Pengambilan sampel berstrata

Anda adalah bagian dari sebuah agensi yang mengirimkan survei remaja kepada sampel remaja yang mewakili populasi nasional, usia 14 hingga 20 tahun. Himpunan data yang diunggah, youth_survey, mencatat Age, Height (in inches), Weight (in pounds), Gender, dan jawaban pilihan ganda pelaporan diri How would you describe your weight? untuk setiap individu.

Dalam latihan ini, Anda akan membuat sampel berstrata berbobot sebesar 1% dari responden dalam himpunan data. pandas telah diimpor sebagai pd.

Himpunan data berisi informasi tentang gender semua responden, sehingga Anda akan menggunakan kolom Gender sebagai kolom stratifikasi.

Latihan ini adalah bagian dari kursus

Menganalisis Data Survei di Python

Lihat Kursus

Latihan interaktif praktis

Cobalah latihan ini dengan menyelesaikan kode contoh berikut.

# Calculate the percentage of female and male respondents
print(youth_survey.Gender____(normalize=____) * 100)

Edit dan Jalankan Kode

Latihan ini adalah bagian dari kursus

Menganalisis Data Survei di Python

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Mulai Kursus Gratis

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: Pengambilan sampel acak Exercise 2: Sampel acak karyawan Exercise 3: Pengambilan sampel acak yang dapat direproduksi Exercise 4: Stratified Random Sampling Exercise 5: Sebaran jawaban yes dan no Exercise 6: Pengambilan sampel berstrata

Latihan Saat Ini

Exercise 7: Pengambilan sampel berbobot Exercise 8: Survei blog Exercise 9: Pengambilan sampel berbobot pada kecondongan tangan Exercise 10: Sampling Klaster Exercise 11: Kelompokkan klaster Exercise 12: Memilih klaster Exercise 13: Analisis pengambilan sampel klaster

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: Descriptive statistics in survey analysis Exercise 2: Frequency distribution Exercise 3: Measures of variability Exercise 4: Measures of central tendency Exercise 5: Inferential statistics in survey analysis Exercise 6: Visualize data: histogram Exercise 7: Find the z-score Exercise 8: Correlations Exercise 9: Analyze variables with .corr()Exercise 10: Are employees happy?Exercise 11: Fair and square

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