Congratulations, we have now learned some essential skills for making various plots that visualize the distribution of data. We discussed key statistics related to the central tendency of data by calculating the standard deviation, mean, median, and mode of a series of data values. We looked at normal distributions and how data values can be skewed positively or negatively. When data has symmetry, it becomes easier to work with some algorithms found in predictive analytics. We reviewed patterns and outliers that are common when working with datasets, along with how to use a box plot chart to visualize outliers.
We discussed best practices and tips for working with geospatial data, along with how it can be used to help to tell a story with data. Finally, we discussed the difference between correlation versus causation along with the importance of the correlation coefficient, so you can understand the relationships between two variables/series of data values.
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