Statistics & Excel
Published 9/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 19.62 GB | Duration: 29h 56m
Published 9/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 19.62 GB | Duration: 29h 56m
Unlock the Power of Statistical Analysis and Excel in Data-Driven Decision-Making for Various Fields
What you'll learn
Perform In-Depth Data Analysis: Dive deep into diverse datasets, applying statistical techniques to uncover meaningful insights and trends.
Create Powerful Data Visualizations: Develop informative data visualizations using tools like Excel, making complex data easy to understand.
Build Predictive Models: Construct predictive models to forecast future outcomes accurately.
Drive Strategic Decision-Making: Use statistical insights to guide strategic decisions across diverse professional contexts.
Communicate Data Findings: Enhance your data communication skills, conveying results persuasively through various mediums.
Calculate and interpret key descriptive statistics such as mean, median, mode, variance, and standard deviation to summarize data effectively.
Understand the fundamental principles of probability, including probability distributions, random variables, and their applications in real-life scenarios.
Create clear and informative data visualizations, such as histograms, scatter plots, and box plots, to communicate insights effectively.
Requirements
Basic Math Skills: A fundamental understanding of arithmetic, algebra, and basic mathematical concepts is required.
Access to Microsoft Excel: You should have access to Microsoft Excel or equivalent spreadsheet software for hands-on exercises and projects.
Curiosity and Dedication: Approach the course with a curious mindset and a dedication to learning, as statistics can be challenging but rewarding.
Computer and Internet Access: You'll need a computer or laptop with internet access to participate in the course materials and online resources.
Openness to Data Analysis: Be open to exploring data, drawing conclusions, and making data-driven decisions in various fields.
Description
Welcome to "Statistics and Excel," your comprehensive guide to mastering the art of data analysis and statistics, enriched with practical Excel applications. In this course, we will delve into the core concepts of statistics, providing you with a solid foundation rooted in standard undergraduate statistical textbook concepts.The Significance of Data:In our data-driven world, the ability to understand, analyze, and draw conclusions from data is a paramount skill. Data plays a pivotal role in fields like medicine, finance, meteorology, education, and social sciences. We'll explore the essential role of statistics in these domains, setting the stage for our statistical journey.Decoding Data's Dual Nature:Data can be both enlightening and deceptive, a concept beautifully encapsulated by Mark Twain's famous quote about lies and statistics. Our course aims to equip you with the discernment needed to distinguish between meaningful insights and misleading interpretations. Real-world case studies will be our compass on this enlightening path.Empowering Statistical Thinking:Our primary goal is to empower you with a deep understanding of statistical principles. Probability theory will be a key ally in quantifying uncertainty and making data-informed decisions. Throughout the course, we'll utilize Excel as a versatile tool to translate theory into practice.Confronting Statistical Challenges:As we progress, we'll confront two fundamental statistical challenges. First, comprehensive data analysis involves extracting valuable insights from complete datasets. For example, we might predict future trends in student performance based on historical academic records. Second, statistical inference guides us in making predictions about larger populations based on smaller samples, such as estimating average heights using survey data.Course Goals:Our educational journey is enriched with a plethora of real-world examples, illustrating the practicality and wide applicability of statistical analysis. Beyond formulaic calculations, we aim to nurture your understanding of the logical foundations and strategies that underpin statistical reasoning.Preparing for a Data-Centric World:In today's technology-driven era, statistical literacy is a vital asset. The ability to interpret data and draw meaningful insights is highly sought after. With the ever-increasing availability of vast datasets and advanced analytical techniques, your proficiency in statistics is an invaluable asset in various academic and professional domains.Key Tools:Mathematics: A foundational language of statistics, which we'll explore through key concepts and formulae.Excel: We'll harness the power of Excel for practical applications and hands-on exercises, ensuring you're well-prepared to tackle real-world data challenges.Join us on this enriching journey into the realm of statistics and Excel, and gain the skills and knowledge needed to excel in our data-driven society. Whether you're a student, a professional, or simply curious about the power of data, this course is your gateway to statistical mastery, firmly grounded in standard undergraduate statistical material.
