MS Excel: Statistics and Data Analysis
4.1 (21 ratings)
124 students enrolled

# MS Excel: Statistics and Data Analysis

Perform Statistical analysis beginning from descriptives to hypothesis testing using MS-Excel Analysis Toolpak
4.1 (21 ratings)
124 students enrolled
Last updated 2/2016
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This course includes
• 1.5 hours on-demand video
• Access on mobile and TV
• Certificate of Completion
Training 5 or more people?

What you'll learn
• Design, Develop and administer questionnaires, Collect data from different sources, Enhance ability to analyze data, and Derive inferences to take successful decisions. Data Analysis speed and accuracy will enhance 10x.
Requirements
• Quest to analyze legions of Data
• An understanding of Excel
Description

Present day organizations are data driven. Starting from Start-ups to Conglomerates every organization is relying on data for decision making. Organizations are flooded with data from multiple facets (websites, social network sites, third party data sources, daily operational data etc). Skimming this data to get meaningful information has become daunting task for organizations. They are looking for skilled manpower who can convert this gigantic data into sleek information for decision making. This course is for the beginners who wish to test the water in Data Analytics.

This course fuses Statistical Analysis with MS Excel because of which you would be able to churn legions of data into meaningful information within no time. Excel has hundreds of built-in functions and Data Analysis Toolpak (Excel Add-in) with which you can run descriptive statistics to predictive analysis with ease. In this course I created videos that help you understand statistical concepts and solve complex equations using Excel. Excel Workbooks are provided to you for practice and master the concepts.

Who this course is for:
• Students who want to pursue career as Data Analyst, Data Scientist, Research Associates
• Social Science students who want to do empirical research report/ Project Assignment / Thesis
• Business Management Students (all streams)
• Research Scholars / Research Students of Social Sciences and Business Management
• All professionals who want to turn data into information
• Entrepreneurs who wants to leverage of Data
Course content
Expand all 30 lectures 01:35:14
+ Introduction to the Course
1 lecture 02:18

Know what is there in this course for you. For whom this course is and how are you going to benefitted from this course.

Preview 02:18
+ Statistics - Understanding the Basics
7 lectures 13:18

Organizations expect you to perform statistical analysis on your own. You need to crunch data as per your requirements. As you work in intense competitive work environment you don’t have a luxury to take days and days to crunch data.A strong theoretical knowledge of statistics is not suffice, you should also be able to collect, organize, visualize and analyze data with Software.

In this course you will learn how to design a research project, source data, clean data, perform data analysis with MS-Excel, interpret results, and complete research assignment in stipulated time frame.

Along with video lectures, you are provided with pdf notes and Excel work sheets to practice the learning.

Introduction to Statistics- What is in it for me
01:46

In this lecture you will learn the DCOVA frame work. You are introduced to Design, Collection, Organizing, Visualizing, and Analyzing Data.

This lecture is vital for your research projects. Majority of research projects commence with an well articulated to research plan.

The DCOVA framework
02:22

On completion of this lecture you will be able to differentiate descriptive stats with inferential stats.

Descriptive Statistics and Inferential Statistics
01:55
In this lecture you will learn about Variable Types and what statistical techniques should be run on different variable types
Variable types (Categorical Variables, Numerical Variables)
01:38

Learn about types of Variables or Data Sets and pertinent statistical tools for each type of data set.

In this lecture you are introduced to univariate, bivariate, and mutlivariate data sets. And what types of charts and statistical techniques need to be used for each data set type is also explained.

Number of Variables - Types of Analysis
01:40

Get familiar with measurements of scales in statistics. You will learn about - Nominal Scale, Ordinal Scale, Interval Scale and Ratio Scale.

I will also learn how and when to use each measurement scale to source the data.

Measurement Scales for Variables
02:06

In this lecture I will introduce you to Primary Data sources (experimental, observational, and survey data), and also to Secondary Data sources (Distributed data, Data from daily business activities)

Data Sources (Primary Data sources, Secondary Data sources)
01:51
+ Sort Data and Draw Random Samples
4 lectures 13:22
Learn how to Sort data and create Filters in MS-Excel. This lecture would be a great help in drawing random samples from large population.
Sorting Data using Excel
03:27

Learn how to sort data using column heading and create advanced filters in MS-Excel.

01:47

Learn how to draw cluster random sample with the help of MS-Excel by using highly clustered real time large data set.

Preview 03:56
Learn how to draw stratified random sample using MS-Excel built-in tools and make your sample proxy for population.
Drawing Stratified Random Sample using Excel
04:12
+ Data Presentation
1 lecture 03:25

Learn how to create charts to identify trends, clusters, extreme values using MS-Excel Chart Wizard.

