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Advance Analytics with Excel - data analysis toolpak/ Solver
Rating: 4.3 out of 5(1,631 ratings)
7,754 students

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
Created byGopal Prasad Malakar
Last updated 1/2021
English
EnglishTurkish [Auto],

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

Course content

3 sections • 28 lectures • 2h 47m total length

  • Course Content2:39

    Explore descriptive and categorical data analysis with pivot tables, chi-square test of independence, regression (simple and multiple), anova, t-tests, f-tests, plus solver and goal seek for linear programming in Excel.

  • Descriptive Statistics for Numerical Data Analysis8:59
  • Excel files - where they are?2:39

    Open the download area and click view resource to reveal the Excel data files associated with the course, then download what’s available.

  • Interpret Descriptive statistics output15:09

    Learn to interpret descriptive statistics in Excel from a mileage dataset, including sum, mean, median, mode, variance, standard deviation, skewness, kurtosis, standard error, and 95% confidence intervals.

  • Pivot Table Analysis - count and percentage for each distinct category5:06
  • Additional Topic - Creating BI kind of dashboard using Excel Pivot table part 012:21

    Learn to build a BI-style dashboard in Excel with pivot tables, enabling regional filtering, drill-down, and real-time updates of total price, quantity, and average case price.

  • Additional Topic - Creating BI kind of dashboard using Excel Pivot table part 025:07

    Step by step - how to create pivot table based dashboard

  • Category wise Numeric data analysis using Pivot table5:07

    Use pivot tables to perform category-wise numeric analysis in Excel, calculating average mileage by headroom and extending to standard deviation, min, and max price for each category.

  • Cross tab Analysis4:33
  • Chi Square Test of independence15:02

    Learn to analyze response rates by gender and status using Excel pivot tables, compute percentages, and test independence with chi-square, including merging categories to meet expected counts and interpreting p-values.

  • Simple Linear Regression11:07
  • Multiple Linear Regression9:19

    Learn to run a multiple regression in Excel’s data analysis toolpak, relate mileage to headroom, weight, length, and trunk space, and interpret R-square, p-values, and a parsimonious model.

  • Comparing Two Sample Variances6:13
  • Comparing Two Sample Means6:20
  • Pair T Test6:57
  • One Factor (One Way) ANOVA4:47

    Explore one-way ANOVA to compare trainer groups using Excel data analysis toolpak, interpreting p-values to determine if means differ across five trainer groups.

  • Two Factor ANOVA without replication3:43
  • Two Factor ANOVA with replication5:37
  • Generating Random Numbers, which has Normal / Poison / Uniform etc. Distribution6:07
  • Rank and Percentile calculation3:55

    Rank students and compute percentiles in Excel using the Data Analysis Toolpak, then map results to roll numbers with VLOOKUP and fixed ranges.

  • Histogram Procedure and Getting Pareto Chart6:45

    Automate histogram and Pareto chart creation in Excel using the data analysis toolpak, selecting bins to reveal the data's distribution and cumulative frequencies.

  • Exponential Smoothing and Moving Average5:17
  • Random Sampling, Co-variance and Correlation procedure6:29

    Use the Excel data analysis toolpak to perform random sampling and generate a correlation matrix and covariance, interpreting r-values for headroom, trunk space, weight, and length.

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" .

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