Overview
Section 1: PP-Introduction-Getting a Picture From Data
Lecture 1 1000 Introduction
Lecture 2 1120 Getting a Picture – Data & Distribution
Section 2: ON-Introduction-Getting a Picture From Data
Lecture 3 OneNote Resource
Lecture 4 1011 Hamlet, Harry Potter, & Statistics
Lecture 5 1014 Where to Find Data to Practice With
Lecture 6 1021 Wages Data Box Plot or Box & Whiskers
Lecture 7 1025 Wages Data Box Plot or Box Whiskers vs Histogram
Lecture 8 1031 Histogram vs. Bar Chart
Lecture 9 1041 Histograms with Different Bucket Sizes
Lecture 10 1051 Misleading Histogram
Lecture 11 1056 Histograms with Car Related Data
Lecture 12 1061 Scatter Plots with Car Related Data
Lecture 13 1066 Histogram and Scatter Plots with Population Data
Lecture 14 1070 Histogram Examples
Section 3: Ex-Introduction-Getting a Picture From Data
Lecture 15 1010 Hamlet, Harry Potter, & Statistics
Lecture 16 1015 Generating Practice Data in Excel
Lecture 17 1016 Sort Comma Delimited Data into a Column
Lecture 18 1017 Randomly Sort a Column of Data
Lecture 19 1020 Wages Box Plot
Lecture 20 1022 Wages Data Box Plot or Box Whiskers Analysis
Lecture 21 1024 Wages Data Box Plot or Box Whiskers vs Histogram
Lecture 22 1030 Histogram vs. Bar Chart
Lecture 23 1040 Histogram with Different Bucket Sizes
Lecture 24 1050 Misleading Histogram
Lecture 25 1055 Histograms with Car Related Data
Lecture 26 1060 Scatter Plots with Car Related Data
Lecture 27 1065 Histogram and Scatter Plots with Population Data
Section 4: PP-Statistical Inference - Questions of: How Close & How Confident
Lecture 28 1306 Statistical Inference - Questions of: How Close & How Confident
Section 5: ON-Statistical Inference - Questions of: How Close & How Confident
Lecture 29 1311 Height Statistical Inference Data Practice Problem
Lecture 30 1316 Coin Flip Statistics Example
Lecture 31 1326 Deck of Cards, Statistics, & Excel
Lecture 32 1336 Election Poll Statistics Example
Lecture 33 1346 Combining Two Histograms on One Chart
Lecture 34 1361 Calories Data Statistics Sample Example
Section 6: Ex-Statistical Inference - Questions of: How Close & How Confident
Lecture 35 u1310 Height Statistical Inference Data - Excel Practice Problem
Lecture 36 1315 Coin Flip Statistics Example in Excel
Lecture 37 1319 Coin Flip Statistics Example in Excel Part 2
Lecture 38 1325 Deck of Cards, Statistics, & Excel
Lecture 39 1329 Deck of Cards, Statistics, & Excel Part 2
Lecture 40 1335 Election Poll Statistics Example
Lecture 41 1339 Election Poll Statistics Example Part 2
Lecture 42 1345 Combining Two Histograms on One Chart Part 1
Lecture 43 1349 Combining Two Histograms on One Chart Part 2
Lecture 44 1353 Combining Two Histograms on One Chart Part 3
Lecture 45 1360 Calories Data Statistics Sample Example
Section 7: PP-Data Dispersion or Spread – Standard Deviation & Variance
Lecture 46 1406 Standard Deviation – Measuring Spread
Section 8: ON-Data Dispersion or Spread – Standard Deviation & Variance
Lecture 47 1411 Typing Mathematical Equations in Microsoft Excel
Lecture 48 1417 Mean and Outliers
Lecture 49 1423 Issue with 5 Number Summary & Box Blot
Lecture 50 1429 Average Deviation
Lecture 51 1433 Population Variance & Standard Deviation
Lecture 52 1443 Standard Deviation & Variance for Population with Salary Data
Lecture 53 1447 Standard Deviation & Variance – Large Outlier Impact
Lecture 54 1467 Standard Deviation & Variance for a Population – Comparing Two Data Sets of
Section 9: Ex-Data Dispersion or Spread – Standard Deviation & Variance
