English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 137 lectures (7h 51m) | 2.83 GB

Learn statistics with fun, real-world projects; probability distributions, hypothesis tests, regression analysis & more!

This is a hands-on, project-based course designed to help you learn and apply essential statistics concepts for data analysis & business intelligence. Our goal is to simplify and demystify the world of statistics using familiar tools like Microsoft Excel, and empower everyday people to understand and apply these tools and techniques – even if you have absolutely no background in math or stats!

We’ll start by discussing the role of statistics in business intelligence, the difference between sample and population data, and the importance of using statistical techniques to make smart predictions and data-driven decisions.

Next we’ll explore our data using descriptive statistics and probability distributions, introduce the normal distribution and empirical rule, and learn how to apply the central limit theorem to make inferences about populations of any type.

From there we’ll practice making estimates with confidence intervals, and using hypothesis tests to evaluate assumptions about unknown population parameters. We’ll introduce the basic hypothesis testing framework, then dive into concepts like null and alternative hypotheses, t-scores, p-values, type I vs. type II errors, and more.

Last but not least, we’ll introduce the fundamentals of regression analysis, explore the difference between correlation and causation, and practice using basic linear regression models to make predictions using Excel’s Analysis Toolpak.

Throughout the course, you’ll play the role of a Recruitment Analyst for Maven Business School. Your goal is to use the statistical techniques you’ve learned to explore student data, predict the performance of future classes, and propose changes to help improve graduate outcomes.

You’ll also practice applying your skills to 5 real-world BONUS PROJECTS, and use statistics to explore data from restaurants, medical centers, pharmaceutical companys, safety teams, airlines, and more.

What you’ll learn

- Learn powerful statistics tools and techniques for data analysis & business intelligence
- Understand how to apply foundational statistics concepts like the central limit theorem and empirical rule
- Explore data with descriptive statistics, including probability distributions and measures of variability & central tendency
- Model data and make estimates using probability distributions and confidence intervals
- Make data-driven decisions and draw conclusions with hypothesis testing
- Use linear regression models to explore variable relationships and make predictions

