Efficient computation of statistical measures using C programming

Accurate computation of statistical measures such as mean, median, mode, variance, and standard deviation is fundamental to data analysis and decision making. Many traditional approaches rely on manual calculations or high-level languages like R and Python, which may not be applicable or feasible in resource-constrained environments or for educational reasons. In this paper, we present a C language implementation capable of calculating central tendency and dispersion measures on a dataset. The program is implemented to take user input dynamically, using loops and functions present results for maximum computational efficiency. A dataset is analyzed using Python to compare the statistical results with those obtained from the C programs. We compared the execution times of Excel and C for large datasets. The results, measured in seconds, show that C is significantly faster than Excel for big data.