Statistics for Business Analytics using MS Excel

Statistics for Business Analytics using MS Excel, available at $79.99, has an average rating of 4.67, with 97 lectures, 9 quizzes, based on 604 reviews, and has 44446 subscribers.

You will learn about Learn the concepts of Probability and statistics required for making business decisions Use concept of Statistical inference to make statistics-based judgement of business scenarios Knowledge of all the essential Excel formulas required for Business Analysis Implement predictive ML models such as simple and multiple linear regression to predict outcomes to real world problems Knowledge of data-related operations such as calculating, transforming, matching, filtering, sorting, and aggregating data Learnr important probability distributions such as Normal distribution, Poisson distribution, Exponential distribution, Binomial distribution etc Solve business case-studies with Excel's data analytics tools such as solver, goal seek, scenario manager, etc Learn about important data processing topics like outlier treatment, missing value imputation, variable transformation, and correlation. This course is ideal for individuals who are Anyone curious to master Excel for Business Analysis in a short span of time or Business Analysts/ Managers who want to expand on the current set of skills It is particularly useful for Anyone curious to master Excel for Business Analysis in a short span of time or Business Analysts/ Managers who want to expand on the current set of skills.

Enroll now: Statistics for Business Analytics using MS Excel

Summary

Title: Statistics for Business Analytics using MS Excel

Price: $79.99

Average Rating: 4.67

Number of Lectures: 97

Number of Quizzes: 9

Number of Published Lectures: 89

Number of Published Quizzes: 9

Number of Curriculum Items: 106

Number of Published Curriculum Objects: 98

Original Price: $24.99

Quality Status: approved

Status: Live

What You Will Learn

Learn the concepts of Probability and statistics required for making business decisions
Use concept of Statistical inference to make statistics-based judgement of business scenarios
Knowledge of all the essential Excel formulas required for Business Analysis
Implement predictive ML models such as simple and multiple linear regression to predict outcomes to real world problems
Knowledge of data-related operations such as calculating, transforming, matching, filtering, sorting, and aggregating data
Learnr important probability distributions such as Normal distribution, Poisson distribution, Exponential distribution, Binomial distribution etc
Solve business case-studies with Excel's data analytics tools such as solver, goal seek, scenario manager, etc
Learn about important data processing topics like outlier treatment, missing value imputation, variable transformation, and correlation.

Who Should Attend

Anyone curious to master Excel for Business Analysis in a short span of time
Business Analysts/ Managers who want to expand on the current set of skills

Target Audiences

Anyone curious to master Excel for Business Analysis in a short span of time
Business Analysts/ Managers who want to expand on the current set of skills

You’re looking for a complete course on understanding Statistics for Business Analytics, right?

You’ve found theright Statistics for Business Analytics using MS Excelcourse! This course will teach you data-driven decision-making and the use of analytical and statistical methods in business settings.

After completing this course you will be able to:

Understand how to formulate a business problem as an analytics problem
Summarize business data into tables and charts to communicate information effectively
Make predictive machine learning model to predict business outcomes
Use statistical concepts to reach business decisions
Interpret the results of statistical models for formulating strategy

How this course will help you?

A Verifiable Certificate of Completion is presented to all students who undertake this course on Statistics for Business Analytics in Excel.

If you are a business manager, or business analyst or an executive, or a student who wants to learn Statistics concepts and apply analytics techniques to real-world problems of the Business business function, this course will give you a solid base for Statistics and Analytics by teaching you the most popular Business analysis models and how to implement it them in MS Excel.

Why should you choose this course?

We believe in teaching by example. This course is no exception. Every Section’s primary focus is to teach you the concepts through how-to examples. Each section has the following components:

Theoretical concepts and use cases of different Statistical models required for evaluating business models
Step-by-step instructions on implementing business models in MS Excel
Downloadable Excel files containing data and solutions used in MS Excel
Class notes and assignments to revise and practice the concepts in MS Excel

The practical classes where we create the model for each of these strategies are something that differentiates this course from any other course available online.

What makes us qualified to teach you?

