Statistical Foundation
Statistical reasoning is the framework in which data science is enacted. Having the context and logic of statistics allows data scientists to collect, analyze, and interpret data effectively. This competency includes knowledge of statistical tests, probability, regression analysis, and hypothesis testing.Strong statistical foundations help with making informed decisions based on the data, identifying trends, and predicting future outcomes.
In practice, a data scientist uses statistical methods to make sense of large datasets and to determine the reliability of the conclusions drawn from the data. For example, data scientists might use statistics to evaluate whether a difference in air quality between two regions is more affiliated with differences in nearby pollutants or nearby plant life. This is crucial in fields ranging from business to public health, where strategic decisions, particularly the allocation of limited resources, are often based on data analysis.
Our repository prioritizes curriculum materials which employ and develop foundational statistic skills. Modules which involve statistical foundations can be combined with other educational materials to embellish coursework and may mesh particularly well with courses which are already covering statistics.
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