Advance Analytics with Excel - data analysis toolpak/ Solver

Description

What is this course all about?

1. This course demonstrates how to use "Data Analysis ToolPak".
2. It explains the business scenario and then shows application of statistical procedure using data analysis tool pack on the given data.
3. The course also shows how to use Goal Seek and Solver (to solve linear optimization problems)
4. It gives clue about what is the most important portion of statistical procedure output and how to interpret it with respect to problem at hand.

Tags

• Statistical Analysis using Excel
• Linear optimization using Excel
• Data Analysis toolpak (Excel Add-in)
• Statistical Analysis case studies
• Data Analysis examples
• Data analysis using Excel

What Kind of Material is included

• All the excel files that has been used in videos are available to download.
• These excel contains data files, so that students can practice it on their own.

How long it should take to complete the course

It should take roughly 10 hours to practice and master all the procedure.

How is the course structured

The course first explains a business context and the data. Then it demonstrates how to use statistical procedure using data analysis tool pack. It Also explains how to solve linear programming problem using solver. It demonstrates how th use goal seek. The content of the course will be

1. Numeric data Analysis
2. Categorical data Analysis
3. Chi square test of independence
4. Simple Linear regression / Multiple linear regression
5. F test for equality of variances
6. T- Test for Comparing two sample means
7. Pair t test
8. ANOVA – single factor
9. ANOVA – two factor with / without replication
10. Generating random numbers with uniform / normal / poison distr.
11. Rank and Percentile
12. Histogram and pareto charts
13. Goal seek
14. Linear programming problem - Solver example

Why Take this course

1. To quickly understand how to perform statistical analysis using excel.
2. The understand, which are the most important portion of statistical procedure output and how to interpret it for a given context.
3. To understand the process of formulating linear programming cases in solver and getting solution.

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