📘 Course Title: Statistics

Code: 29020-AUX

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🏁 Introduction:

Statistics is the science of collecting, analyzing, interpreting, and presenting data. It provides essential tools for decision-making under uncertainty and supports scientific discovery across disciplines.

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✨ Course Description:

This course covers both the fundamental and advanced concepts of statistics, including descriptive statistics, probability theory, inferential methods, and advanced modeling techniques. It is designed to build a strong foundation for applications in data science, research, and engineering.

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🎯 Target Audience:

• Students and professionals in Mathematics, Data Science, Engineering, and Research.

• Analysts and decision-makers who require statistical insights.

• Anyone seeking to develop solid statistical reasoning skills.

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📚 What You Will Learn:

• Summarize and visualize data using descriptive statistics.

• Understand and apply basic probability concepts.

• Perform statistical inference including estimation and hypothesis testing.

• Use advanced statistical techniques like ANOVA and statistical modeling.

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🧑‍🏫 Instruction Methodology:

• 📖 Theoretical Lectures with Practical Examples.

• 📊 Hands-on Data Analysis Workshops.

• 🖥️ Software-based Analysis (Excel, R, or Python).

• 📚 Assignments and Case Studies.

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🧩 Main Modules:

1️⃣ Descriptive Statistics

• 📊 Measures of Central Tendency (Mean, Median, Mode)

• 📊 Measures of Dispersion (Variance, Standard Deviation)

2️⃣ Probability Theory

• 🎲 Random Variables

• 🎲 Probability Distributions (Binomial, Normal, Poisson)

3️⃣ Statistical Inference

• 🧮 Estimation Techniques

• 🧮 Hypothesis Testing (Z-test, t-test, Chi-Square test)

4️⃣ Advanced Statistical Analysis

• 📈 Analysis of Variance (ANOVA)

• 📈 Statistical Modeling (Regression Analysis)

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🎒 Materials Included:

• 📘 Comprehensive Lecture Notes

• 📈 Practice Datasets and Problem Sets

• 🖥️ Software Tutorials (R/Python/Excel)

• 📹 Recorded Sessions and Supplementary Videos

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🕒 Course Duration:

• 8 weeks — Two sessions per week.

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📈 Level:

• Intermediate (Basic knowledge of algebra and introductory probability is recommended).

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