Mô tả

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.


COURSE OUTLINE:


  • Why Statistics?

    • Discuss the role of statistics in the context of business intelligence and decision-making, and introduce the statistics workflow


  • Understanding Data with Descriptive Statistics

    • Understand data using descriptive statistics, including frequency distributions and measures of central tendency & variability

    • PROJECT #1: Maven Pizza Parlor


  • Modeling Data with Probability Distributions

    • Model data with probability distributions, and use the normal distribution to calculate probabilities and make value estimates

    • PROJECT #2: Maven Medical Center


  • The Central Limit Theorem

    • Introduce the Central Limit Theorem, which leverages the normal distribution to make inferences on populations with any distribution


  • Making Estimates with Confidence Intervals

    • Make estimates with confidence intervals, which use sample statistics to define a range where an unknown population parameter likely lies

    • PROJECT #3: Maven Pharma


  • Drawing Conclusions with Hypothesis Tests

    • Draw conclusions with hypothesis tests, which let you evaluate assumptions about population parameters using sample statistics

    • PROJECT #4: Maven Safety Council


  • Making Predictions with Regression Analysis

    • Make predictions with regression analysis, and estimate the values of a dependent variable via its relationship with independent variables

    • PROJECT #5: Maven Airlines


Join today and get immediate, lifetime access to the following:


  • 7.5 hours of high-quality video

  • Statistics for Data Analysis PDF ebook (150+ pages)

  • Downloadable Excel project files & solutions

  • Expert support and Q&A forum

  • 30-day Udemy satisfaction guarantee


If you're an analyst, data scientist, business intelligence professional, or anyone looking to use statistics to make smart, data-driven decisions, this course is for you!


Happy learning!

-Enrique Ruiz (Lead Statistics & Excel Instructor, Maven Analytics)

Bạn sẽ học được gì

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

Yêu cầu

  • No math or stats background is required – we'll start with the absolute basics!
  • We'll use Microsoft Excel (Office 365) for course projects and demos

Nội dung khoá học

14 sections

Getting Started

6 lectures
Course Structure & Outline
01:59
READ ME: Important Notes for New Students
02:13
DOWNLOAD: Course Resources
00:11
Setting Expectations
01:57
The Course Project
02:48
Helpful Resources
02:30

Why Statistics?

5 lectures
Section Intro
01:04
Why Statistics?
01:42
Populations & Samples
02:43
The Statistics Workflow
02:29
QUIZ: Why Statistics?
2 questions

Understanding Data with Descriptive Statistics

25 lectures
Section Intro
01:14
Descriptive Statistics Basics
01:26
Types of Variables
02:07
Types of Descriptive Statistics
02:41
Categorical Frequency Distributions
08:13
Numerical Frequency Distributions
06:47
Histograms
06:17
ASSIGNMENT: Frequency Distributions
01:52
KNOWLEDGE CHECK: Frequency Distributions
1 question
SOLUTION: Frequency Distributions
03:43
Mean, Median, and Mode
13:36
Left & Right Skew
03:11
ASSIGNMENT: Measures of Central Tendency
00:58
KNOWLEDGE CHECK: Measures of Central Tendency
1 question
SOLUTION: Measures of Central Tendency
03:09
Min, Max & Range
02:20
Interquartile Range
06:25
Box & Whisker Plots
04:53
Variance & Standard Deviation
07:05
PRO TIP: Coefficient of Variation
03:28
ASSIGNMENT: Measures of Variability
01:12
KNOWLEDGE CHECK: Measures of Variability
1 question
SOLUTION: Measures of Variability
08:16
Key Takeaways
01:15
QUIZ: Descriptive Statistics
3 questions

PROJECT #1: Maven Pizza Parlor

2 lectures
PROJECT BRIEF: Maven Pizza Parlor
01:56
SOLUTION: Maven Pizza Parlor
08:12

Modeling Data with Probability Distributions

25 lectures
Section Intro
01:14
Probability Distribution Basics
02:58
Types of Probability Distributions
02:05
The Normal Distribution
05:16
Z Scores
04:31
The Empirical Rule
04:08
ASSIGNMENT: Normal Distributions
01:14
KNOWLEDGE CHECK: Normal Distributions
1 question
SOLUTION: Normal Distributions
04:20
Excel's Normal Distribution Functions
01:17
Calculating Probabilities with the Normal Distribution
02:24
The NORM.DIST Function
05:14
The NORM.S.DIST Function
03:42
ASSIGNMENT: Calculating Probabilities
00:50
KNOWLEDGE CHECK: Calculating Probabilities
1 question
SOLUTION: Calculating Probabilities
02:20
PRO TIP: Plotting the Normal Curve
06:57
Estimating X or Z Values with the Normal Distribution
00:52
The NORM.INV Function
02:33
The NORM.S.INV Function
02:11
ASSIGNMENT: Estimating Values
00:52
KNOWLEDGE CHECK: Estimating Values
1 question
SOLUTION: Estimating Values
01:26
Key Takeaways
01:35
QUIZ: Probability Distributions
3 questions

PROJECT #2: Maven Medical Center

2 lectures
PROJECT BRIEF: Maven Medical Center
01:18
SOLUTION: Maven Medical Center
10:02

