Is Statistics Required for Machine Learning?

What is Statistics?

Statistics is a branch of mathematics that is used for comparing and analyzing various data points and the numbers associated with them. It also includes the study of numbers and drawing out insights from those numbers. Some of the statistical measures include average, median, mode, variance, standard deviation, correlation, regression, etc. Some of these help in analyzing single sets of data while others are used in comparing two or more sets of data and then making a comparative analysis in the form of trends and patterns. Often these tools are also brought into play when it comes to predicting future numbers.

What is Machine Learning?

Machine Learning is the application of artificial intelligence where the systems are programmed to perform a specific set of tasks. The computers are programmed to function automatically depending on the various scenarios and come up with the required results. It enables the analysis of huge data for drawing out various business insights.

Also, it makes the sorting and analysis of data quick and easy as the automation is brought into play with the help of machine learning. It is a really powerful tool in this data-driven world of today. It collects data from various sources as given by the algorithm, prepares it for analysis and then evaluates this data for bringing out insights and also throws light on various performance indicators in the form of patterns and trends.

Statistics and Machine Learning

Both Statistics and Machine Learning deal with the analysis of data therefore one could guess that the two areas are interrelated. Various statistical methods are used to transform raw data and bring out various results. Many believe that knowing Statistics is a prerequisite for understanding Machine Learning. Statistics is important as the data sets have to be created which can be easily made if one has prior knowledge of Statistics. Also, with the help of statistics, the observations are transformed and put to good use.

Machine Learning has a deep relation with Statistics and the elements of statistics such as the collection of data, classification, and sorting of data, analysis of data, etc. Predictive modeling can be done by someone who at least has a basic understanding of Statistics. Machine learning is also known as “Applied Statistics” as it practically uses various statistical theories and principles to drive growth and various results.

Data analysis is important for machine learning and statistics is an art of handling data. It is the primary skill that drives machine learning algorithms. Statistics plays a very important role when it comes to machine learning. One needs to know about the various parameters on which the data shall be analyzed to bring out desired results.

Methods such as Correlation and Regression are often used to compare various sets of data and these tools are built into algorithms with the help of machine learning so that these numbers of comparison can be automatically calculated and a comparative study can be made based on these numbers. Learning Statistics before getting into machine learning is the best way to go about it. Various Machine Learning training will also give you an idea about statistics and how it is applied to Machine Learning.

Machine Learning and Statistics are two parts of the same coin. Machine Learning makes use of statistics for sanitizing data and on the other hand, Statistics is given a practical shape and is made applicable with the help of machine learning. Therefore, it becomes easy to conclude that one must have at least a basic understanding of statistics to understand the aspects of Machine Learning.

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