Statistics is an important field that forms a strong base for learning data science and computing large volumes of data. Are you looking to build a career in this field? These Statistics Interview Questions will help you prepare for jobs encompassing data science and machine learning by refreshing your memory of key aspects of Statistics […]
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In statistics, covariance and correlation are two mathematical notions. Both phrases are used to describe the relationship between two variables. This blog talks about covariance vs correlation: what’s the difference? Let’s get started! Introduction Covariance and correlation are two mathematical concepts used in statistics. Both terms are used to describe how two variables relate to
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Introduction Statistical analyses serve as the backbone of informed decision-making across various disciplines. One such powerful tool, the Chi-Square Test, holds a key position in the realm of statistics. Whether you’re a student delving into research or a professional navigating data-driven insights, understanding the Chi-Square Test is essential. Definition and Significance The Chi-Square Test is
Contributed by: P. Renukadevi Introduction Descriptive Statistics Measure of Central Tendency Measure of dispersion Inferential Statistics Steps in Hypothesis testing Introduction Statistics is as old as human life. This is evident from the data that was collected by kings and their ministers on the population of their kingdom, the area of cultivation, the volume of products,
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Contributed by: Venkat M LinkedIn Profile: https://www.linkedin.com/in/venkat-murali-3753bab/ What is Distribution? The distribution of a statistical dataset is the spread of the data which shows all possible values or intervals of the data and how they occur. A distribution is simply a collection of data or scores on a variable. Usually, these scores are arranged in
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What is Mean Squared Error? In Statistics, Mean Squared Error (MSE) is defined as Mean or Average of the square of the difference between actual and estimated values. Contributed by: Swati Deval To understand it better, let us take an example of actual demand and forecasted demand for a brand of ice creams in a
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Contributed by: Sreekanth Tadakaluru LinkedIn Profile: https://www.linkedin.com/in/sreekanth-tadakaluru-3301649b/ First, the only certainty is that there is no certainty. Second, every decision as a consequence is a matter of weighing probabilities. Third, despite uncertainty, we must decide and we must act. And lastly, we need to judge decisions not only on the results but how those decisions
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