Olasılık dağılımı oluşturma

Birkaç ay önce yeni bir restoran açıldı ve yönetim, en sık gelen grupların büyüklüklerine göre oturma düzenini iyileştirmek istiyor. Bir akşam, restoranda oturmayı bekleyen 10 grup var; ancak geliş sırasına göre değil, rastgele çağrılacaklar. Bu egzersizde, farklı büyüklükteki grupların ilk seçilme olasılığını inceleyeceksin. On grubun her birine ait veriler restaurant_groups DataFrame'inde yer alıyor.

Beklenen değerin, her olası sonucun kendi olasılığıyla çarpılıp toplanmasıyla hesaplandığını unutma. restaurant_groups verisi hazır. pandas pd olarak, numpy np olarak ve matplotlib.pyplot plt olarak yüklü.

Bu egzersiz, kursun bir parçasıdır

Python ile İstatistiğe Giriş

Kursa Göz Atın

Uygulamalı etkileşimli egzersiz

Bu egzersizi bu örnek kodu tamamlayarak deneyin.

# Create a histogram of restaurant_groups and show plot
restaurant_groups['group_size'].____
____

Kodu Düzenle ve Çalıştır

Bu egzersiz, kursun bir parçasıdır

Python ile İstatistiğe Giriş

IntermediárioNível de habilidade

4.8+

Kursa Ücretsiz Başla

Summary statistics gives you the tools you need to boil down massive datasets to reveal the highlights. In this chapter, you'll explore summary statistics including mean, median, and standard deviation, and learn how to accurately interpret them. You'll also develop your critical thinking skills, allowing you to choose the best summary statistics for your data.

Exercise 1: What is statistics?Exercise 2: Descriptive and inferential statistics Exercise 3: Data type classification Exercise 4: Measures of center Exercise 5: Calculating mean and median Exercise 6: Mean, median, and distribution shape Exercise 7: Measures of spread Exercise 8: Variance and standard deviation Exercise 9: Quartiles, quantiles, and quintiles Exercise 10: Finding outliers using IQR

In this chapter, you'll learn how to generate random samples and measure chance using probability. You'll work with real-world sales data to calculate the probability of a salesperson being successful. Finally, you’ll use the binomial distribution to model events with binary outcomes.

Exercise 1: Şansın ne kadar?Exercise 2: Yerine koyarak mı, koymadan mı?Exercise 3: Olasılıkları hesaplama Exercise 4: Anlaşmaları örnekleme Exercise 5: Ayrık dağılımlar Exercise 6: Olasılık dağılımı oluşturma

Geçerli egzersiz

Exercise 7: Dağılımları belirleme Exercise 8: Beklenen değer vs. örneklem ortalaması Exercise 9: Sürekli dağılımlar Exercise 10: Hangi dağılım?Exercise 11: Veri yedeklemeleri Exercise 12: Bekleme sürelerini simüle etme Exercise 13: Binom dağılımı Exercise 14: Satış anlaşmalarını simüle etme Exercise 15: Binom olasılıklarını hesaplama Exercise 16: Kaç satış kazanılacak?

It’s time to explore one of the most important probability distributions in statistics, normal distribution. You’ll create histograms to plot normal distributions and gain an understanding of the central limit theorem, before expanding your knowledge of statistical functions by adding the Poisson, exponential, and t-distributions to your repertoire.

Exercise 1: The normal distribution Exercise 2: Distribution of Amir's sales Exercise 3: Probabilities from the normal distribution Exercise 4: Simulating sales under new market conditions Exercise 5: Which market is better?Exercise 6: The central limit theorem Exercise 7: Visualizing sampling distributions Exercise 8: The CLT in action Exercise 9: The mean of means Exercise 10: The Poisson distribution Exercise 11: Identifying lambda Exercise 12: Tracking lead responses Exercise 13: More probability distributions Exercise 14: Distribution dragging and dropping Exercise 15: Modeling time between leads Exercise 16: The t-distribution

In this chapter, you'll learn how to quantify the strength of a linear relationship between two variables, and explore how confounding variables can affect the relationship between two other variables. You'll also see how a study’s design can influence its results, change how the data should be analyzed, and potentially affect the reliability of your conclusions.

Exercise 1: Correlation Exercise 2: Guess the correlation Exercise 3: Relationships between variables Exercise 4: Correlation caveats Exercise 5: What can't correlation measure?Exercise 6: Transforming variables Exercise 7: Does sugar improve happiness?Exercise 8: Confounders Exercise 9: Design of experiments Exercise 10: Study types Exercise 11: Longitudinal vs. cross-sectional studies Exercise 12: Congratulations!