Data can be classified into two main types:Qualitative Data (Categorical Data):This type of data represents categories or labels, not numbers. It can be divided into two subtypes: Nominal Data: Categories with no order (e.g., gender, colors, eye color). Ordinal Data: Categories with a meaningful order or rank (e.g., satisfaction levels like satisfied, neutral, dissatisfied). Quantitative Data (Numerical Data):This type of data deals with numbers and can be used for calculations. It includes two subtypes: Interval Data: Numeric data with equal intervals but no true zero (e.g., temperature in Celsius). Ratio Data: Numeric data with a true zero, allowing all mathematical operations (e.g., weight, height, age). Other Important Data Types Discrete Data:Data that can be counted and takes only whole numbers. Examples: Number of students in a class, number of cars in a parking lot. Continuous Data:Data that can be measured and can take any value within a range. Examples: Height, weight, temperature, or time. Binary Data:Data with only two possible outcomes, such as true/false, yes/no, or 0/1. Examples: Whether a person is present or absent, on or off, pass or fail. Time Series Data:Data that is recorded at regular time intervals. Examples: Stock market prices, daily rainfall, or hourly temperature readings. Spatial Data:Data that has a geographical component, meaning it represents a location on a map or in space. Examples: GPS coordinates, location of schools, or earthquake epicenters.

We have two types of data the first one is qualitative data it is also know as categorical data in this data no numbers are used in this you can put nominal or ordinal scale of data and the other is quantitative data it is also called numerical data it includes only numbers and it also include intervals and ratios. We can apply wide variety of arithmetic operations. DISCREET DATA: A type of data which can be counted with integers. They have equal gap. CONTINOUS DATA: A type of data which can be written in range. It is a measurable data. BINARY DATA: A type data which can either be true or false or yes or know or 0,1 . TIME SERIES DATA: The data points collected or recorded at regular time interval. Examples are : stock market data , recording rain fall , measuring temperature. SPATIAL DATA: The data that has a geographical or spatial component.

Level/Scale of measurement Types of Measurement Nominal, Ordinal, Interval, and Ratio Difference b/w Qualitative and Quantitative Data encode Discreet, Continous, Binary, Time series, and Spatial Data

Scales of Measurement and its types, Data types such as Quantitative vs Qualitative, Data encoding, Discrete vs continious data, Time series data, Spatial Data

qualitative, quantitative, continuous, time series

We have two types of data the first one is qualitative data it is also know as categorical data in this data no numbers are used in this you can put nominal or ordinal scale of data and the other is quantitative data it is also called numerical data it includes only numbers and it also include intervals and ratios. We can apply wide variety of arithmetic operations.DISCREET DATA: A type of data which can be counted with integers. They have equal gap.CONTINOUS DATA: A type of data which can be written in range. It is a measurable data.BINARY DATA: A type data which can either be true or false or yes or know or 0,1 .TIME SERIES DATA: The data points collected or recorded at regular time interval. Examples are : stock market data , recording rain fall , measuring temperature.SPATIAL DATA: The data that has a geographical or spatial component.

catagorical numeric binary dicrete continous binary time series saptial

scaling ka concept clear hogya asy hi baki sab step by stpe smj araha hai ....

baba g the great

Ammaar bhai thankyou so much aap ne eik din mai itna koch sikhaa diya stats ka jitna mai ne university mai nai sikha tha(statistics ke course mai) mujhe tu even ke data ki types tuk ka nai pta tha but aap ne hur cheez itne asaan tarike se btaai ke foran samjh lag gai Thankyou again.