In data analysis, we make use of a lot of theory, whether we like to admit it or not. In a traditional statistical training, things like the central limit theorem and the law of large numbers (and their many variations) are deeply baked into our heads. I probably use the central limit theorem everyday in my work, sometimes for the better, and sometimes for the worse. Even if I’m not directly applying a Normal approximation, knowledge of the central limit theorem will often guide my thinking and help me to decide what to do in a given data analytic situation.
torsdag 13 december 2018
The Role of Theory in Data Analysis
Simply Statistics:
In data analysis, we make use of a lot of theory, whether we like to admit it or not. In a traditional statistical training, things like the central limit theorem and the law of large numbers (and their many variations) are deeply baked into our heads. I probably use the central limit theorem everyday in my work, sometimes for the better, and sometimes for the worse. Even if I’m not directly applying a Normal approximation, knowledge of the central limit theorem will often guide my thinking and help me to decide what to do in a given data analytic situation.
In data analysis, we make use of a lot of theory, whether we like to admit it or not. In a traditional statistical training, things like the central limit theorem and the law of large numbers (and their many variations) are deeply baked into our heads. I probably use the central limit theorem everyday in my work, sometimes for the better, and sometimes for the worse. Even if I’m not directly applying a Normal approximation, knowledge of the central limit theorem will often guide my thinking and help me to decide what to do in a given data analytic situation.