Introduction_to_Statistics_IGCSE with data

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1. Introduction to Statistics (IGCSE 0580) Types of Data and Methods of Collecting Data

2. Lesson Objectives • Understand what 'Statistics' means and why it’s important. • Identify types of data: qualitative, quantitative, discrete, and continuous. • Describe methods of collecting data: survey, observation, experiment, and secondary data.

3. What is Statistics? Statistics is the study of data — how it is collected, organized, analyzed, and interpreted. We use statistics to make decisions in real life, such as: • Sports performance • Weather forecasting • Business and marketing • Science and medicine

4. Why Study Statistics? • Helps us understand trends and patterns. • Assists in making predictions and decisions. • Used in almost every career field!

5. Types of Data: Qualitative vs Quantitative • Qualitative data: descriptive, non-numerical (e.g., color, name, brand). • Quantitative data: numerical, measurable (e.g., height, age, score). 🎯 Mini Quiz: Is 'shoe size' qualitative or quantitative? (Click to reveal) 👉 Answer: Quantitative

6. Types of Data: Discrete vs Continuous • Discrete data: countable, whole numbers only (e.g., number of siblings). • Continuous data: measurable, can take any value (e.g., weight, time). 🎯 Example: Height → Continuous | Number of pets → Discrete

7. Activity: Classify Me! Identify the type of data for each example: 1️⃣ Number of goals scored in a match 2️⃣ Favorite music genre 3️⃣ Temperature in °C 4️⃣ Eye color (Click for answers) Answers: 1 Discrete, 2 Qualitative, 3 Continuous, 4 Qualitative

8. Methods of Collecting Data Main ways to collect data: • Surveys • Observations • Experiments • Secondary sources

9. Survey Definition: Asking people questions to gather data. Example: A questionnaire about favorite social media platforms. Advantages: Quick, easy to reach many people. Disadvantages: Responses may be biased or incomplete.

10. Observation Definition: Watching and recording behavior or events. Example: Counting how many cars pass a junction in 10 minutes. Advantages: Real-time, no survey bias. Disadvantages: Can be time-consuming.

11. Experiment Definition: Data collected through a test or trial. Example: Testing how fertilizer affects plant growth. Advantages: Reliable and controlled. Disadvantages: Requires planning and equipment.

12. Secondary Data Definition: Using existing data collected by others. Example: Government statistics or school records. Advantages: Saves time. Disadvantages: May be outdated or not specific enough.

13. Group Activity – Design a Mini Survey In groups, create a simple survey question (e.g., 'How many hours of TV do you watch daily?'). Then identify: • Type of data (qualitative/quantitative) • Data sub-type (discrete/continuous) • Collection method (survey, observation, etc.)

14. Exit Ticket – Review Quiz 1️⃣ What is Statistics? 2️⃣ Name two types of data. 3️⃣ Give one method of collecting data. (Click to reveal answers) Answers: 1 Study of data, 2 Qualitative & Quantitative, 3 Survey/Observation/Experiment

15. Summary • Statistics helps us make sense of data. • Data can be qualitative or quantitative, discrete or continuous. • Data can be collected using surveys, observations, experiments, or secondary sources. ✅ Great work today! Don’t forget to complete your mini investigation for homework.