Statistics & Excel

Unlock the Power of Statistical Analysis and Excel in Data-Driven Decision-Making for Various Fields

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Course curriculum

1. 1000 Introduction
2. 1120 Getting a Picture – Data & Distribution
1. OneNote Recourse
2. 1011 Hamlet, Harry Potter, & Statistics
3. 1014 Where to Find Data to Practice With
4. 1021 Wages Data Box Plot or Box & Whiskers
5. 1025 Wages Data Box Plot or Box Whiskers vs Histogram
6. 1031 Histogram vs. Bar Chart29e63df.autosave
7. 1041 Histograms with Different Bucket Sizes
8. 1051 Misleading Histogram
9. 1056 Histograms with Car Related Data
10. 1061 Scatter Plots with Car Related Data
11. 1066 Histograms and Scatter Plots with Population Data
12. 1070 Histogram Examples
1. 1010 Hamlet, Harry Potter, & Statistics
2. 1015 Generating Practice Data in Excel
3. 1016 Sort Comma & Space Delimited Data into a Column
4. 1017 Sort Data Randomly
5. 1020 Wages Data Box Plot or Box & Whiskers
6. 1022 Wages Data Box Plot or Box & Whiskers Analysis
7. 1024 Wages Data Box Plot or Box Whiskers vs Histogram
8. 1030 Histogram vs. Bar Chart
9. 1040 Histograms with Different Bucket Sizes
10. 1050 Misleading Histogram
11. 1055 Histograms with Car Related Data
12. 1060 Scatter Plots with Car Related Data
13. 1065 Histograms and Scatter Plots with Population Data
1. 1306 Statistical Inference - Questions of How Close & How Confident
1. OneNote Recourse
2. 1311 Height Statistical Inference Data Practice Problem
3. 1316 Coin Flip Statistics Example
4. 1326 Deck of Cards, Statistics, & Excel
5. 1336 Election Poll Statistics Example
6. 1346 Combining Two Histograms on One Chart
7. 1361 Calories Data Statistics Sample Example
1. 1310 Height Statistical Inference Data - Excel Practice Problem
2. 1315 Coin Flip Statistics Example in Excel
3. 1319 Coin Flip Statistics Example in Excel Part 2
4. 1325 Deck of Cards, Statistics, & Excel
5. 1329 Deck of Cards, Statistics, & Excel Part 2
6. 1335 Election Poll Statistics Example
7. 1339 Election Poll Statistics Example Part 2
8. 1345 Combining Two Histograms on One Chart
9. 1349 Combining Two Histograms on One Chart Part 2
10. 1353 Combining Two Histograms on One Chart Part 3
11. 1360 Calories Data Statistics Sample Example
1. 1406 Standard Deviation – Measuring Spread
1. OneNote Recourse
2. 1411 Typing Mathematical Equations in Microsoft Office
3. 1417 Mean and Outliers
4. 1423 Issue with 5 Number Summary & Box Blot
5. 1429 Average Deviation
6. 1433 Population Variance & Standard Deviation
7. 1443 Average Deviation, Standard Deviation & Variance for Population with Salary Data
8. 1447 Standard Deviation & Variance - Large Outlier Impact
9. 1467 Standard Deviation & Variance for a Population – Comparing Two Data Sets Related to Weight
1. 1410 Typing Mathematical Equations in Microsoft Excel
2. 1416 Mean and Outliers
3. 1422 Issue with 5 Number Summary & Box Blot
4. 1428 Average Deviation
5. 1432 Population Variance & Standard Deviation
6. 1436 Standard Deviation vs Average Deviation
7. 1442 Average Deviation, Standard Deviation & Variance for Population with Salary Data
8. 1446 Standard Deviation & Variance - Large Outlier Impact
9. 1452 Standard Deviation & Variance – Population Location Data
10. 1458 Standard Deviation & Variance for a Population - Calories Data
11. 1466 Standard Deviation & Variance for a Population – Comparing Two Data Sets Related to Weight
1. 1506 Probability Distribution Models and Families
1. OneNote Recourse
2. 1511 Uniform Distributions Dice
3. 1521 Poisson Distribution Formula & Graph
4. 1537 Poisson Distribution – Roller Coaster Line Example
5. 1547 Poisson Distribution – Potholes in Road Example
6. 1557 Binomial Distribution Formula and Chart
