Advance Analytics with Excel - data analysis toolpak/ Solver
3.8 (24 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
332 students enrolled
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Advance Analytics with Excel - data analysis toolpak/ Solver

Advanced data analysis in excel: Data Analysis tools (toolpak add-in) for statistics / solver for linear optimization
3.8 (24 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
332 students enrolled
Last updated 2/2017
English
Price: $20
30-Day Money-Back Guarantee
Includes:
  • 3 hours on-demand video
  • 2 Supplemental Resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I 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
View Curriculum
Requirements
  • Basic usage of Excel
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.
Who is the target audience?
  • 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" .
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Curriculum For This Course
Expand All 27 Lectures Collapse All 27 Lectures 02:49:39
+
Statistical Analysis
23 Lectures 02:29:18

Descriptive Statistics for Numerical Data Analysis
08:59

Excel files - where they are?
02:39

Interpret Descriptive statistics output
15:09

Pivot Table Analysis - count and percentage for each distinct category
05:06


Step by step - how to create pivot table based dashboard

Additional Topic - Creating BI kind of dashboard using Excel Pivot table part 02
05:07

Category wise Numeric data analysis using Pivot table
05:07

Cross tab Analysis
04:33

Chi Square Test of independence
15:02


Multiple Linear Regression
09:19

Comparing Two Sample Variances
06:13

Comparing Two Sample Means
06:20

Pair T Test
06:57


Two Factor ANOVA without replication
03:43

Two Factor ANOVA with replication
05:37

Generating Random Numbers, which has Normal / Poison / Uniform etc. Distribution
06:07

Rank and Percentile calculation
03:55

Histogram Procedure and Getting Pareto Chart
06:45

Exponential Smoothing and Moving Average
05:17

Random Sampling, Co-variance and Correlation procedure
06:29
+
Using Goal Seek
1 Lecture 02:49
Goal Seek Example
02:49
+
Solving Linear Optimization Problems using Excel Solver
3 Lectures 15:32
Example 1 - using solver for linear programming case
06:51

Example 2 - using solver for linear programming case
08:41

How to download Excel files
2 pages
About the Instructor
Gopal Prasad Malakar
4.2 Average rating
972 Reviews
14,270 Students
13 Courses
Credit Card Analytics Professional - Trains on Data Mining

I am a seasoned Analytics professional with 16+ years of professional experience. I have industry experience of impactful and actionable analytics. 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 and MS access based database application development.