The Central Limit Theorem

8 lectures
Section Intro
00:52
The Central Limit Theorem
03:14
DEMO: Proving the Central Limit Theorem
03:18
Standard Error
02:40
Implications of the Central Limit Theorem
02:22
Applications of the Central Limit Theorem
01:20
Key Takeaways
01:13
QUIZ: The Central Limit Theorem
3 questions

Making Estimates with Confidence Intervals

32 lectures
Section Intro
01:12
Confidence Intervals Basics
03:36
Confidence Level
01:53
Margin of Error
04:47
DEMO: Calculating Confidence Intervals
03:06
The CONFIDENCE.NORM Function
01:52
ASSIGNMENT: Confidence Intervals
01:11
KNOWLEDGE CHECK: Confidence Intervals
1 question
SOLUTION: Confidence Intervals
02:57
Types of Confidence Intervals
01:34
T Distribution
01:57
Excel's T Distribution Functions
01:45
Confidence Intervals with the T Distribution
05:20
ASSIGNMENT: Confidence Intervals (T Distribution)
00:45
KNOWLEDGE CHECK: Confidence Intervals (T Distribution)
1 question
SOLUTION: Confidence Intervals (T Distribution)
03:29
Confidence Intervals for Proportions
07:21
ASSIGNMENT: Confidence Intervals (Proportions)
00:51
KNOWLEDGE CHECK: Confidence Intervals (Proportions)
1 question
SOLUTION: Confidence Intervals (Proportions)
02:55
Confidence Intervals for Two Populations
02:31
Dependent Samples
05:19
ASSIGNMENT: Confidence Intervals (Dependent Samples)
00:50
KNOWLEDGE CHECK: Confidence Intervals (Dependent Samples)
1 question
SOLUTION: Confidence Intervals (Dependent Samples)
02:38
Independent Samples
08:48
ASSIGNMENT: Confidence Intervals (Independent Samples)
00:41
KNOWLEDGE CHECK: Confidence Intervals (Independent Samples)
1 question
SOLUTION: Confidence Intervals (Independent Samples)
05:56
PRO TIP: Difference Between Proportions
06:54
Key Takeaways
01:29
QUIZ: Confidence Intervals
4 questions

PROJECT #3: Maven Pharma

2 lectures
PROJECT BRIEF: Maven Pharma
01:20
SOLUTION: Maven Pharma
05:56

Drawing Conclusions with Hypothesis Tests

28 lectures
Section Intro
01:15
Hypothesis Testing Basics
02:58
Null & Alternative Hypothesis
05:06
Significance Level
03:08
Test Statistic (T-score)
03:50
P-Value
05:08
Drawing Conclusions from Hypothesis Tests
04:46
ASSIGNMENT: Hypothesis Tests
01:18
KNOWLEDGE CHECK: Hypothesis Tests
1 question
SOLUTION: Hypothesis Tests
03:49
Relationship between Confidence Intervals & Hypothesis Tests
02:34
Type I & Type II Errors
03:47
One Tail & Two Tail Hypothesis Tests
02:56
DEMO: One Tail Hypothesis Test
04:40
Hypothesis Tests for Proportions
00:47
ASSIGNMENT: Hypothesis Tests (Proportions)
01:21
KNOWLEDGE CHECK: Hypothesis Tests (Proportions)
1 question
SOLUTION: Hypothesis Tests (Proportions)
05:26
Hypothesis Tests for Dependent Samples
01:26
ASSIGNMENT: Hypothesis Tests (Dependent Samples)
01:21
KNOWLEDGE CHECK: Hypothesis Tests (Dependent Samples)
1 question
SOLUTION: Hypothesis Tests (Dependent Samples)
05:40
Hypothesis Tests for Independent Samples
01:19
ASSIGNMENT: Hypothesis Tests (Independent Samples)
01:09
KNOWLEDGE CHECK: Hypothesis Tests (Independent Samples)
1 question
SOLUTION: Hypothesis Tests (Independent Samples)
04:39
Key Takeaways
02:31
QUIZ: Hypothesis Tests
4 questions

PROJECT #4: Maven Safety Council

2 lectures
PROJECT BRIEF: Maven Safety Council
01:08
SOLUTION: Maven Safety Council
13:10

Making Predictions with Regression Analysis

22 lectures
Section Intro
01:07
Linear Relationships
04:41
Correlation (R)
05:16
ASSIGNMENT: Linear Relationships
00:48
KNOWLEDGE CHECK: Linear Relationships
1 question
SOLUTION: Linear Relationships
02:18
Linear Regression & Least Squared Error
09:45
Excel's Linear Regression Functions
04:15
ASSIGNMENT: Simple Linear Regression
00:48
KNOWLEDGE CHECK: Simple Linear Regression
1 question
SOLUTION: Simple Linear Regression
03:56
Determination (R-Squared)
08:42
Standard Error
03:43
Homoskedasticity & Heteroskedasticity
02:24
Hypothesis Testing with Regression
06:49
ASSIGNMENT: Model Evaluation
00:38
KNOWLEDGE CHECK: Model Evaluation
1 question
SOLUTION: Model Evaluation
07:20
Excel's Regression Tool (Analysis ToolPak)
05:14
PRO TIP: Multiple Linear Regression
08:14
Key Takeaways
02:22
QUIZ: Regression Analysis
4 questions

PROJECT #5: Maven Airlines

2 lectures
PROJECT BRIEF: Maven Airlines
01:28
SOLUTION: Maven Airlines
12:04

BONUS LESSON

1 lectures
BONUS LESSON
01:45

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