Statistical Concepts and Uses: descriptive vs. inferential statistics, population, survey, sample, random variables, data types, forecasting, Data Collection & Samplings: - published vs. survey data, Data Collection: Real (Secondary; and Primary: sampling). Hypothesis: assumptions, null vs. alternative hypothesis, hypothesis use, tests and effect, type-I and II errors, Inference &Estimation: statistical inference, tests of 1-sample vs. 2 sample tests, confidence intervals, p-value, precision planning, and significance level, and analyze & interpret results. Probability Distributions: probability concept & theories, set theories, applications of probability laws, quantitative decisions about a process, types of probability distributions, Forecasting: concept, types, steps and elements of good forecast, forecasting techniques like simple & weighted moving averages, linear regression, exponential smoothing, and accuracy tests & TS. Statistical Software: analytical and graphical software, specific analysis using software like SPSS.