Statistics and data analysis with Excel

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Paid

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Level

Beginner

Last updated on October 15, 2024 9:43 am

Learn how to perform advanced statistical calculations and data analysis using Microsoft Excel. This course is perfect for data analysts, marketing experts, and data scientists. Topics covered include descriptive analysis, outlier detection, confidence intervals, correlation and regression forecasting, hypothesis tests, database operations, and pivot tables. Each video lesson includes a practical example in Excel, with downloadable spreadsheets provided. Excel is a valuable tool for anyone who needs to crunch data and perform various analyses.

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What you’ll learn

  • Basic and advanced univariate statistics in Excel
  • Hypothesis tests (Student’s t test, chi-square, F-test, Welch test), t-table and z-table
  • Confidence intervals for mean value and proportions
  • Correlation coefficient and linear regression forecast
  • Outlier identification
  • Database operations
  • Pivot tables

In this practical course, we are going to focus on how to perform advanced statistical calculations and data analysis using Microsoft Excel.

Excel is a very used tool in several companies and has very powerful data analysis capabilities that can be used by data analysts and marketing experts. Even if you work with a lot of statistics you’d be surprised at how valuable Excel is for calculating hypothesis tests and the most common metrics you can calculate on a dataset. There are several basic and advanced functions you can use to get the best from your data and that’s why Excel is a very useful tool for anybody who needs to crunch data and perform analyses of various kinds.

This course can be attended by both data analysts and marketing experts who need to work with data and surveys.

With this course, you are going to learn:

  1. Univariate descriptive analysis (mean, standard deviation, skewness, quantiles, percentiles, IQR)

  2. Advanced univariate analysis (outlier detection, rolling measures)

  3. Confidence intervals

  4. Linear correlation and regression forecasting

  5. Hypothesis tests (Student’s t-test, chi-square test, F-test, Welch test)

  6. t tables and z tables

  7. Database operations and conditional operations

  8. Vertical lookup

  9. Pivot tables

All the video lessons of this course start with a brief introduction and end with a practical example in Excel. All the Excel spreadsheets are attached to each lesson and can be downloaded.

Who this course is for:

  • Data analysts
  • Marketing experts
  • Data scientists

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    Statistics and data analysis with Excel
    Statistics and data analysis with Excel
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