The aim of this course is to provide students with the fundamental concepts of statistics, methods of data collection and organization, measures of central tendency and variability, the basic principles of probability theory, and probability distributions. Within the scope of the course, it is intended to improve students’ statistical thinking skills and enable them to analyze and interpret data effectively.

This course aims to provide students with the fundamental concepts of statistics, data analysis methods, and the basic principles of probability theory. Within the scope of the course, fundamental concepts such as population, sample, parameter, statistical unit, and types of measurement scales are introduced, along with methods for organizing and graphically presenting data. In addition, measures of central tendency and resistant averages for simple, frequency, and grouped data series are examined. The course further covers measures of variability, including range, interquartile range, mean absolute deviation, variance, standard deviation, and coefficient of variation. In the probability section, topics such as experiments, sample space, counting rules, conditional probability, dependent and independent events, as well as the addition and multiplication rules of probability are discussed. Furthermore, the concept of random variables, discrete and continuous probability distributions, Bernoulli, Binomial, and Poisson distributions, together with expected value and variance calculations, are analyzed. In the final part of the course, continuous probability distributions such as the Uniform and Normal distributions are covered, with the aim of improving students’ statistical analysis, interpretation, and decision-making skills.