The course is taught by Abhishek(MBA – FMS Delhi, B. Tech – IIT Roorkee) and Pukhraj (MBA – IIM Ahmedabad, B. Tech – IIT Roorkee). As managers in the Global Analytics Consulting firm, we have helped businesses solve their business problems using Analytics and we have used our experience to include the practical aspects of analytics in this course. We have in-hand experience in Business Analysis and MS Excel.

We are also the creators of some of the most popular online courses – with over 600,000 enrollments and thousands of 5-star reviews like these ones:

This is very good, i love the fact the all explanation given can be understood by a layman – Joshua

Thank you Author for this wonderful course. You are the best and this course is worth any price. – Daisy

Our Promise

Teaching our students is our job and we are committed to it. If you have any questions about the course content, practice sheet, or anything related to any topic, you can always post a question in the course or send us a direct message.

Download Practice files, take Quizzes, and complete Assignments

With each lecture, there are class notes attached for you to follow along. You can also take quizzes to check your understanding of concepts like Business Statistics and Analytics in MS Excel. Each section contains a practice assignment for you to practically implement your learning on Business Analysis in MS Excel.

What is covered in this course?

The analysis of data is not the main crux of analytics. It is the interpretation that helps provide insights after the application of analytical techniques that makes analytics such an important discipline. We have used the most popular analytics software tool which is MS Excel. This will aid the students who have no prior coding background to learn and implement Statistics and Analytics concepts to actually solve real-world problems of Business Analysis.

Let me give you a brief overview of the course

Part 1 – Excel for data analytics

In the first section, i.e. Excel for data analytics, we will learn how to use excel for data-related operations such as calculating, transforming, matching, filtering, sorting, and aggregating data.

We will also cover how to use different types of charts to visualize the data and discover hidden data patterns.

Part 2 – Statistics foundations for business analysts

Then, in the second section, i.e. Statistics foundations for business analysts, we will start learning about the core concepts of Business Analytics i.e. probability and probability distribution. We will look at important probability distributions used in a business setting such as Normal distribution, Poisson distribution, Exponential distribution, Binomial distribution etc

These concepts form the foundation of data analytics, machine learning, and deep learning.

Part 3 – Statistical Decision making

Once we have covered the basics of probability, in the 3rd section, i.e. Statistical Decision making we will discuss some advanced concepts related to sample testing i.e. hypothesis testing.

These are the concepts that differentiate a beginner from a pro!

Part 4 – Optimizing Business Models

In the fourth section, i.e. Optimizing Business Models we will learn how to solve common business problems with the help of excel’s data analytics tools such as solver, goal seek, scenario manager, etc.

Part 5 – Preprocessing Data for ML models

In this section, you will learn what actions you need to take step by step to get the data and then prepare it for analysis, these steps are very important. We start with understanding the importance of business knowledge then we will see how to do data exploration. We learn how to do uni-variate analysis and bivariate analysis then we cover topics like outlier treatment, missing value imputation, variable transformation, and correlation.

Part 6 – Linear regression model for predicting metrics

This section starts with simple linear regression and then covers multiple linear regression.

We have covered the basic theory behind each concept without getting too mathematical about it so that you understand where the concept is coming from and how it is important. But even if you don’t understand it, it will be okay as long as you learn how to run and interpret the result as taught in the practical lectures.

I am pretty confident that the course will give you the necessary knowledge on Business Statistics and Business Analysis using MS Excel, and the skillsets of a Business Analyst to immediately see practical benefits in your workplace.

Go ahead and click the enroll button, and I’ll see you in lesson 1 of this Statistics for Business Analytics course!

