spatial data is a data of space/geographical data e.g. maps, location or GIS.

Data and Different Types of Data in Statistics

Data and Types of Data

In this serieses i learn level of mearsurment .nominal (like a name virable) these are 4 types 1. nominal ( name of variable ) 2. ordinal (name + ordinal variable) 3. interval. (name+ ordered+ propotional interval between variable) 4. ratio .name+ordered+ propostionate+ interval+ between variable can accoumodate absollute zero then next is QUALITATIVE , QUANTATIVE. qualitative in qutitity , catagorical data, no numbar used, nominal scal, ordinal scale, and quantitve in data of quanitity and these are nomannal data ,only numbar used, interval/ ratio scale , arthimattic like(-,+<,+ ) DISCREET DATA . mostly these type of data in forme of interger like counting,.. COUNTINOUSE DATA. these data measurable counting like hight, weight, tempreture time like etc, BINERY DATA . like selected like yes, no / true , fals/ , coinne task in the air some posibaality out come tail , head / light off ,on and also we learn TIME SERIES DATA . over the time data points collected /recorded at regular time interval example stock market, mountrly rainfall , tempreture DATA SPATIAL . about space data and geographical data

I learned statistics, data lifecycle, levels of measurement, qualitative and quantitative data, discrete, continuous and binary data,time series and spatial data.

I learned introduction of statistics its important scales and level of measurments,quantitative vs qualitative , differences between discrete ,countinous and binary Data. time series data and spatial data

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