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Business Business Analytics & Intelligence Excel Analytics

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
Rating: 4.2 out of 54.2 (362 ratings)
2,026 students
Created by Gopal Prasad Malakar
Last updated 1/2021
English
English
30-Day Money-Back Guarantee

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
Curated for the Udemy for Business collection

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 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" .

Course content

3 sections • 28 lectures • 2h 49m total length

  • Preview02:39
  • 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
  • Preview02:21
  • 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
  • Preview11:07
  • Multiple Linear Regression
    09:19
  • Comparing Two Sample Variances
    06:13
  • Comparing Two Sample Means
    06:20
  • Pair T Test
    06:57
  • Preview04:47
  • 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

  • Goal Seek Example
    02:49
  • Solving a puzzle using Goal Seek
    00:04

  • 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

Instructor

Gopal Prasad Malakar
Trains Industry Practices on data science / machine learning
Gopal Prasad Malakar
  • 4.0 Instructor Rating
  • 9,410 Reviews
  • 105,462 Students
  • 16 Courses

       I am a seasoned Analytics professional with 18+ 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

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