Veriyi görselleştir: histogram

İstatistik dersi projen için, genç yetişkinlerde belirli tercihlerde cinsiyet farklılıklarını daha iyi anlamak amacıyla arkadaşlarından bir ankete katılmalarını istedin. Anketin bir bölümü olan young_people, katılımcıların Gender, Age, Height ve Weight bilgilerini sordu.

Bu egzersizde, katılımcıların boy dağılımını görselleştireceksin.

pandas, scipy.stats ve matplotlib.pyplot sırasıyla pd, stats ve plt kısaltmalarıyla senin için yüklendi.

Bu egzersiz

Python ile Anket Verilerini Analiz Etme

kursunun bir parçasıdır

Kursu Görüntüle

Egzersiz talimatları

Height sütunundaki değerlerin dağılımını bir histogram kullanarak çiz.

Uygulamalı interaktif egzersiz

Bu örnek kodu tamamlayarak bu egzersizi bitirin.

# Histogram of Height column
young_people.____.____(kind=____)
plt.show()

Kodu Düzenle ve Çalıştır

Bu egzersiz

Python ile Anket Verilerini Analiz Etme

kursunun bir parçasıdır

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Kursa Ücretsiz Başlayın

What is survey data, and how do we determine which statistical test to use to analyze the data? To answer this, you’ll be able to define all sorts of survey data types, encounter important concepts like descriptive and inferential statistics, and visualize survey data to determine the appropriate statistical modeling technique needed. In doing so, you will know how to best qualitatively and quantitatively define the trends and insights you come across in surveys.

Exercise 1: Introducing Survey Data Analysis Exercise 2: Looking at levels of measurements Exercise 3: Crosstabulation Exercise 4: Descriptive and Inferential Statistics Exercise 5: Descriptive statistics Exercise 6: Inferential statistics Exercise 7: Statistical Modeling Techniques Exercise 8: Scatter plot inspection Exercise 9: Choose a statistical method Exercise 10: Sampling technique match

In this chapter, you’ll learn the different ways of creating sample survey data out of population survey data by analyzing the parameters by which the survey data was taken.

Exercise 1: Random sampling Exercise 2: Random sample of employees Exercise 3: Reproducible random sampling Exercise 4: Stratified Random Sampling Exercise 5: Spread of yes's and no's Exercise 6: Stratified sampling Exercise 7: Weighted sampling Exercise 8: Blog survey Exercise 9: Weighted sampling on handedness Exercise 10: Cluster Sampling Exercise 11: Group clusters Exercise 12: Choosing clusters Exercise 13: Cluster sampling analysis

Now it’s time to understand the difference between descriptive and inferential statistics concerning survey data analysis with some real-life examples. Through hands-on exercises, you’ll further interpret the meaning of different variables, key measures such as central tendency and zscore, and interpret results for actionable steps.

Exercise 1: Anket analizinde betimsel istatistikler Exercise 2: Frekans dağılımı Exercise 3: Değişkenlik Ölçüleri Exercise 4: Merkezi eğilim ölçüleri Exercise 5: Anket analizinde çıkarımsal istatistikler Exercise 6: Veriyi görselleştir: histogram

Geçerli Egzersiz

Exercise 7: z-score'u bul Exercise 8: Korelasyonlar Exercise 9: .corr() ile değişkenleri analiz et Exercise 10: Çalışanlar mutlu mu?Exercise 11: Adil ve açık

Last but not least, it’s time to apply statistical modeling to survey data analysis with regression analysis, the two-sample t-test, chi-square test, and interpret the assumptions associated with these tests.

Exercise 1: Regression analysis Exercise 2: Fitting a linear regression model Exercise 3: Visualizing survey data Exercise 4: Safety precautions needed?Exercise 5: Two sample t-test Exercise 6: Are women more extroverted?Exercise 7: Two sample t-test on extraversion Exercise 8: Chi-square test Exercise 9: To chi-square or not to chi-square?Exercise 10: Mental health in tech survey Exercise 11: Mental health vs. remote work Exercise 12: Congratulations