Week 5 - BALT 4363 - Probability and Statistics for Data Science

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Probability and Statistics for Data Science 

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This week I decided to write my blog on the chapter we went over. I absolutely love everything to do with data science. However, there are about three main points that are my favorite. Visualizations top the chart, then analyzing statistics, and then probability. During this chapter, we went over both probability and statistics, so I loved the reading. 

The first topic covered was descriptive statistics. Some common descriptive statistics are mean, median, modem standard deviation, etc. These are statistics that we have seen since a young age, and continue to be a prominent statistic as we grow older and get in higher levels of math, in either school or the workplace. All of these statistics are highly important and they can all give us important information. Such as average age of employees at your company, or the median value of a certain dataset.

We then move on to probability. Probability distributions basically describe the chance of a certain outcome. Some common probability distributions include the normal, binomial and Poisson distributions. Normal distribution is typically used to describe something natural, such as the age or height of people. Using visualizations, we can see a possible trend in some data, leading to us being able to potentially have a prediction of a height or age that a certain group of people will reach. 

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