## Table of Contents

**Getting Started**

Course Structure & Outline

READ ME Important Notes for New Students

DOWNLOAD Course Resources

Setting Expectations

The Course Project

Helpful Resources

**Why Statistics**

Section Intro

Why Statistics

Populations & Samples

The Statistics Workflow

**Understanding Data with Descriptive Statistics**

Section Intro

Descriptive Statistics Basics

Types of Variables

Types of Descriptive Statistics

Categorical Frequency Distributions

Numerical Frequency Distributions

Histograms

ASSIGNMENT Frequency Distributions

KNOWLEDGE CHECK Frequency Distributions

SOLUTION Frequency Distributions

Mean, Median, and Mode

Left & Right Skew

ASSIGNMENT Measures of Central Tendency

KNOWLEDGE CHECK Measures of Central Tendency

SOLUTION Measures of Central Tendency

Min, Max & Range

Interquartile Range

Box & Whisker Plots

Variance & Standard Deviation

PRO TIP Coefficient of Variation

ASSIGNMENT Measures of Variability

KNOWLEDGE CHECK Measures of Variability

SOLUTION Measures of Variability

Key Takeaways

**PROJECT #1 Maven Pizza Parlor**

PROJECT BRIEF Maven Pizza Parlor

SOLUTION Maven Pizza Parlor

**Modeling Data with Probability Distributions**

Section Intro

Probability Distribution Basics

Types of Probability Distributions

The Normal Distribution

Z Scores

The Empirical Rule

ASSIGNMENT Normal Distributions

KNOWLEDGE CHECK Normal Distributions

SOLUTION Normal Distributions

Excel’s Normal Distribution Functions

Calculating Probabilities with the Normal Distribution

The NORM.DIST Function

The NORM.S.DIST Function

ASSIGNMENT Calculating Probabilities

KNOWLEDGE CHECK Calculating Probabilities

SOLUTION Calculating Probabilities

PRO TIP Plotting the Normal Curve

Estimating X or Z Values with the Normal Distribution

The NORM.INV Function

The NORM.S.INV Function

ASSIGNMENT Estimating Values

KNOWLEDGE CHECK Estimating Values

SOLUTION Estimating Values

Key Takeaways

**PROJECT #2 Maven Medical Center**

PROJECT BRIEF Maven Medical Center

SOLUTION Maven Medical Center

**The Central Limit Theorem**

Section Intro

The Central Limit Theorem

DEMO Proving the Central Limit Theorem

Standard Error

Implications of the Central Limit Theorem

Applications of the Central Limit Theorem

Key Takeaways

**Making Estimates with Confidence Intervals**

Section Intro

Confidence Intervals Basics

Confidence Level

Margin of Error

DEMO Calculating Confidence Intervals

The CONFIDENCE.NORM Function

ASSIGNMENT Confidence Intervals

KNOWLEDGE CHECK Confidence Intervals

SOLUTION Confidence Intervals

Types of Confidence Intervals

T Distribution

Excel’s T Distribution Functions

Confidence Intervals with the T Distribution

ASSIGNMENT Confidence Intervals (T Distribution)

KNOWLEDGE CHECK Confidence Intervals (T Distribution)

SOLUTION Confidence Intervals (T Distribution)

Confidence Intervals for Proportions

ASSIGNMENT Confidence Intervals (Proportions)

KNOWLEDGE CHECK Confidence Intervals (Proportions)

SOLUTION Confidence Intervals (Proportions)

Confidence Intervals for Two Populations

Dependent Samples

ASSIGNMENT Confidence Intervals (Dependent Samples)

KNOWLEDGE CHECK Confidence Intervals (Dependent Samples)

SOLUTION Confidence Intervals (Dependent Samples)

Independent Samples

ASSIGNMENT Confidence Intervals (Independent Samples)

KNOWLEDGE CHECK Confidence Intervals (Independent Samples)

SOLUTION Confidence Intervals (Independent Samples)

PRO TIP Difference Between Proportions

Key Takeaways

**PROJECT #3 Maven Pharma**

PROJECT BRIEF Maven Pharma

SOLUTION Maven Pharma

**Drawing Conclusions with Hypothesis Tests**

Section Intro

Hypothesis Testing Basics

Null & Alternative Hypothesis

Significance Level

Test Statistic (T-score)

P-Value

Drawing Conclusions from Hypothesis Tests

ASSIGNMENT Hypothesis Tests

KNOWLEDGE CHECK Hypothesis Tests

SOLUTION Hypothesis Tests

Relationship between Confidence Intervals & Hypothesis Tests

Type I & Type II Errors

One Tail & Two Tail Hypothesis Tests

DEMO One Tail Hypothesis Test

Hypothesis Tests for Proportions

ASSIGNMENT Hypothesis Tests (Proportions)

KNOWLEDGE CHECK Hypothesis Tests (Proportions)

SOLUTION Hypothesis Tests (Proportions)

Hypothesis Tests for Dependent Samples

ASSIGNMENT Hypothesis Tests (Dependent Samples)

KNOWLEDGE CHECK Hypothesis Tests (Dependent Samples)

SOLUTION Hypothesis Tests (Dependent Samples)

Hypothesis Tests for Independent Samples

ASSIGNMENT Hypothesis Tests (Independent Samples)

KNOWLEDGE CHECK Hypothesis Tests (Independent Samples)

SOLUTION Hypothesis Tests (Independent Samples)

Key Takeaways

**PROJECT #4 Maven Safety Council**

PROJECT BRIEF Maven Safety Council

SOLUTION Maven Safety Council

**Making Predictions with Regression Analysis**

Section Intro

Linear Relationships

Correlation (R)

ASSIGNMENT Linear Relationships

KNOWLEDGE CHECK Linear Relationships

SOLUTION Linear Relationships

Linear Regression & Least Squared Error

Excel’s Linear Regression Functions

ASSIGNMENT Simple Linear Regression

KNOWLEDGE CHECK Simple Linear Regression

SOLUTION Simple Linear Regression

Determination (R-Squared)

Standard Error

Homoskedasticity & Heteroskedasticity

Hypothesis Testing with Regression

ASSIGNMENT Model Evaluation

KNOWLEDGE CHECK Model Evaluation

SOLUTION Model Evaluation

Excel’s Regression Tool (Analysis ToolPak)

PRO TIP Multiple Linear Regression

Key Takeaways

**PROJECT #5 Maven Airlines**

PROJECT BRIEF Maven Airlines

SOLUTION Maven Airlines

**BONUS LESSON**

BONUS LESSON

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