7. 1561 Binomial Distribution – Coin Flip – Random Number Generation
8. 1567 Binomial Distribution – Manual & Excel Function – Sales Calls Example
9. 1571 Binomial Distribution – Multiple X – Drive to Work in Traffic Example
10. 1577 Exponential Distribution – In Seconds – Roller Coaster Line Example
11. 1581 Create & Compare Sample Line Waiting Data to Exponential Distribution
1. 1510 Uniform Distributions Dice
2. 1520 Poisson Distribution Formula
3. 1526 Poisson Distribution - Excel Function & Graph
4. 1530 Poisson Distribution - Random Number Generation Example
5. 1536 Poisson Distribution – Roller Coaster Line Example
6. 1539 Poisson Distribution – Roller Coaster Line Example Part 2
7. 1546 Poisson Distribution – Potholes in Road Example Part 1
8. 1550 Poisson Distribution – Potholes in Road Example Part 2
9. 1556 Binomial Distribution Formula and Chart
10. 1560 Binomial Distribution – Coin Flip – Random Number Generation
11. 1566 Binomial Distribution – Manual & Excel Function – Sales Calls Example
12. 1570 Binomial Distribution – Multiple X – Drive to Work in Traffic Example
13. 1576 Exponential Distribution – In Seconds – Roller Coaster Line Example
14. 1580 Create & Compare Sample Line Waiting Data to Exponential Distribution
1. 1610 Normal Distribution Bell Shaped Curve Gaussian Curve
1. OneNote Recourse
2. 1611 Bell Curve – Test Score Example
3. 1621 Normal Distribution – Heights of Baseball Players Data545849f.autosave
4. 1627 Bell Curve-People Weight Example
5. 1633 Normal Distribution – Calories Example
6. 1639 Bell Curve Batting Average Comparison
1. 1610 Bell Curve – Test Score Example Part 1
2. 1612 Bell Curve – Test Score Example Part 2
3. 1614 Bell Curve – Test Score Example Part 3
4. 1620 Normal Distribution – Hights of Baseball Players Data
5. 1622 Normal Distribution – Hights of Baseball Players Data Part 2
6. 1626 Bell Curve-People Weight Example Part 1
7. 1628 Bell Curve-People Weight Example Part 2
8. 1632 Normal Distribution – Calories Example
9. 1634 Normal Distribution – Calories Example Part 2
10. 1638 Bell Curve Batting Average Comparison
11. 1640 Bell Curve Batting Average Comparison Part 2
1. 1710 Correlation and Regression
1. OneNote Recourse
2. 1711 Perfect Positive Correlation
3. 1719 Perfect Negative Correlation
4. 1726 Correlation Simple Few Data Points Example
5. 1731 Correlation Random Number Generation Example
6. 1741 Correlation Calculation with Strange Result
7. 1751 Correlation Large Data Sets Focus of Z Score Relationship95be444.autosave
8. 1761 Correlation Baseball Statistics
1. 1710 Perfect Positive Correlation
2. 1712 Perfect Positive Correlation Part 2
3. 1718 Perfect Negative Correlation
4. 1725 Correlation Simple Low Data Points Example
5. 1730 Correlation Random Number Generation Example
6. 1732 Correlation Random Number Generation Example Part 2
7. 1740 Correlation Calculation with Strange Result
8. 1750 Correlation Large Data Sets Focus of Z Score Relationship Part 1
9. 1752 Correlation Large Data Sets Focus of Z Score Relationship Part 2
10. 1760 Correlation Baseball Statistics
11. 1762 Correlation Baseball Statistics Part 2
1. 1810 Probability-The Engine of Inference
1. 1811 Coin Flip Expected Value-Even & Uneven Odds & Coin
2. 1821 Birthday Probability Game
3. 1827 Roulette Probability Example
4. 1851 Chuck-A-Luck Example
5. 1857 Dice Central Limit Theorem Example
1. 1810 Coin Flip Expected Value-Even & Uneven Odds & Coin Part 1
2. 1812 Coin Flip Expected Value-Even & Uneven Odds & Coin Part 2
3. 1814 Coin Flip Expected Value-Even & Uneven Odds & Coin Part 3
4. 1820 Birthday Probability Game
5. 1826 Roulette Probability Example Part 1
6. 1828 Roulette Probability Example Part 2