Cheers

Start-Tech Academy

Course Curriculum

Chapter 1: Introduction

Lecture 1: Welcome to the course

Lecture 2: Course resources

Chapter 2: Excel for data analytics

Lecture 1: Milestone

Lecture 2: Basic Formula Operations

Lecture 3: Important Excel Functions – Sum, Average, Concatenate, Trim

Lecture 4: Important Excel Functions- Vlookup, If, Count If, Sum if

Lecture 5: Sorting, Filtering and Data Validation

Lecture 6: Text-to-columns and remove duplicates

Lecture 7: Advanced Filter option

Lecture 8: Pivot Tables

Chapter 3: Introduction to probability

Lecture 1: Probability module – Introduction

Lecture 2: Basics of probability

Lecture 3: Calculating Probability in Excel – Part 1

Lecture 4: Calculating Probability in Excel – Part 2

Lecture 5: Important laws of probability

Lecture 6: Implementing laws of probability in Excel

Chapter 4: Probability distribution concepts

Lecture 1: Concepts of probability distribution

Lecture 2: Measures of probability distribution in Excel

Lecture 3: Discreet vs continuous probability distribution

Lecture 4: Using probablity distribution

Chapter 5: Types of discreet probability distribution

Lecture 1: Discreet Uniform probability distribution

Lecture 2: Discreet binomial probability distribution

Lecture 3: Binomial – Practical session

Lecture 4: Discreet Poisson probability distribution

Lecture 5: Poisson – Practical session

Chapter 6: Types of continuous probablity distribution

Lecture 1: Continuous probability distribution – Introduction

Lecture 2: Uniform continuous probability distribution

Lecture 3: Normal distribution

Lecture 4: Normal distribution – Practical

Lecture 5: Exponential distribution

Lecture 6: Exponential distribution – Practical

Chapter 7: Statistical Inference

Lecture 1: Module Introduction

Lecture 2: Sampling and Types of Sampling

Lecture 3: Point Estimation

Lecture 4: Excel – How to do random sampling

Lecture 5: Excel – Point Estimation

Lecture 6: Sampling Distributions

Lecture 7: Excel – Demo of key results

Lecture 8: Interval Estimation

Lecture 9: Excel – Interval Estimation for mean

Lecture 10: Excel – Interval Estimation for proportion

Lecture 11: How to determine sample size?

Lecture 12: Sample case study

Chapter 8: Hypothesis Testing

Lecture 1: What is Hypothesis testing?

Lecture 2: Type 1 and Type 2 errors

Lecture 3: The process of hypothesis testing Part-1

Lecture 4: The process of hypothesis testing Part-2

Lecture 5: How to find the p-value?

Lecture 6: Excel – Statistical Formulas for T distribution

Lecture 7: Excel – Statistical Formulas for Z distribution

Lecture 8: Vaccination case study

Lecture 9: Ecommerce site case study

Chapter 9: Optimizing business models

Lecture 1: Module introduction

Lecture 2: Goal-seek and Scenario Manager in Excel

Lecture 3: Solver in Excel

Lecture 4: Different Solving methods of Excel Solver

Lecture 5: Solving a Transportation problem

Lecture 6: Price Skimming

Lecture 7: Excel – Price Skimming model

Lecture 8: Concept of Customer lifetime Value

Lecture 9: Excel – Calculating customer lifetime value

Chapter 10: Predictive analytics – Preparing the Data

Lecture 1: Module introduction

Lecture 2: Gathering Business Knowledge

Lecture 3: Data Exploration

Lecture 4: The Data and the Data Dictionary

Lecture 5: Univariate analysis and EDD

Lecture 6: Discriptive Data Analytics in Excel

Lecture 7: Outlier Treatment

Lecture 8: Identifying and Treating Outliers in Excel

Lecture 9: Missing Value Imputation

Lecture 10: Identifying and Treating missing values in Excel

Lecture 11: Variable Transformation in Excel

Lecture 12: Dummy variable creation: Handling qualitative data

Lecture 13: Dummy Variable Creation in Excel

Lecture 14: Correlation Analysis

Lecture 15: Creating Correlation Matrix in Excel

Chapter 11: Building a Linear Regression Model

Lecture 1: The Problem Statement

Lecture 2: Basic Equations and Ordinary Least Squares (OLS) method

Lecture 3: Assessing accuracy of predicted coefficients

Lecture 4: Assessing Model Accuracy RSE and R squared

Instructors

Start-Tech Academy
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Rating Distribution

1 stars: 8 votes
2 stars: 8 votes
3 stars: 53 votes
4 stars: 212 votes
5 stars: 323 votes

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