![]() If I weigh myself only once a day, that is probably reasonable. Note, we also assume that each measurement is independent, and uncorrelated with the previous and next measurement. We do not have enough data to determine if it is normal here, but it is worth noting that assumption underlies the analysis. This analysis makes sense if we think my weight fluctuates about some average with a normal distribution of fluctuations. Then, we simply call the mean and std functions of that array inside a formatted string. We start by making an array in a variable called weights. We will extensively use numpy arrays for data analysis. To perform this analysis, we need a computational tool, we will use Python. Let's consider the average and standard deviation of the second weights above. ![]() Each of these has the purpose of extracting information from the data. ![]() There are many kinds of analysis one can do: statistical, regression, integration, etc. It is analysis of data that is helpful, but you have to know what the data is supposed to represent to know if the analysis is helpful. It doesn't really make sense to average the first set, whereas the average of the second set gives you a good idea of how my weight fluctuates on a daily basis.ĭata by itself is not helpful. The first set is data over four decades, while the second set is over four days. Datum is the singular form of data.įor example, here are two sets of data on my weight: It is critical to know something about your data so you understand what analysis may be appropriate. It is usually a set of numerical values that are collected. We will start with some high level thinking about what we mean by data, why we get it, and what we do with it.ĭata are things we measure, assume to be facts, and that we use to learn about the process the data was collected from. Don't worry about what this code means yet, it is an idea I want to get across. You have to use the narrative text in the Markdown cells to explain what you are trying to do, what approximations you have to make to accomplish it. You cannot expect others to read your mind and guess what your intentions were.The code is for a computer, and it represents your attempt to convert some idea in your head into an executable program.Jupyter notebooks are a way to communicate your work. You will be using both code and Markdown cells to document what you are doing, why you are doing it, and what it means. Separate text by blank lines so they appear as "paragraphs" Type some regular text and press C-enter to render it. Now press Enter to go into the cell, or double click in it. The one that says "Code" tells you it is a code cell. You can see it is a code cell at the top in the icons. We are going to change this to a Markdown cell. Remember, by default this will be a code cell. ![]() That will insert a cell above the selected cell. Type print('Hi there') and press C-enter to execute it. This will create a new cell after the cell, and enter it so you can add something. With your cursor on this cell, type Esc-b and then Enter. When on a cell that is rendered, you can use the up and down arrows to move from cell to cell. Now type S-enter (shift-enter) to render the cell and move to the next cell. Type C-enter (Control and enter at the same time) to render the cell.ĭouble click on the cell again. It is written in Markdown, a lightweight text markup language. If you double click on a cell, you can see how it was made. If you click on one you will see a blue bar indicating the scope of the cell. ![]() You can shrink the navigation bar by clicking on the folder icon next to the left of the + symbol.This is probably the best way to access notebooks. You can double click on a notebook here to open it. On the left side is a panel that should show a navigation panel. ![]()
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