Handle Missing Survey Data Values in Google Sheets

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Dans ce Projet guidé gratuit, vous :

Understand the value of handling missing values when preparing data for analysis.

Consider best practices for removing data entries in survey data sets and impute missing values with methods of centrality in Google Sheets.

Consider when survey values can be restored from other sources and impute values with cross-validation methods in Google Sheets.

Showcase this hands-on experience in an interview

Clock2 hours
BeginnerAdapté aux débutants
CloudAucun téléchargement requis
VideoVidéo en écran partagé
Comment DotsAnglais
LaptopOrdinateur de bureau uniquement

You have probably heard the expression “garbage in and garbage out.” When it comes to having confidence in a data set, “garbage in” refers having poor data quality. Poor data quality translates to poor quality or low confidence in the insights mined from the data. How do we shore up the data quality of a survey data set so we can have confidence in using that data for decision-making? We apply Exploratory Data Analysis or EDA methodology to identify strategies to handle and replace missing values. In your Handle Missing Survey Data Values in Google Sheets project, you will gain hands-on experience conducting EDA, identifying strategies for handling missing values, and replacing missing values in a survey data set. To do this you will work in the free-to-use spreadsheet software Google Sheets. By the end of this project, you will be able to confidently handle missing values in a survey data set to aid in shoring up the data quality and confidence in using the data for decision-making. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Conditions

Some familiarity with spreadsheet software is helpful, but not required.

Les compétences que vous développerez

Survey MethodologyStatistical Data PreparationImpute Missing ValuesBusiness IntelligenceData Validation

Apprendrez étape par étape

Votre enseignant(e) vous guidera étape par étape, grâce à une vidéo en écran partagé sur votre espace de travail :

  1. Review Exploratory Data Analysis (EDA) and how it is aids identifying missing values in a data set.

  2. Examine the handling of missing values in data preparation.

  3. Import data, identify missing values with a chart, and build a framework to handle them.

  4. Review when to remove data entries and impute missing values with methods of centrality.

  5. Impute survey data values through cross-validation.

Comment fonctionnent les projets guidés

Votre espace de travail est un bureau cloud situé dans votre navigateur, aucun téléchargement n'est requis.

Votre enseignant(e) vous guide étape par étape dans une vidéo en écran partagé

Foire Aux Questions

Foire Aux Questions

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