# Analyzing Survey Data in Python
This is a DataCamp course: Learn how to analyze survey data with Python and discover when it is appropriate to apply statistical tools that are descriptive and inferential in nature.
## Course Details
- **Duration:** ~4h
- **Level:** Intermediate
- **Instructor:** EbunOluwa Andrew
- **Students:** ~19,440,000 learners
- **Subjects:** Python, Probability & Statistics, Data Science and Analytics
- **Content brand:** DataCamp
- **Practice:** Hands-on practice included
- **Prerequisites:** Hypothesis Testing in Python
## Learning Outcomes
- Python
- Probability & Statistics
- Data Science and Analytics
- Analyzing Survey Data in Python
## Traditional Course Outline
1. Why Analyze Survey Data & When to Apply Statistical Tools - 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.
2. Sampling and Weighting - 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.
3. Descriptive & Inferential Statistics - 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.
4. Statistical Modeling - 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.
## Resources and Related Learning
No public datasets, resources, or related tracks are listed for this course.
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Course
Analyzing Survey Data in Python
IntermediateSkill Level
Updated 11/2023PythonProbability & Statistics4 hr14 videos46 Exercises3,700 XP2,729Statement of Accomplishment
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Try DataCamp for BusinessCourse Description
Learn How to Use Python on Survey Data
Whether it is a company looking to understand its employees’ work preferences or a marketing campaign wanting to know how to best cater to its dominant audience, survey data is one of the best tools used to better understand a population and how to proceed on a matter. Here, you’ll learn the purpose of analyzing survey data and when it is appropriate to apply statistical tools that are descriptive and inferential in nature.
Get Familiar with Key Statistical Survey Analysis Tools
Building on topics covered in Hypothesis Testing in Python, this hands-on course allows you to become familiar with using Python to analyze all sorts of survey data.
You will learn to apply various sampling methods, ensuring that you accurately represent the population in a study and can infer their effects on the conclusion from your analysis.
As you visualize your survey results, you’ll also qualitatively interpret the variables and results associated with modeling tests such as linear regression, the two-sample t-test, and the chi-square test, as it pertains to the type of survey you’re analyzing.
Prerequisites
Hypothesis Testing in Python1
Why Analyze Survey Data & When to Apply Statistical Tools
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.
2
Sampling and Weighting
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.
3
Descriptive & Inferential Statistics
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.
4
Statistical Modeling
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.
Analyzing Survey Data in Python
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FAQs
What statistical methods for survey analysis does this course teach?
You learn sampling methods, descriptive statistics, inferential techniques including z-scores, regression analysis, two-sample t-tests, and chi-square tests applied specifically to survey data.
Is this course focused on creating surveys or analyzing them?
It focuses entirely on analyzing existing survey data, teaching you how to choose appropriate statistical tools, visualize results, and interpret findings for actionable insights.
What Python libraries are used in this course?
You use Python with pandas for data manipulation and standard statistical libraries. Prerequisites include pandas, statistics, hypothesis testing, and sampling courses.
Does the course cover different sampling methods?
Yes. Chapter 2 teaches multiple approaches to creating sample survey data from population data and how to apply appropriate weighting to your samples.
Who would find this course most useful?
Market researchers, HR analysts, and anyone who regularly works with questionnaire or opinion data will benefit from learning systematic approaches to survey data analysis in Python.
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