Topic: Stack Overflow hosts an annual survey for developers. The study for 2019 includes almost 90,000 respondents (Stack Overflow, n.d.a).
Problem: Surveys usually contain instructions for participants that direct them to answer to the best of their ability. Inherently, this expectation of honest answers equates to consistent responses. Inconsistency can arise in a variety of ways, how one person interprets the question, versus the next, is one example. Another example is when the answers are multiple-choice, and more than one or none of the choices are appropriate to that respondent. In the study by Stack Overflow (n.d.b), respondents answered questions about employment and employment-related questions inconsistently. Modeling the survey results can present new insight into these inconsistencies
Question: Using a neural network and a random forest model and the Stack Overflow (n.d.b) data, will the survey responses to employment, developer status, and coding as a hobbyist, along with the answers to an open-source sharing question provide sufficient information to predict how the participant responded to the question about their student status?
for data use file attached
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