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Table Of Contents
Python in Excel for Data Analytics
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https://packt.link/EarlyAccessCommunity
Statistical inference is the point where analysis shifts from describing what happened to assessing how confident we can be in those results. In earlier chapters, you used exploratory data analysis (EDA) and visualization to spot patterns in the data. Those approaches help surface interesting questions, but they do not tell you how much weight to place on what you see. A bar chart might suggest one group outperforms another, but it cannot tell you whether that difference would persist in a new sample or if it is simply due to random variation.
In this chapter, you will use Python in Excel to run formal statistical tests that address these questions directly. Rather than relying on the Analysis ToolPak or manual formula construction, you will write Python code using libraries such as SciPy (specifically its scipy.stats module) and statsmodels, which are designed for statistical inference. These packages provide...