Microsoft Excel: Essential Statistics for Data Analysis
Learn statistics for data analysis with fun, real-world Excel demos: probability, hypothesis testing, regression & more!
4.65 (1399 reviews)
10 610
students
8 hours
content
Nov 2024
last update
$99.99
regular price
What you will 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
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Comidoc Review
Our Verdict
Microsoft Excel: Essential Statistics for Data Analysis offers a comprehensive approach, transforming traditional statistics education by incorporating real-world examples and practical exercises. While some areas might benefit from further explanation or adjustments in pacing, the course's strengths lie in emphasizing interpretation and application of fundamental statistical concepts. Enhance your data analysis skills with this insightful and engaging learning experience.
What We Liked
- The course excels in emphasizing the interpretation of statistical concepts rather than just focusing on formulas, making it easy for learners to grasp the essence of statistics.
- Examples and exercises using Excel formulas enable critical data analysis before drawing conclusions, enhancing practical skills.
- In-depth exploration of essential topics like t-distributions, confidence intervals, and regression models prepares learners for real-world applications.
- Frequent quizzes, challenges, and instructor-led solutions promote better understanding and conceptual thinking during the learning process.
Potential Drawbacks
- Some learners might find the lack of extensive use of normal distribution graphs in explaining confidence intervals confusing.
- Pace can be overwhelming for those seeking a more gradual introduction to certain topics, such as hypothesis testing.
- The course is denser than its advertised duration, making it challenging for learners to complete within the suggested timeframe.
- Expanding on concepts introduced towards the end of the course may help increase understanding and direct applicability.
Related Topics
4978160
udemy ID
15/11/2022
course created date
04/12/2022
course indexed date
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