Here are the answers to all questions on your exam paper:
QUE. 1 - MULTIPLE CHOICE QUESTIONS
1. -------- is not an example of secondary data.
Answer: D) Population Census
Population Census is primary data (collected directly by the government). Company Annual Reports, CSO Reports, and RBI Bulletins are all secondary data sources (already compiled/published by organizations).
2. Which of the following is a measure of central tendency?
Answer: C) Mean
Mean, Median, and Mode are measures of central tendency. Standard Deviation and Variance are measures of dispersion. M.D. (Mean Deviation) is also a measure of dispersion.
3. A continuous variable can take ________
Answer: C) Any value within a range
A continuous variable can take any numerical value within a given range (e.g., height = 165.3 cm, 165.31 cm). It is not restricted to integers or whole numbers only.
4. The difference between upper limit and lower limit of a class is called
Answer: B) Class width
Class width (also called class interval or class size) = Upper class limit - Lower class limit.
5. The easiest and most commonly used method of sampling is ________
Answer: A) Simple random sampling
Simple random sampling is the most basic and commonly referenced sampling method where every member of the population has an equal chance of being selected.
QUE. 2 - SHORT ANSWER QUESTIONS (5 Marks Each)
A) Define 'Biostatistics'. Write the scope of Statistics in Ayurveda.
Definition of Biostatistics:
Biostatistics is the application of statistical methods to biological and health-related data. It involves the collection, organization, analysis, interpretation, and presentation of data related to living organisms, especially in the context of medicine and public health.
Scope of Statistics in Ayurveda:
- Clinical Research - Statistical methods help design and evaluate Ayurvedic clinical trials (e.g., efficacy of herbal formulations).
- Drug Standardization - Statistics helps in quality control of Ayurvedic drugs and raw materials.
- Epidemiological Studies - Understanding the prevalence of diseases and the role of Prakriti (body constitution) in disease susceptibility.
- Outcome Assessment - Measuring treatment outcomes using scoring systems for symptoms like Ashtavidha Pariksha results.
- Survey and Sampling - Population surveys on dietary habits, lifestyle diseases, and traditional practices.
- Evidence-Based Ayurveda - Building scientific evidence base for Ayurvedic interventions through properly designed studies.
- Documentation & Records - Systematic documentation of case studies for analysis.
B) Write a short note on Histogram and Bar Chart.
Histogram:
- A histogram is a graphical representation of the frequency distribution of continuous (quantitative) data.
- The data is grouped into class intervals (bins) on the X-axis; frequency is on the Y-axis.
- The bars are adjacent (touching each other) - no gaps between bars.
- Area of each bar = frequency of that class.
- Used for: age distribution, weight distribution, blood pressure values, etc.
Bar Chart (Bar Diagram):
- A bar chart is used to represent discrete or categorical (qualitative) data.
- Bars are drawn with equal width and gaps between them.
- Height of each bar represents the frequency or value of that category.
- Can be vertical (column chart) or horizontal.
- Used for: comparing blood groups among patients, number of cases per disease, etc.
| Feature | Histogram | Bar Chart |
|---|---|---|
| Data type | Continuous | Discrete/Categorical |
| Bars | Adjacent (no gap) | Separated (with gaps) |
| X-axis | Class intervals | Categories |
| Purpose | Frequency distribution | Comparison |
QUE. 3 - LONG ANSWER QUESTION (10 Marks)
A) Define Measures of Central Tendency. Which measures are commonly used? Discuss in brief.
Definition:
A measure of central tendency is a single value that represents the center or typical value of a dataset. It summarizes a large set of data into one representative figure around which the other values tend to cluster.
Commonly Used Measures of Central Tendency:
1. Mean (Arithmetic Mean)
- The sum of all observations divided by the total number of observations.
- Formula: X̄ = ΣX / N
- Example: If weights of 5 patients are 50, 55, 60, 65, 70 kg → Mean = 300/5 = 60 kg
- Merits: Uses all values; mathematically precise; widely used.
- Demerits: Affected by extreme values (outliers).
- Use in Medicine: Mean blood glucose level, mean BP, mean age of patients.
2. Median
- The middle value when data is arranged in ascending or descending order.
- For odd n: Median = value of ((n+1)/2)th observation.
- For even n: Median = average of (n/2)th and (n/2 + 1)th observations.
- Example: 50, 55, 60, 65, 70 → Median = 60
- Merits: Not affected by extreme values; suitable for skewed distributions.
- Demerits: Does not use all values; less algebraically manageable.
- Use in Medicine: Median survival time, median income for health surveys.
3. Mode
- The value that occurs most frequently in a dataset.
- A dataset can be unimodal, bimodal, or multimodal.
- Example: In the data 55, 60, 60, 65, 70 → Mode = 60
- Merits: Easy to determine; not affected by extremes; can be used for qualitative data.
- Demerits: May not be unique; not always clearly defined.
- Use in Medicine: Most common blood group, most frequent symptom reported.
Comparison Table:
| Property | Mean | Median | Mode |
|---|---|---|---|
| Affected by outliers | Yes | No | No |
| Uses all values | Yes | No | No |
| Best for | Symmetric data | Skewed data | Categorical data |
| Mathematical use | High | Moderate | Low |
Relationship between Mean, Median & Mode:
For a moderately skewed distribution:
Mode = 3 Median - 2 Mean (Karl Pearson's empirical relation)
In a perfectly normal (symmetric) distribution: Mean = Median = Mode
Conclusion: Among the three, the Mean is the most commonly used measure in medical research due to its mathematical properties and use in further statistical calculations like standard deviation, t-tests, etc. However, the Median is preferred when data is skewed or has outliers (e.g., survival data, income data).
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