7. 1830 Roulette Probability Example Part 3
8. 1832 Roulette Probability Example Part 4
9. 1834 Roulette Probability Example Part 5
10. 1836 Roulette Probability Example Part 6
11. 1838 Roulette Probability Example Part 7
12. 1840 Roulette Probability Example Part 8
13. 1850 Chuck-A-Luck Example Part 1
14. 1852 Chuck-A-Luck Example Part 2
15. 1856 Dice Central Limit Theorem Example Part 1
16. 1858 Dice Central Limit Theorem Example Part 2
17. 1860 Dice Central Limit Theorem Example Part 3
18. 1862 Dice Central Limit Theorem Example Part 4
1. 1910 Sampling
2. 1915 Central Limit Theorem (CLT)
3. 1920 Standard Error
1. 1910-1 Central Limit Theorem Pop Data Skewed to the Right
2. 1921 Central Limit Theorem – All Possible Samples Example
3. 1925-6 Standard Error, Estimated Standard Deviation of Xbar Correction Factor
4. 1930 Standard Deviation of Means Estimate Example
5. 1936-7 Binomial Distribution Standard Deviation of Sample Means or Standard Error (1)
6. 1941 Standard Error, Margin of Error, Hypothesis Test, _ Confidence Interval
1. 1910 Central Limit Theorem Pop Data Skewed to the Right
2. 1920 Central Limit Theorem – All Possible Samples Example
3. 1925 Standard Error, Estimated Standard Deviation of Xbar Correction Factor
4. 1930 Standard Deviation of Means Estimate Example
5. 1936 Binomial Distribution Standard Deviation of Sample Means or Standard Error
6. 1938 Binomial Distribution Standard Deviation of Sample Means or Standard Error Part 2
7. 1940 Standard Error, Margin of Error, Hypothesis Test, & Confidence Interval
8. 1942 Standard Error, Margin of Error, Hypothesis Test, & Confidence Interval Part 2
1. 1930 Confidence Interal
1. 1947 Confidence Interval Example T Distribution
2. 1949 Binomial Experiment – Do You Own a Pet
3. 1951 Binomial Experiment – Proportion of Customer Complaints Remedied
4. 1955 t Distribution Graph Showing Degrees of Freedom
5. 1957 Confidence Interval when Standard Deviation of Population is Know
6. 1961 Confidence Interval when Standard Deviation of Population is Not Know
7. 1967 Confidence Interval t distribution when Standard Deviation of Population is Not Know
8. 1971 Confidence Interval – Binomial Distribution Survey Example
9. 1975 Confidence Interval – Binomial Distribution Survey Example - 2
1. 1946 Confidence Interval Example T Distribution
2. 1948 Binomial Experiment – Do You Own a Pet
3. 1950 Binomial Experiment – Proportion of Customer Complaints Remedied
4. 1954 t Distribution Graph Showing Degrees of Freedom
5. 1956 Confidence Interval when Standard Deviation of Population is Know34df668.autosave
6. 1958 Confidence Interval when Standard Deviation of Population is Know Part 2
7. 1960 Confidence Interval when Standard Deviation of Population is Not Know
8. 1966 Confidence Interval t distribution when Standard Deviation of Population is Not Know
9. 1970 Confidence Interval – Binomial Distribution Survey Example
10. 1974 Confidence Interval – Binomial Distribution Survey Example - 2
1. 1925 Hypothesis Testing
1. 1977 Hypothesis Testing 1 Tail Upper - STDp Known
2. 1979 Hypothesis Testing 1 Tail Lower - STDp Known
3. 1981 Hypothesis Testing 2 Tail - STDp Known
4. 1983 Hypothesis Testing t Distribution 1 Tail Upper- STDp Not Known
5. 1985 Hypothesis Testing t Distribution 1 Tail Lower- STDp Not Known
6. 1987 Hypothesis Testing t Distribution 2 Tail- STDp Not Known
1. 1976 Hypothesis Testing 1 Tail Upper - STDp Known
2. 1978 Hypothesis Testing 1 Tail Lower - STDp Known
3. 1980 Hypothesis Testing 2 Tail - STDp Known
4. 1982 Hypothesis Testing t Distribution 1 Tail Upper- STDp Not Known
5. 1984 Hypothesis Testing t Distribution 1 Tail Lower- STDp Not Known
6. 1986 Hypothesis Testing t Distribution 2 Tail- STDp Not Known

