokter

Simpangan baku jumlah kunjungan dokter

Memusatkan kembali sebaran bootstrap

Uji median harga sewa apartemen 1 BR di Manhattan

Menyimpulkan uji hipotesis pada median

Uji untuk rata-rata berat bayi

Bootstrapping for estimating a parameter

In this chapter you'll use Central Limit Theorem based techniques to estimate a single parameter from a numerical distribution. You will do this using the t-distribution.

t-distribution

When to t?

Probabilities under the t-distribution

Cutoffs under the t-distribution

Estimating a mean with a t-interval

Average commute time of Americans

Average number of hours worked

t-interval for paired data

t-interval at various levels

Understanding confidence intervals

Testing a mean with a t-test

Estimate the median difference in textbook prices

Test for a difference in median test scores

Interpret the p-value

Introducing the t-distribution

In this chapter you'll extend what you have learned so far to use both simulation and CLT based techniques for inference on the difference between two parameters from two independent numerical distributions.

Hypothesis testing for comparing two means

Evaluating the effectiveness of stem cell treatment

Evaluating the effectiveness of stem cell treatment (cont.)

Conclusion of the hypothesis test

Evaluating the relationship between smoking during pregnancy and birth weight

Bootstrap CI for difference in two means

Quantifying the relationship between smoking during pregnancy and birth weight

Median lengths of pregnancies for smoking and non-smoking mothers

Comparing means with a t-test

Hourly pay vs. citizenship status

Estimating the difference of two means using a t-interval

Inference for difference in two parameters

In this chapter you will use ANOVA (analysis of variance) to test for a difference in means across many groups.

Vocabulary score vary between vs. (self identified) social class

EDA for vocabulary score vs. social class

Comparing many means, visually

ANOVA

ANOVA for vocabulary score vs. (self identified) social class

Conditions for ANOVA

Checking the normality condition

Checking the constant variance condition

Post-hoc testing

Calculate alpha*

Compare pairwise means

Congratulations!

Comparing many means

Chp1-vid1-boot-dist-noaxes-parantheses

Chp1-vid1-bootsamp-bootpop.001

Chp1-vid1-manhattan-rents

Chp1-vid2-boot-dist-withaxes

Chp1-vid2-perc-method.001

Chp1-vid2-perc-method.002

Chp1-vid3-boot-test.001

Chp3-vid3-hrly-rate-citizen-smaller

Chp3-vid3-hrly-rate-citizen

Chp4-vid1-class-bar

Chp4-vid1-wodrsum-hist

Gss moredays

GSS data

Manhattan rent data

Runners.001

Tdistcomparetonormaldist

Di kursus ini, Anda akan mempelajari cara menggunakan teknik statistik untuk melakukan inferensi dan estimasi menggunakan data numerik. Kursus ini menggunakan dua pendekatan untuk tugas-tugas umum tersebut. Pendekatan pertama memanfaatkan bootstrapping dan permutasi untuk membuat uji dan interval kepercayaan berbasis pengambilan ulang sampel. Pendekatan kedua menggunakan hasil teoretis dan sebaran t untuk mencapai hasil yang sama. Anda akan mempelajari cara (dan kapan) melakukan uji t, membuat interval kepercayaan, dan melakukan ANOVA!

Foundations of Inference in R

Pelajari teknik bootstrapping dan distribusi-t untuk inferensi statistik pada data numerik.

Inferensi untuk Data Numerik di R

Dalam kursus ini, Anda akan mempelajari teknik-teknik untuk melakukan inferensi statistik pada data numerik.

Penarikan Kesimpulan Statistik di R

Metode mana yang lebih tepat: persentil atau SE?

Inferensi untuk Data Numerik di R

Latihan interaktif langsung