We start learning statistics. Statistics deals with data, and data is usually represented in a form of table. In this table, we have several rows that are shown on referrals, but we can imagine much more rows and several columns, and each row which is called observation, for example can correspond to some participants of a study, or to some other kind of observation. Each column represents some variables, some property of these observations. Invention Learning variables are also called features, and this table is very large and to get some idea about our data, we can use a different summarization and visualization techniques. First of all, we will discuss descriptive statistics. The word statistics here does not mean that branch of science. It mean just some number that is associated with our data. For example consider a column with age, we can be interested in the average age of participants of our study. To find this average, we can just use arithmetic mean of all numbers that we have in column age in our data set. We can conclude that average age is 31. But this information is not enough to get reasonable understanding of our data. For example, we may be interested also in measures of statistical dispersion of measures of how different our values are. All of them are near the average value or there is a wide range of ways. To answer this question, we can use another descriptive statistics so-called standard deviation. We can find a standard deviation by formulas that we will discuss and get to that it is 22. After that, we can report for example that the age of our participants is 31 plus or minus 22. It gives information about the average value, and it gives information about an error or deviation from these average value. So the range of the participants of our study. These two are example of descriptive statistics. In other ways and to get information about the data is visualization. For example, we can draw a histogram of our variable age, and using this histogram, we can get an idea of the distribution of ages of the participants of our study, and we also can communicate the same thing to somebody else. Visualizations are important technique in understanding of the data. At this week, first of all, we will discuss the connection between statistics and probability theory, connection between random variables that we studied in probability theory and our data. We will discuss different kinds of data and different kinds of descriptive statistics. Descriptive statistics are measures of central tendency which measure in some sense typical objects in our data set. There are mean, median, mode, and measures of statistical dispersion like variance, standard deviation, or inter-quartile range. We will also discuss quartiles themselves and they degeneralization quantiles. We will discuss how to visualize distributions of continuous and categorical variables so using histograms and bar plots, and finally, we will discuss how to use Python to find descriptive statistics and visualize data.