About this course

$150.00
205 lessons
88.5 hours of video content

Description

Welcome to this Statistics & Excel course your comprehensive resource for mastering the art of data interpretation and statistical analysis, complemented by practical applications in Excel. Throughout this course, we will delve into the foundational principles of statistics, providing you with a robust grounding in the essential concepts typically found in undergraduate-level statistical textbooks.

Understanding the Significance of Data:

In our data-centric world, the ability to comprehend, analyze, and draw meaningful conclusions from data is an invaluable skill. Data holds a pivotal role in various domains, including medicine, finance, meteorology, education, and social sciences. We will delve into the critical role of statistics within these fields, laying the groundwork for our exploration of statistical concepts.

Deciphering the Dual Nature of Data:

Data can be both enlightening and misleading, as famously noted in Mark Twain's quote about lies and statistics. Our course's objective is to equip you with the discernment needed to differentiate between insightful findings and deceptive interpretations. Real-world case studies will serve as our guiding compass on this enlightening journey.

Fostering Statistical Insight:

Our primary aim is to empower you with a profound understanding of statistical principles. Probability theory will be a valuable ally in quantifying uncertainty and facilitating data-driven decision-making. Throughout the course, we will harness the versatility of Excel as a tool to bridge the gap between theory and practical application.

Addressing Statistical Challenges:

As we progress, we will confront two fundamental statistical challenges. Firstly, comprehensive data analysis entails extracting valuable insights from extensive datasets. For instance, we may predict future trends in student performance based on historical academic records. Secondly, statistical inference will guide us in making predictions about broader populations based on smaller sample sizes, such as estimating average heights using survey data.

Course Objectives:

Our educational journey will be enriched with a multitude of real-world examples, illustrating the practicality and wide applicability of statistical analysis. Beyond mere formulaic calculations, our goal is to cultivate your understanding of the logical foundations and strategies that underpin sound statistical reasoning.

Preparation for a Data-Centric World:

In today's technology-driven era, statistical literacy is an indispensable asset. The ability to interpret data and derive meaningful insights is in high demand. Given the increasing availability of vast datasets and advanced analytical techniques, your proficiency in statistics is a valuable asset in various academic and professional spheres.

Essential Tools:

Mathematics: A foundational language of statistics, which we will explore through key concepts and formulas.

Excel: We will harness the capabilities of Excel for practical applications and hands-on exercises, ensuring your readiness to tackle real-world data challenges.

Join us on this enriching journey into the world of data analysis and statistics with Excel, and acquire the skills and knowledge essential for success in our data-driven society. Whether you are a student, a professional, or simply intrigued by the potential of data, this course serves as your gateway to mastering statistics, firmly grounded in standard undergraduate statistical material.