Statistics — Mean, Median, Mode, Range and Basic Data Interpretation
Overview
Statistics is a scoring topic in TS TET Paper II Mathematics and Science section. It tests your ability to organise, analyse and interpret numerical data—skills every upper primary teacher must possess to assess student performance and handle classroom data.
Questions typically involve calculating measures of central tendency (mean, median, mode) and measures of dispersion (range) from raw or grouped data. You may also encounter data interpretation questions based on tables, bar graphs or pie charts. Mastering the formulas and understanding when to apply each measure is essential for quick, accurate answers.
This topic connects mathematics to real-world applications—analysing marks, attendance, survey results—making it pedagogically important. Expect 2-4 questions directly from this area, and the concepts reappear in EVS and Social Studies data questions.
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Key Concepts
**Data** is a collection of facts, figures or observations. It can be raw (unorganised) or organised (arranged in tables, arrays or frequency distributions).
**Mean (Arithmetic Average)** gives the central value by distributing the total equally among all observations. It uses every data point, making it sensitive to extreme values (outliers).
**Median** is the middle value when data is arranged in ascending or descending order. It is not affected by extreme values, making it ideal for skewed distributions.
**Mode** is the most frequently occurring value. A dataset can be unimodal (one mode), bimodal (two modes), multimodal or have no mode if all values occur equally.
**Range** measures the spread of data. It tells how dispersed the values are but is highly sensitive to outliers.
**Frequency Distribution** organises data into classes with their corresponding frequencies, simplifying calculation of mean, median and mode for large datasets.
**Graphical Representation** includes bar graphs, histograms, pie charts and frequency polygons—each suited for different data types and comparison needs.
For **grouped data**, we use class marks (mid-values) and apply modified formulas for mean, and cumulative frequency methods for median.
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Formulas / Key Facts
### Ungrouped Data
| Measure | Formula | |---------|---------| | **Mean** | Mean = (Sum of all observations) ÷ (Number of observations) = Σx ÷ n | | **Median** (odd n) | Middle value = value at position (n + 1)/2 | | **Median** (even n) | Average of values at positions n/2 and (n/2 + 1) | | **Mode** | Value with highest frequency | | **Range** | Range = Maximum value − Minimum value |
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| Measure | Formula | |---------|---------| | **Mean (Direct)** | Mean = Σ(f × x) ÷ Σf, where x = class mark, f = frequency | | **Mean (Assumed Mean)** | Mean = A + [Σ(f × d) ÷ Σf], where d = x − A | | **Median Class** | Class where cumulative frequency ≥ n/2 | | **Mode Class** | Class with highest frequency |
### Key Facts
Class mark = (Lower limit + Upper limit) ÷ 2
Cumulative frequency: running total of frequencies up to each class
Mean is best for symmetric data; median for skewed data; mode for categorical data
Range alone does not indicate how data is distributed within the spread
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Worked Examples
### Example 1: Ungrouped Data — All Measures
**Data:** Marks of 7 students: 12, 18, 15, 12, 20, 15, 12
A bar graph shows books read by 5 students: Anu (8), Bala (12), Chitra (6), Devi (10), Eswar (14).
*Questions:*
Who read the most books? **Eswar (14)**
What is the mean? (8 + 12 + 6 + 10 + 14) ÷ 5 = 50 ÷ 5 = **10 books**
What is the range? 14 − 6 = **8 books**
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Common Mistakes
**Forgetting to arrange data before finding median** → Always sort data in ascending order first; unsorted data gives wrong median position.
**Confusing mean and median for even-numbered data** → Mean uses all values; median for even n requires averaging two middle values, not picking one.
**Using class limits instead of class marks** → For grouped data, always calculate class mark = (lower + upper) ÷ 2 before computing mean.
**Declaring "no mode" when all frequencies are equal** → Correct. But if two values share the highest frequency, the data is bimodal—state both modes.
**Ignoring outliers when choosing central tendency** → Mean gets distorted by extreme values. If data has outliers (e.g., one student scoring 100 when others score 20-40), prefer median.
**Misreading cumulative frequency as simple frequency** → Cumulative frequency is a running total. For median class identification, use cumulative frequency, not class frequency.
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Quick Reference
1. **Mean** = Total sum ÷ Number of observations (uses all data, affected by outliers)
2. **Median** = Middle value after sorting (robust to outliers, use for skewed data)
3. **Mode** = Most frequent value (best for categorical data, can be multiple)
4. **Range** = Maximum − Minimum (simple spread measure, sensitive to extremes)
5. **Grouped data mean**: Use class marks and Σ(f × x) ÷ Σf
6. **For quick median in odd n**: Position = (n + 1)/2; in even n: average of n/2 and (n/2 + 1) positions