Microsoft Excel Statistics & Data Analysis - Zero to Analyst

voska89 · 2026-06-29T18:54:47+0300

Microsoft Excel Statistics & Data Analysis - Zero to Analyst
Published 6/2026
Created by Andreas Exadaktylos • Msc in Computer Science & Electronic Engineering
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 81 Lectures ( 8h 11m ) | Size: 7 GB
Statistics in Excel from scratch. Master t-tests, ANOVA, chi-square and regression - no math background required

What you'll learn

Master Excel Statistics from absolute zero - no math degree, no prior stats, no Python required

Describe any dataset with confidence: mean, median, standard deviation, z-scores, IQR, boxplots

Use the binomial and Poisson distributions for real business questions (defect rates, calls per hour)

Apply the Central Limit Theorem - the single most useful idea in statistics

Build 95% confidence intervals for means and proportions, and explain what they actually mean

Run the full toolkit of hypothesis tests: t-tests, z-tests, paired t-tests, F-tests, ANOVA, chi-square

Build simple and multiple regression models in Excel, with diagnostics and predictions

Use the Data Analysis ToolPak like a working analyst - every test, every output, every interpretation

Complete 10 hands-on exercises modeled on real first-week analyst tasks at a fictional coffee chain

Translate every statistical finding into business language an executive can act on
Requirements

Excel 2016 or later - including Excel for Microsoft 365, Excel Online, and Mac versions

Basic Excel comfort: opening files, entering formulas, navigating worksheets (nothing advanced)

No prior statistics knowledge required - we cover everything from scratch

About 30-40 minutes a day for two to three weeks (or work at your own pace)

A willingness to actually open Excel and follow along - this is a hands-on course
Description
Picture this. You open Excel, a dataset is staring back at you - sales numbers, survey results, website traffic, exam scores - and you know there's something important in it. But you're not sure how to prove it. That's why I created thisExcel Statistics course.
Welcome to theMicrosoft Excel Statistics & Data Analysis Course - From Zero to Analyst. This is a practical, hands-on, Excel-first course designed to take you from "I have a spreadsheet I don't understand" to "I can explain a decision with confidence using data." Everything we cover, we cover in Excel Statistics workflows - no Python, no R, no expensive software.
What makes this course different
Most statistics courses on Udemy use disconnected worked examples - one dataset for the hypothesis testing section, another for ANOVA, another for regression. Students learn each technique in isolation and never see how they fit together.
This course is different. The entire curriculum runs on a continuous storyline. You're the new junior analyst at BrightRoast Coffee - a fictional 200-store chain - and every section adds a new skill to your toolkit. Maria, the Head of Analytics, gives you the questions. You do the analysis in Excel. Across the course you'll complete10 hands-on exercises that mirror exactly what an entry-level analyst does in a real first week on the job. Each exercise ends with a self-check that turns green when you've nailed it.
The curriculum at a glance

Foundations - Statistics in plain English. Samples vs. populations. Descriptive vs. inferential. Excel essentials including absolute references, Tables, and Flash Fill.

Descriptive Statistics - Mean, median, mode. Range, standard deviation, IQR. Z-scores and the Empirical Rule. Histograms, boxplots, and outlier detection. The Data Analysis ToolPak's descriptive output, explained line by line.

Probability & Distributions - Counting outcomes with PERMUT and COMBIN. The binomial distribution for yes/no situations (BINOM.DIST). The Poisson distribution for events arriving at a rate (POISSON.DIST). The normal distribution and z-tables.

The Central Limit Theorem - Standard error of the mean. Standard error of a proportion. Why n ≥ 30 makes the CLT work. The t-distribution vs. the z-distribution.

Confidence Intervals - For proportions. For means. How sample size changes the interval. The difference between 90%, 95%, and 99% confidence.

Hypothesis Testing - The 5-step framework. One-tailed vs. two-tailed tests. Type 1 and Type 2 errors. P-values explained honestly. One-sample tests for means and proportions.

Two-Sample Tests - Independent vs. paired samples. Two-proportion z-tests. Welch's t-test. Paired t-tests for before/after studies. F-tests for comparing variances.

ANOVA & Chi-Square - Comparing 3+ groups with one-way ANOVA. Post-hoc tests. Effect size with eta-squared. The chi-square test for categorical data (goodness-of-fit and independence). Cramer's V as effect size.

Regression Analysis - Correlation vs. regression. Simple linear regression: SLOPE, INTERCEPT, RSQ, FORECAST.LINEAR. Multiple regression with the Data Analysis ToolPak. R-squared and adjusted R-squared. Regression diagnostics (the LINE assumptions: Linearity, Independence, Normality, Equal variance). Making predictions with prediction intervals.
Section checkpoints
At the end of every section, a one-slide checkpoint shows exactly what you can now do. Six items, six green checkmarks. Your progress is visible - section by section, skill by skill.
What you get
• 80+ short, focused video lectures
• The exact Excel workbooks used in every lecture, downloadable for follow-along
• 10 hands-on exercises with paired challenge/solution worksheets
• Practice quizzes after each section
• Direct Q&A support - post a question and I'll personally walk you through the step that's confusing
• Lifetime access and free updates
If you're ready to turn spreadsheets into insight and masterExcel Statistics for real-world data analysis, click the Enroll button and let's get started.
Who this course is for

Excel users in marketing, operations, sales, HR, or finance who want to make data-driven decisions

Anyone preparing for an analyst, data analyst, or business analyst role and needs the statistics foundation

Students who took a statistics class once, forgot most of it, and want the practical version

Complete beginners who have never touched statistics - the course assumes zero background

Excel users who keep hearing words like "p-value," "confidence interval," or "regression" and want to actually understand them

Business professionals tired of relying on others to interpret data for them
Homepage

Code:

https://www.udemy.com/course/microsoft-excel-statistics-data-analysis

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Microsoft Excel Statistics & Data Analysis - Zero to Analyst

voska89

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