1. What is Statistics?

2. Types of Data

   1. Qualitative vs Quantitative

   2. Discrete vs Continuous

   3. Scales of Measurement: Nominal, Ordinal, Interval, Ratio

3. Data Collection Methods

4. Frequency Distributions

5. Graphical Representation of Data

   1. Bar Charts

   2. Histograms

   3. Pie Charts

   4. Box Plots

   5. Stem-and-Leaf Plots

   6. Scatter Plots

6. Measures of Central Tendency

   1. Mean

   2. Median

   3. Mode

7. Measures of Dispersion (Spread)

   1. Range

   2. Variance

   3. Standard Deviation

   4. Interquartile Range (IQR)

8. Measures of Position

   1. Percentiles

   2. Quartiles

   3. Z-Scores

Probability Distributions 

1. Random Variables (Discrete and Continuous)

2. Probability Distribution Functions (PDF)

3. Expected Value and Variance of a Random Variable

4. Binomial Distribution

5. Poisson Distribution

6. Geometric and Negative Binomial Distribution

7. Uniform Distribution

8. Normal Distribution

   1. Standard Normal Distribution

   2. Z-Scores and Normal Table

9. Central Limit Theorem

10. Exponential Distribution

Non-Parametric Tests (Advanced/Optional) 

1. Basic Probability Concepts

   1. Sample Space and Events

   2. Classical, Empirical, and Subjective Probability

2. Addition and Multiplication Rules

3. Complement Rule

4. Conditional Probability

5. Independent and Dependent Events

6. Permutations and Combinations

7. Bayes' Theorem

Inferential Statistics 

1. Sampling Methods and Techniques

   1. Random, Stratified, Systematic, Cluster Sampling

2. Sampling Distributions

3. Estimation

   1. Point Estimators

   2. Confidence Intervals (for mean, proportion, variance)

4. Hypothesis Testing

   1. Null and Alternative Hypotheses

   2. Type I and Type II Errors

   3. p-value and Significance Level (α)

   4. One-Tailed vs Two-Tailed Tests

5. Tests for Population Means and Proportions

   1. Z-test

   2. t-test (One-sample and Two-sample)

   3. Chi-Square Test

   4. ANOVA (Analysis of Variance)

   5. F-test

Correlation and Regression 

1. Scatter Plots

2. Correlation Coefficient (r)

3. Linear Regression

   1. Least Squares Method

   2. Coefficient of Determination (R²)

4. Multiple Regression (Intro)

5. Residuals and Prediction

Statistical Software and Tools (Optional Section) 

1. Using Excel, R, Python, SPSS, or MiniTab for Statistical Analysis

2. Graphing and Data Visualization Tools

3. Simulations in Statistics
   
   

Real-Life Applications of Statistics