Therefore a dataset has no mode, if no number is repeated or if no category is the same. The mode is the value or category that occurs most often within the data. The mean is computed by the sum of all values, divided by the number of values. Central tendency determines the tendency for the values of your data to cluster around its mean, mode, or median. The mean is simply the average and considered the most reliable measure of central tendency for making assumptions about a population from a single sample. These are also called the “Central Tendency.” These are just three different kinds of “averages” and certainly the most popular ones. In statistics we have to deal with the mean, mode and the median. Unimodal means that there is only one peak. You can see on the picture that the distribution is bell-shaped, which simply means that it is not heavily peaked. It should look like the distribution on the picture below:

In a perfect normal distribution, each side is an exact mirror of the other. This basically means that, if your data is not normally distributed, you need to be very careful what statistical tests you apply to it since they could lead to wrong conclusions.Ī normal distribution is given if your data is symmetrical, bell-shaped, centered and unimodal. Inferential statistics and the calculation of probabilities require that a normal distribution is given. It is sometimes called the “bell curve” or the “Gaussian curve.” It basically describes how large samples of data look like when they are plotted. The normal distribution is one of the most important concepts in statistics since nearly all statistical tests require normally distributed data. Inferential statistics: Inferential statistics are produced by more complex mathematical calculations, and allow us to infer trends and make assumptions and predictions about a population based on a study of a sample taken from it. Descriptive Statistics: In descriptive statistics, you are describing, presenting, summarizing and organizing your data (population), either through numerical calculations or graphs or tables.Ģ. Within statistics, there are two main categories:ġ. Statistics is a branch of mathematics that deals with collecting, interpreting, organization and interpretation of data. Take your time and carefully run descriptive statistics and make sure that the data meets the requirements to do further analysis.īut first of all, we should go over what statistics really is: A lot of people skip this part and therefore lose a lot of valuable insights about their data, which often leads to wrong conclusions. Introduction to Descriptive Statistics for Machine Learningĭoing a descriptive statistical analysis of your dataset is absolutely crucial.

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