Probability and Statistics  has always been a tough subject to study and the students are always struggling with a fear factor associated with mathematics. Although practice makes a man perfect holds true in many typical tasks it is also valid for study as well. Mathematics has been too complicated for majority of students. But mathematics as primary subject in core and new engineering course is compulsory in world-wide engineering education. In engineering there are several branches such as computer science engineering, electrical engineering, mechanical engineering, electronics and communication engineering, and civil engineering and each branch has different study set focused on the significance of mathematics. 

Probability is used in civil engineering to measure and manage risks from uncertain factors. Engineers use it to predict structural loads, design safe buildings and bridges, evaluate soil and ground stability, and forecast floods or extreme weather. 

Probability distributions are essential in civil engineering to model natural randomness and data uncertainties. Engineers use them to predict extreme loads, assess material strengths, and calculate safety risks for structures, water systems, and soils .

Sampling and estimation in civil engineering allow professionals to infer material properties, evaluate structural safety, and forecast project costs. Engineers use random samples to test soil, concrete, and steel strength, and apply statistical or mathematical estimation to predict overall project expenses, material quantities, and structural reliability. [1, 2, 3, 4, 5] 

Statistics summarizes test data, control manufacturing quality, analyze material properties, and evaluate experimental errors. They turn raw laboratory measurements into clear averages, spreads, and graphs for better design decisions. 

Curve fitting and correlation analysis are fundamental tools in engineering for understanding relationships between variables, predicting future behavior, and optimizing designs. Curve fitting helps find mathematical functions that best describe data, while correlation analysis quantifies the strength and direction of relationships between variables.