![]() It provides us with mathematical tools to update our beliefs about random events in light of seeing new data or evidence about those events. ![]() Bayesian Statistics. Finally, Bayesian statistics is an approach applying probability to statistical problems.The most common technique used for dimensionality reduction is PCA, which essentially creates vector representations of features showing how important they are to the output, i.e., their correlation. When data is insufficient, oversampling duplicates the minority class values to have the same number of examples as the majority class has. If the majority class is overrepresented, undersampling helps select some of the data from it to balance it with the minority class has. Over and Under Sampling that help to balance datasets.The most common in Data Science are a Uniform Distribution that has is concerned with events that are equally likely to occur, a Gaussian, or Normal Distribution where most observations cluster around the central peak (mean) and the probabilities for values further away taper off equally in both directions in a bell curve, and a Poisson Distribution similar to the Gaussian but with an added factor of skewness. Probability Distributions represent the probabilities of all possible values in the experiment.It’s all fairly easy to understand and implement them in code even at the novice level. Statistical features like bias, variance, mean, median, percentiles, and many others are the first stats technique you would apply when exploring a dataset.However, as a beginner data scientist, you can start with 5 basic statistics concepts: Both statistics and probability are separate and complicated fields of mathematics. Statistical methods themselves are dependent on the theory of probability, which allows us to make predictions. With the help of statistical methods, we make estimates for further analysis. Statistics is, in simple terms, the use of mathematics to perform technical analysis of data. Probability and statistics are the basis of Data Science. Introduction To The Basic Business Intelligence Concepts - an insightful article giving an overview of the basic concepts in BI īusiness Intelligence for Dummies -step-by-step guidance through BI technologies īig Data & Business Intelligence - an online course for beginners īusiness Analytics Fundamentals - another introductory course teaching the basic concepts of BI. We recommend you to have a look at the following introductory books to feel more confident in analytics: ![]() However, it is important to have at least dim vision of BI tasks and strategies. In a more complex production environment, there will probably be separate Business Analysts to do insightful interpreting. ![]()
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