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Business Statistics Made Easy
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Business Statistics Made Easy
Last updated 6/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 5.15 GB | Duration: 5h 58m

An easy-to-understand course covering the fundamentals of statistics and their applications to business



What you'll learn
The Representation of Data in order to paint a clear picture of what a dataset is telling us (stem-and-leaf diagrams, box-and-whisker plots, histograms and cumulative frequency graphs);
Measures of Location in order to estimate the most likely outcome of an experiment (mean, median, mode);
Measures of Spread in order to understand how volatile or variable a dataset is (range, quartiles, interquartile range, standard deviation);
Sigma Notation and summation
Counting Methods: Learn efficient methods for counting the number of arrangements of a set number of objects using permutation and combination functions;
Probability: Learn how to determine the likelihood of an event occurring (Venn diagrams, unions, intersections, conditional probabilities, mutually exclusive outcomes, and independent trials);
Solving probability problems involving permutations, combinations, and tree diagrams;
The Binomial Distribution: theory and application;
Discrete Probability Distributions: theory and applications, as well as understanding of expectation, variance, and standard deviation;
The Normal Distribution: theory and application;
Using the Normal Distribution to Approximate the Binomial Distribution
Hypothesis Testing
Linear Regression Analysis

Requirements
Basic algebra and mathematical techniques

Description
Are you battling to understand statistics? Are you confused by intimidating formulae and jargon? Do you want to know what metrics analyze in your business or in your job, that will allow you to produce insightful reports in order to make better decisions?Well if so, this course is perfect for you. I designed this statistics course combining years of teaching, investment banking, and entrepreneurial experience. The result is an easy-to-understand and real-world applicable course with detailed explanations and worked examples, which will not only help you to understand statistical concepts, but will also help you to see how statistics is applied in real-world business scenarios. This "learn-by-doing" approach, will empower you to master the concepts being taught quickly, via direct application. The video format of the course accelerates learning, and provides an engaging delivery mechanism for the educational content. In addition to this, the practice questions at the end of each learning section, provide students with a large body of practice material to reinforce the learning of the concepts being taught. In this preview course a conceptual overview of statistics is provided, covering representation of data, measures of spread, and measures of location. In the full course a comprehensive list of concepts would be expanded upon to include producing powerful reports, hypothesis testing and regression.

Overview

Section 1: Data Representation

Lecture 1 Introduction

Lecture 2 Chapter 1 Part 2 - Stem-and-Leaf Diagram

Lecture 3 Chapter 1 Part 3 - Bar charts and histograms

Lecture 4 Chapter 1 Part 4 - Cumulative Frequency Curves

Section 2: Measures of Location

Lecture 5 Chapter 2 Part 1 - Measures of Location

Lecture 6 Chapter 2 Part 2 - The Mean and Sigma Notation

Lecture 7 Chapter 2 Part 3 - The Mode

Section 3: Measures of Spread

Lecture 8 Chapter 3 Part 1 - The Range and 5 No. Summary

Lecture 9 Chapter 3 Part 2 - Sigma Notation Revisited

Lecture 10 Chapter 3 Part 3 - Variance and Std. Deviation

Lecture 11 Chapter 3 Part 4 - Variance and Std. Deviation For Frequency Tables

Lecture 12 Part 1 Summary

Section 4: Probability

Lecture 13 Chapter 4 - Part 1 Probability General Terms and Concepts

Lecture 14 Chapter 4 - Part 2 Mutually Exclusive Outcomes

Lecture 15 Unions and Intersections

Lecture 16 Conditional Probability

Lecture 17 Tree Diagrams

Lecture 18 Independence

Section 5: Permutations and Combinations

Lecture 19 Permutations

Lecture 20 Permutations with Repeated Items

Lecture 21 Combinations

Lecture 22 Combinations with Repeated Items

Lecture 23 Complex Problems

Section 6: Discrete Probability Distributions

Lecture 24 Discrete Probability Distributions

Section 7: The Binomial Distribution

Lecture 25 The Binomial Distribution

Lecture 26 The Parameters of the Binomial Distribution

Lecture 27 The Geometric Distribution

Lecture 28 The Mode of the Geometric Distribution

Section 8: Expectation and Variance of a Random Variable

Lecture 29 Expectation and Variance of a Random Variable

Lecture 30 Expectation and Variance of a Binomial Random Variable

Lecture 31 Expectation of a Geometrically Distributed Random Variable

Section 9: The Normal Distribution

Lecture 32 The Normal Distribution Introduction

Lecture 33 The Normal Distribution Worked Examples

Lecture 34 Standardizing The Normal Distribution

Lecture 35 The Normal Approximation to the Binomial Distribution

Lecture 36 Normal Approximation to Binomial Worked Examples

Business analysts, data analysts and any professional in a research or marketing role, who uses statistics on a daily basis


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