Variables in Statistics & Measurement Scales | Nominal, Ordinal, Interval, Ratio Explained in hindi

16 May 2025 · 7 min
7:24

In this Hindi tutorial, Akansha Yadav introduces the fundamental concepts of variables and measurement scales used in statistics. She begins by distinguishing the two broad categories of variables—discrete (countable) and continuous (uncountable)—explaining how each is described by a probability mass function (PMF) or a probability density function (PDF) and noting that discrete variables have positive probabilities for single values while continuous variables assign zero probability to exact points and only to intervals. The lecture then moves to measurement scales, emphasizing that the scale chosen must match the variable type. She defines the four classic scales with concrete examples: 1. Nominal scale – categorical, qualitative data such as gender or religion. 2. Ordinal scale – ordered categories or rankings like class positions, race finishes, or customer satisfaction levels. 3. Interval scale – numeric values with equal intervals but no true zero, exemplified by temperature in Celsius/Fahrenheit. 4. Ratio scale – numeric values with equal intervals and a meaningful zero point, illustrated by time, length, weight, etc. Throughout, she stresses the importance of aligning variable types with the appropriate measurement scale for correct statistical analysis, and concludes with a brief recap encouraging further learning.

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