Drawing charts is the first step in your data presentation. With MS-Excel you can create eye catching charts and present your data in vibrant way.

You are introduced to different chart types like, column, line, bar, scatter, stock etc. and when to you which chart type.

Creating Chart to get Bird's Eye View with Excel
03:25
+ Descriptive Statistics
4 lectures 12:02

Data Analysis Toolpak is an Excel add-in program. However, you need to load it manually. Once you load the Data Analysis Toolpak, a Data Analysis command button will appear under Data menu ribbon.

With the help of Data Analysis command button you can run many statistical tools like, histograms, correlation, regression, anova, t-test, independent t-test, moving averages, exponential smoothing etc, with writing any formulas.

Irrespective of the size of your data, you can run the analysis in few minutes.

How to Load the Analysis Toolpak in Excel
01:42

Compute descriptive statistics methods like Mean, Median, Mode, Variance, Standard Deviation,

Skewness, and Kurtosis in few clicks with the help of MS-Excel Data Analysis command. It takes just a minute to calculate all the descriptives, irrespective of number of records or data points.

Preview 02:10

Calculate grouped frequency distribution, cumulative percentage, histogram, and normal curve chart with MS-Excel Data Analysis command.

Calculating Frequency Distribution and Histogram with Data Analysis Command
04:51

In this lecture you will learn The Empirical Rule and Tests of Normality. Also learn how to interpret the standard deviation, and test normality of data using Skewness and Kurtosis.

The Empirical Rule - Tests of Normality
03:19
+ Bivariate Analysis (Correlation Analysis)
2 lectures 08:33

The first step in understanding the relationship between two variables is to plot the data on scatter plot. In this lecture you will learn how to draw a scatter plot and fit trend line on Bivariate data set.

Preview 03:08

Correlation is used to find out relationship between Bivariate and multivariate data sets. In this lecture you will learn how to compute correlation value (s) and interpret them. Also learn various types of relationships.

Correlation and Cross-order correlations are computed with the help of MS-Excel Data Analysis command.

Calculating Bivariate and Multivariate Correlation with Analysis Toolpak
05:25
+ Casual Relationship (Regression Analysis)
2 lectures 08:12

Regression analysis is most widely used predictive analysis technique. In this lecture you will learn how to predict or forecast using regression analysis.

Importance and assumptions of Simple Linear Regression
03:12

Learn and compute Regression analysis to quantify the relation, direction, and strength between two variables. Regression measures the relationship between two variables i.e. Independent or Predictor variable, and Dependent or Criterion variable. With MS-Excel Data Analysis command you solve the regression equation with few click.

Along with regression analysis you can also test the hypothesis and strength of the relationship.
Running Simple Linear Regression Analysis in Excel
05:00
+ Multiple Linear Regression Analysis
2 lectures 05:34

Multiple regression analysis is most widely used technique in predictive analytics. Multiple regression equation is an extension of simple regression equation.

Y = b0+b1X1+b2X2+b3X3+…..+e.

You don’t need to worry about the complexity of solving the above equation. Using MS-Excel Data Analysis – Regression command you can solve it within no time.
Relevance and Assumptions of Multiple Regression Analysis
02:05

Multiple regression analysis allows you to fit a more sophisticated model with several variables that explain a dependent variable. You use separate casual factors, analyzing each one’s influence on what you are trying to explain. Learn and practice multiple regression analysis.

Running Multiple Linear Regression Analysis in Excel
03:29
+ Time Series Data Analysis
2 lectures 06:48

Learn how to analyze Time series data to discover a pattern or trend in the historical data and extrapolate the pattern into the future.

In this lecture you will learn how to compute Simple Moving average using MS-Excel built-in function.

Preview 03:45

Exponential smoothing is a simple and pragmatic approach to quantitative forecasting that researchers found useful due to its short-term precision and cost effectiveness. In exponential smoothing the forecast is constructed from an exponentially weighted average of historical data.

Learn how to Calculate exponential smoothing is with Excel Data Analysis command.

Exponential Smoothing using Excel Data Analysis Toolpak
03:03
+ Hypothesis Testing - Two Samples
2 lectures 07:35

Learn how to test the hypothesis of similarity and dissimilarity between two paired samples. You are also introduced to frame null and alternative hypothesis.

Context, assumptions, and interpreting the test results are also explained.

Preview 03:45

The independent samples t-test evaluates the difference between the means of two independent or unrelated groups. The t-test evaluates whether the mean value of the test variable for one group differs significantly from the mean value of the test variable for second group.

Compute independent t-test with the help of MS-Excel Data Analysis tool.
Calculating Independent Sample t-test in Excel Data Analysis Toolpak
03:50