Pengujian hipotesis - Statistik non-standar

Pada dua latihan sebelumnya, kita menjalankan uji permutasi untuk perbedaan nilai mean. Sekarang mari melihat statistik non-standar.

Misalkan Anda ingin memahami distribusi donasi yang diterima dari situs web A dan B. Untuk itu, Anda ingin melihat apakah ada perbedaan yang signifikan secara statistik pada median dan persentil ke-80 dari donasi. Pengujian permutasi memberikan kerangka kerja yang sangat fleksibel untuk menangani masalah seperti ini.

Mari kita jalankan sebuah uji untuk melihat apakah ada perbedaan pada median dan persentil ke-80 dari distribusi donasi. Seperti sebelumnya, Anda diberikan donasi dari situs web A dan B dalam variabel donations_A dan donations_B masing-masing.

Latihan ini adalah bagian dari kursus

Simulasi Statistik di Python

Latihan interaktif praktis

Cobalah latihan ini dengan menyelesaikan kode contoh berikut.

# Calculate the difference in 80th percentile and median for each of the permuted datasets (A and B)
samples_percentile = np.____(permuted_A_datasets, 80, axis=1) - np.____(permuted_B_datasets, 80, axis=1)
samples_median = np.____(permuted_A_datasets, axis=1) - np.____(permuted_B_datasets, axis=1)

Edit dan Jalankan Kode

Latihan ini adalah bagian dari kursus

Simulasi Statistik di Python

SkillTag.level.intermediateSkillTag.label

4.9+

Mulai Kursus Gratis

This chapter gives you the tools required to run a simulation. We'll start with a review of random variables and probability distributions. We will then learn how to run a simulation by first looking at a simulation workflow and then recreating it in the context of a game of dice. Finally, we will learn how to use simulations for making decisions.

Exercise 1: Introduction to random variables Exercise 2: np.random.choice()Exercise 3: Poisson random variable Exercise 4: Shuffling a deck of cards Exercise 5: Simulation basics Exercise 6: Throwing a fair die Exercise 7: Throwing two fair dice Exercise 8: Simulating the dice game Exercise 9: Using simulation for decision-making Exercise 10: Simulating one lottery drawing Exercise 11: Should we buy?Exercise 12: Calculating a break-even lottery price

This chapter provides a basic introduction to probability concepts and a hands-on understanding of the data generating process. We'll look at a number of examples of modeling the data generating process and will conclude with modeling an eCommerce advertising simulation.

Exercise 1: Probability basics Exercise 2: Queen and spade Exercise 3: Two of a kind Exercise 4: Game of thirteen Exercise 5: More probability concepts Exercise 6: The conditional urn Exercise 7: Birthday problem Exercise 8: Full house Exercise 9: Data generating process Exercise 10: Driving test Exercise 11: National elections Exercise 12: Fitness goals Exercise 13: eCommerce Ad Simulation Exercise 14: Sign up Flow Exercise 15: Purchase Flow Exercise 16: Probability of losing money

In this chapter, we will get a brief introduction to resampling methods and their applications. We will get a taste of bootstrap resampling, jackknife resampling, and permutation testing. After completing this chapter, students will be able to start applying simple resampling methods for data analysis.

Exercise 1: Pengantar metode pengambilan sampel ulang Exercise 2: Pengambilan sampel dengan pengembalian Exercise 3: Contoh probabilitas Exercise 4: Bootstrapping Exercise 5: Menjalankan bootstrap sederhana Exercise 6: Estimator non-standar Exercise 7: Bootstrapping regresi Exercise 8: Pengambilan sampel jackknife Exercise 9: Estimasi jackknife dasar - mean Exercise 10: Interval kepercayaan jackknife untuk median Exercise 11: Uji permutasi Exercise 12: Membuat satu permutasi Exercise 13: Pengujian hipotesis - Selisih rata-rata Exercise 14: Pengujian hipotesis - Statistik non-standar

Latihan Saat Ini

In this chapter, students will be introduced to some basic and advanced applications of simulation to solve real-world problems. We'll work through a business planning problem, learn about Monte Carlo Integration, Power Analysis with simulation and conclude with a financial portfolio simulation. After completing this chapter, students will be ready to apply simulation to solve everyday problems.

Exercise 1: Simulation for Business Planning Exercise 2: Modeling Corn Production Exercise 3: Modeling Profits Exercise 4: Optimizing Costs Exercise 5: Monte Carlo Integration Exercise 6: Integrating a Simple Function Exercise 7: Calculating the value of pi Exercise 8: Simulation for Power Analysis Exercise 9: Factors influencing Statistical Power Exercise 10: Power Analysis - Part I Exercise 11: Power Analysis - Part II Exercise 12: Applications in Finance Exercise 13: Portfolio Simulation - Part I Exercise 14: Portfolio Simulation - Part II Exercise 15: Portfolio Simulation - Part III Exercise 16: Wrap Up