Sebaran jawaban yes dan no

Perusahaan Anda, ABC, menugaskan Anda melakukan survei kepada karyawan untuk mengetahui minat mereka terhadap kerja di kantor.

Survei awal pada seluruh populasi karyawan perusahaan ABC, ABC_survey, memuat respons "Yes" dan "No" terhadap pertanyaan apakah karyawan ingin bekerja di kantor, onsite_work.

Dalam latihan ini, Anda akan dengan cepat menarik kesimpulan tentang preferensi karyawan terkait kerja di kantor.

pandas dan matplotlib.pyplot telah diimpor untuk Anda sebagai pd dan plt.

Latihan ini adalah bagian dari kursus

Menganalisis Data Survei di Python

Lihat Kursus

Petunjuk latihan

Buat bagan pai yang memvisualisasikan sebaran awal jawaban "Yes" dan "No" untuk pertanyaan bekerja di kantor.

Latihan interaktif praktis

Cobalah latihan ini dengan menyelesaikan kode contoh berikut.

# Create a pie chart to the question of working onsite
ABC_survey.____.____.____.____
plt.show()

Edit dan Jalankan Kode

Latihan ini adalah bagian dari kursus

Menganalisis Data Survei di Python

SkillTag.level.intermediateSkillTag.label

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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

Latihan Saat Ini

Exercise 6: Pengambilan sampel berstrata 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