Learn Statistics

  ✅ 1. What is a Probability Distribution? A probability distribution describes how probabilities are distributed over the values of a random variable . Random Variable : A variable whose values are outcomes of a random phenomenon. 🧮 2. Types of Probability Distributions Type Description GIS Example Discrete           Takes countable values  Number of landslides per year in a          valley Continuous          Takes infinite values over an                 interval Rainfall (mm), elevation, temperature  📌 Discrete Probability Distributions 🎯 3. Binomial Distribution ✅ Definition : Used when an experiment is repeated n times , and each trial has two outcomes : success or failure. ✅ Conditions : Fixed number of trials (n) Only two possible outcomes per trial (success/failure) Constant probability of success (p) Trials are in...

✅ 1. What is Probability? Definition : Probability is the numerical measure of the likelihood that a particular event will happen. Relevance to GIS : Helps in risk mapping , spatial modeling , disaster prediction , land-use forecasting , and uncertainty analysis in geospatial data. 🧠 2. Key Concepts and Terminology Term Description GIS Example Experiment A process that generates data Mapping landslide zones in a valley Sample Space (S) All possible outcomes {High risk, Medium risk, Low risk} zones Event (E) Specific outcome or a group of outcomes E: “Zone is high risk” 🔢 3. Basic Probability Formula P ( E ) = Number of favorable outcomes Total number of outcomes P(E) = \frac{\text{Number of favorable outcomes}}{\text{Total number of outcomes}} P ( E ) = Total number of outcomes Number of favorable outcomes ​ 📍  Example : You analyze 100 buildings in a flood-prone area. 25 buildings are in high-risk zones. ...

  Lets dive into the world of sets —a fundamental concept in mathematics that plays an important role in many GIS operations. Sets are not something from basic maths only but they’re also foundational in spatial data analysis , query-building, overlay operations, and more. So understanding sets isn’t just an academic exercise—it’s a skill that improves our ability to think and work spatially in GIS. 🔢 What Is a Set? A set is simply a collection of distinct objects , considered as a whole. These objects are called elements or members of the set. We usually write sets using curly brackets { } . For example: A = {2, 4, 6, 8} means set A contains the elements 2, 4, 6, and 8. Sets are unordered and do not contain duplicate items. 🧰 Common Set Terminologies Here are some basic terms you need to know: Element : An object in a set (e.g., 4 is an element of A) Subset : A set where all elements are also in another set (e.g., B = {4, 6} is a subset of A) Universal Set (U) :...

Raw spatial data—no matter how accurate—is rarely ready for direct use. Often, it needs to be processed, cleaned, corrected, converted, or reclassified to serve our mapping or analytical goals. This is where data analysis and transformation become essential. Whether you're working with satellite images, population data, or flood zones, understanding how to manipulate and interpret spatial data properly is a fundamental skill in GIS. 🔧 What is Data Transformation in GIS? Let’s start by understanding what we mean by data transformation in a GIS context. Data transformation refers to the process of converting raw spatial or attribute data into a format that is suitable for analysis or visualization . This can include changing the coordinate system , format , scale , data type , or even reclassifying values. Some common examples of data transformation in GIS include: Converting vector data (like points) into raster format (like pixels) and vice versa Changing a dataset...

 Geographic Information Systems (GIS) is all about capturing, analysing, and interpreting spatial data. But here’s the thing: without Statistics , GIS is like a map without a compass. Statistics help us make sense of the numbers behind the maps and drive smart, data-backed decisions. 📌 Why Learn Statistics in GIS? Before diving into formulas and charts, let’s answer the big question: Why is Statistics important in GIS? It helps summarize complex spatial data. It allows us to compare and test patterns across regions. It’s crucial for decision-making in planning, disaster management, environmental monitoring, and more. It turns raw data into actionable insights. 🔍 Types of Data in GIS Understanding your data is the first step in any statistical analysis. In GIS, we deal with two broad types: 1. Quantitative vs Qualitative Data Quantitative : Numeric values (e.g., population, elevation). Qualitative : Categories or labels (e.g., land use types, soil classe...