The course gives a general understanding of using MS Excel in data analysis, hypothesis testing, and time-series analysis. This training is aimed to the understanding of main statistic methods, their step-by-step implementation, and interpretation of obtained results, rather than memorizing formulae or definitions. Participants will be provided with practical problems for decision making.
12 hours
English
Online
To be determined
Usually we know how to take a list of numbers, order them from least to greatest and find the mean, which are simple statistical tools. Building charts, analyzing structure of data and current trends is also a valuable ability. All these usually enhance understanding of the company's actual conditions. However, it is not enough for making proper management decisions or forecast future financial results.
For example, regression analysis is the estimation of the ratio between two or more variables. The two primary uses for regression in business are forecasting and optimization. Regression helps managers and business owners forecast future conditions, lend quantitative support to managers' judgement, point out flaws in management thinking and provide new insights that can help company decision makers move their businesses toward a more profitable future.
Hypothesis testing helps to analyze the effect of one factor on another by exploring the relationship's statistical significance. In a business world, a hypothesis test may be used to explain how much an increase in labor affects productivity or whether the current marketing campaign really boosted sales of the company products. It allows managers to examine causes and effects before making a crucial management decision.
So, when properly used, statistical methods make the decision-making process much easier. However, the application of statistics is both an art and a science and should not be used as the sole basis for making decisions. When interpreting the results of statistical analysis, exercise judgment based on your own real-life experience and other qualitative factors that are not incorporated into the mathematical model.
To provide the audience the understanding that the decision making process should be based on data analysis, to form skills in the use of MS Excel for data processing, analysis, hypothesis testing, and time-series analysis.
