Advance Analytics with Excel - data analysis toolpak/ Solver
What you'll learn
- Perform Data Analysis / Statistical Analysis using Excel
- Be comfortable with data analysis tool pack / solver / goal seek
- Understand the business context / scenario where the statistical procedure is applicable
- Understand the most important portion of statistical procedure output and how to interpret it for a given scenario
- Know how to solve linear programming cases using solver
Requirements
- Basic usage of Excel
Description
What is this course all about?
- This course demonstrates how to use "Data Analysis ToolPak".
- It explains the business scenario and then shows application of statistical procedure using data analysis tool pack on the given data.
- The course also shows how to use Goal Seek and Solver (to solve linear optimization problems)
- 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
- Numeric data Analysis
- Categorical data Analysis
- Chi square test of independence
- Simple Linear regression / Multiple linear regression
- F test for equality of variances
- T- Test for Comparing two sample means
- Pair t test
- ANOVA – single factor
- ANOVA – two factor with / without replication
- Generating random numbers with uniform / normal / poison distr.
- Rank and Percentile
- Histogram and pareto charts
- Goal seek
- Linear programming problem - Solver example
Why Take this course
- To quickly understand how to perform statistical analysis using excel.
- The understand, which are the most important portion of statistical procedure output and how to interpret it for a given context.
- To understand the process of formulating linear programming cases in solver and getting solution.
Who this course is for:
- This course is for professionals who quickly want to learn statistical analysis / data analysis procedure / solver usage for getting solution of linear programming cases
- This course is not for someone, who is looking to get deep understanding of statistics / genesis of formula etc. For that I will recommend you to check my course "Statistics by Example" .
Instructor
![Gopal Prasad Malakar](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.2 Instructor Rating
- 10,432 Reviews
- 110,323 Students
- 17 Courses
I am a seasoned Analytics professional with 20+ years of professional experience. I have industry experience of impactful and actionable analytics, data science, decision strategy and enterprise wise data strategy.
I am a keen trainer, who believes that training is all about making users understand the concepts. If students remain confused after the training, the training is useless. I ensure that after my training, students (or partcipants) are crystal clear on how to use the learning in their business scenarios.
My expertise is in Credit Card Business, Scoring (econometrics based model development), score management, loss forecasting, business intelligence systems like tableau /SAS Visual Analytics, MS access based database application development, Enterprise wide big data framework and streaming analysis.
Please refer to my course for
- SAS / R program details (syntax and options)
- SAS / R output deep dive
- Practical usage in Industrial situation