1. Understanding Data

• Types of data: Categorical vs. Numerical

• Population vs. Sample

• What is a population?

• Why do we take a sample?

• How does sample size affect results?

• Bias in data collection (How to ensure fair representation)

2. Data Representation

• Frequency tables and Tally marks

• Bar graphs and pictographs

• Pie charts (percentages in data)

• Line graphs (showing trends over time)

• Histograms (introduction)

3. Measures of Central Tendency

• Mean, Median, Mode (with real-life applications)

• Comparing different measures and when to use them

4. Interpreting Data and Making Conclusions

• Identifying trends and patterns

• Drawing conclusions from graphs and tables

• Understanding misleading data (how statistics can be misused)