P1_5. Data Handling

1. Types of Data

• Quantitative data: numerical, can be measured and counted.

  • Example: test scores, reaction times.

• Qualitative data: descriptive, non-numerical.

  • Example: opinions, observations of behaviour.

2. Sources of Data

• Primary data: collected first-hand by the researcher.

• Secondary data: already collected by someone else (e.g., textbooks, databases).

3. Measures of Central Tendency

• Mean: average of all scores.

• Median: middle value when scores are arranged in order.

• Mode: most frequently occurring value.

4. Measure of Spread

• Range: difference between highest and lowest values.

5. Data Presentation

• Bar charts: for categorical data.

• Histograms: for continuous data, bars touch each other.

• Scatter diagrams: show relationship between two variables.

6. Distribution

• Normal distribution: symmetrical, bell-shaped curve.

• Most scores cluster around the mean, fewer at extremes.

7. Basic Calculations

• Students should be able to use:

  • Percentages – part of a whole.

  • Ratios – relative sizes of two quantities.

  • Basic calculations – sums, differences, averages, etc.