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Analyzing Survey Data in Python

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.

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4 Hours14 Videos46 Exercises

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Course 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.
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  1. 1

    Why Analyze Survey Data & When to Apply Statistical Tools

    Free

    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.

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    Introducing Survey Data Analysis
    50 xp
    Looking at levels of measurements
    50 xp
    Crosstabulation
    100 xp
    Descriptive and Inferential Statistics
    50 xp
    Descriptive statistics
    100 xp
    Inferential statistics
    100 xp
    Statistical Modeling Techniques
    50 xp
    Scatter plot inspection
    100 xp
    Choose a statistical method
    50 xp
    Sampling technique match
    100 xp
  2. 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.

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Collaborators

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Izzy Weber
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Jasmin Ludolf
Collaborator's avatar
Maham Khan

Prerequisites

Hypothesis Testing in Python
EbunOluwa Andrew HeadshotEbunOluwa Andrew

Data Scientist

Ebun Andrew is a petroleum engineer and data scientist who discovered her passion and interest for data science and analytics while taking a DataCamp course! Her main interests are blogging, visiting new cities, and dabbling in all sorts of exquisite cuisines.
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