• Post category:StudyBullet-3
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How to use Excel for statistics calculation and advanced data analysis

What you will 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

 

Description

 

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.


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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.

 

 

English
language

 

Content

 
Introduction
Introduction
Univariate analysis
Minimum, maximum and count
Mean value
Variance and standard deviation
Skewness
Median, quantiles and percentiles
Interquartile Range
Conditional operations on a single variable
Advanced univariate analysis
Outlier labeling with IQR
Moving average
Rolling maximum and minimum
Percentage change
Confidence intervals of the mean value
Confidence intervals of a proportion
Multivariate analysis
Linear correlation coefficient
Linear regression with predictions
Hypothesis tests
One sample t-test
Two samples t-test
F-test for variance
Chi-square test
Z table
T table
Database operations
Conditional operations on a table
Vertical lookup
Database operations
Pivot tables
How to create a pivot table
Filters on pivot tables
Group by rows and columns
Representation of the results