Topics covered (8)

1. Collection & Representation of Data — Collection of Data Data can be collected as Primary Data (collected first-hand for a specific purpose — surveys, experiments, interviews) or Secondary Data (already collected by…
2. Measures of Central Tendency — Mean Arithmetic Mean (AM): Sum of all values divided by number of values. - Direct Method: Mean = Σx / n - Short-cut (Assumed Mean): Mean = A + (Σd/n), where d = x − A - Step…
3. Measures of Dispersion — What is Dispersion? Dispersion measures how spread out data values are around the central tendency. A low dispersion means values are closely clustered; high dispersion means they…
4. Correlation & Regression — Correlation Correlation measures the strength and direction of the linear relationship between two variables. Types: - Positive correlation: Both variables increase together…
5. Probability Theory — Basic Concepts Sample Space (S): All possible outcomes of an experiment. Event (A): A subset of the sample space. Probability P(A) = n(A) / n(S) where n = number of…
6. Sampling Theory — Census vs Sample Census (Complete Enumeration): Every unit of the population is studied. Accurate but time-consuming and expensive. Sample Survey: Only a portion (sample) is…
7. Index Numbers — What is an Index Number? An index number is a relative measure that shows changes in a variable (or group of variables) over time, compared to a base period. Base period value =…
8. Time Series Analysis — Components of Time Series A time series is a set of observations recorded at successive time intervals. Four Components: 1. Secular Trend (T): Long-term movement (upward or…

Collection & Representation of Data

Collection of Data

Data can be collected as Primary Data (collected first-hand for a specific purpose — surveys, experiments, interviews) or Secondary Data (already collected by someone else — census reports, government publications, journals). Primary data is more accurate but expensive; secondary data is cheaper but may be outdated.

Methods of collection: Direct personal interview, Indirect oral interview, Questionnaire method (mailed or schedule), Local reports, and Published sources.

Classification of Data

Raw data is organised into a frequency distribution by grouping values into classes. Each class has a class limit (lower and upper), class interval (width), mid-value = (lower + upper) / 2, and frequency (count of observations).

Cumulative frequency: Running total of frequencies from the beginning. Relative frequency: individual frequency ÷ total frequency.

Diagrammatic Representation

Ogive (Cumulative Frequency Curve)

Plot cumulative frequencies against upper class boundaries (less-than ogive) or lower boundaries (more-than ogive). The intersection of both ogives gives the median graphically. Quartiles Q1 and Q3 can also be read off the curve.

Key points

• Primary data: collected directly; Secondary data: from existing records
• Class interval must be equal for a valid histogram
• Frequency density = frequency ÷ class width (for histograms with unequal intervals)
• Less-than ogive is plotted against upper class boundaries; more-than ogive against lower
• The median divides the area of the histogram into two equal halves

Frequently asked questions

Is this Statistics & Data Interpretation material free?

Yes — all Statistics & Data Interpretation notes and practice on Siksha Sarovar are completely free.

Is the content available in Hindi?

Yes. Lessons are bilingual (English and Hindi) so you can study in whichever language you are comfortable with.

Which exams does this help with?

It is aligned to SSC CGL Tier II, RBI Grade B, UPSC Statistics, IBPS PO Mains and similar government exams.