Lecture 55 1410 Typing Mathematical Equations in Microsoft Excel
Lecture 56 1416 Mean and Outliers
Lecture 57 1422 Issue with 5 Number Summary & Box Blot
Lecture 58 1428 Average Deviation
Lecture 59 1432 Population Variance & Standard Deviation
Lecture 60 1436 Standard Deviation vs Average Deviation
Lecture 61 1442 Average Deviation, Standard Deviation & Variance for Population with Salary
Lecture 62 1446 Standard Deviation & Variance - Large Outlier Impact
Lecture 63 1452 Standard Deviation & Variance – Population Location Data
Lecture 64 1458 Standard Deviation & Variance for a Population - Calories Data
Lecture 65 1466 Standard Deviation & Variance for a Population – Comparing Two Data Sets Re
Section 10: PP-Probability Distribution Models and Families
Lecture 66 u1506 Probability Distribution Models and Families
Section 11: ON-Probability Distribution Models and Families
Lecture 67 u1511 Uniform Distributions Dice
Lecture 68 u1521 Poisson Distribution Formula
Lecture 69 u1537 Poisson Distribution – Roller Coaster Line
Lecture 70 u1547 Poisson Distribution – Potholes in Road Example
Lecture 71 u1557 Binomial Distribution Formula and Chart
Lecture 72 u1561 Binomial Distribution – Coin Flip – Random Number Generation
Lecture 73 u1567 Binomial Distribution – Manual & Excel Function – Sales Calls Example
Lecture 74 u1571 Binomial Distribution – Multiple X – Drive to Work in Traffic Example
Lecture 75 u1577 Exponential Distribution – In Seconds – Roller Coaster Line Example
Lecture 76 u1581 Exponential Distribution – Create & Compare Sample Line Waiting Data to Ex
Section 12: Ex-Probability Distribution Models and Families
Lecture 77 u1510 Uniform Distributions Dice
Lecture 78 u1520 Poisson Distribution Formula
Lecture 79 u1526 Poisson Distribution Excel Function & Graph
Lecture 80 u1530 Poisson Distribution - Random Number Generation Example
Lecture 81 u1536 Poisson Distribution – Roller Coaster Line
Lecture 82 u1539 Poisson Distribution – Roller Coaster Line Part 2
Lecture 83 u1546 Poisson Distribution – Potholes in Road Example Part 1
Lecture 84 u1556 Binomial Distribution Formula and Chart
Lecture 85 u1560 Binomial Distribution – Coin Flip – Random Number Generation
Lecture 86 u1566 Binomial Distribution – Manual & Excel Function – Sales Calls Example
Lecture 87 u1570 Binomial Distribution – Multiple X – Drive to Work in Traffic Example
Lecture 88 u1576 Exponential Distribution – In Seconds – Roller Coaster Line Example
Lecture 89 u1580 Exponential Distribution – Create & Compare Sample Line Waiting Data to Ex
Students: Undergraduate students studying statistics or related fields who want a solid foundation in statistical concepts and data analysis.,Professionals: Working professionals seeking to enhance their data analysis skills, make informed decisions, and improve their job prospects.,Entrepreneurs: Entrepreneurs and small business owners looking to utilize data-driven insights for business growth and decision-making.,Data Enthusiasts: Anyone passionate about understanding the world through data analysis and gaining practical knowledge of statistics.,Researchers: Researchers from various disciplines who want to strengthen their statistical analysis skills for academic or professional research,Self-Learners: Individuals interested in self-paced learning, regardless of their educational or professional background, who wish to acquire statistical expertise.,Excel Users: Individuals familiar with Microsoft Excel who want to explore its statistical capabilities for practical applications.