From the course: Python in Excel: Data Outputs in Custom Data Visualizations and Algorithms

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Leveraging Excel Solver for logistic regression

Leveraging Excel Solver for logistic regression

From the course: Python in Excel: Data Outputs in Custom Data Visualizations and Algorithms

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Leveraging Excel Solver for logistic regression

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- [Instructor] As we saw in the previous lesson, regression models enable us to find trends in data. Sometimes a linear regression model is a good fit for data points, and sometimes it isn't, like what we see in this scatterplot. Logistic regression models display best fit lines as S shaped curves instead. Classic binomial logistic regression models have two possible actual outcomes. Zero represents one outcome like loss or the response, no. Conversely, one represents another outcome like a winner, yes. The orange line we see on this logistic regression chart represents the predicted probabilities for each X value. Unfortunately, in Excel, we can't directly predict the outcomes in the same way we would for linear regression by calculating the regression coefficients directly through formulas or the data analysis added. In the logistic regression tab, we see the predicted probabilities in column G, which range from zero to one as an open interval. The predictive probabilities from a…

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