Data Scientist Mock Interview
Practice 30 Data Scientist interview questions covering machine learning, statistical modeling, and technical problem-solving.
Question 27 of 30
Can you discuss some of the weaknesses of a linear analysis model?
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William Swansen has worked in the employment assistance realm since 2007. He is an author, job search strategist, and career advisor who helps individuals worldwide and in various professions to find their ideal careers.
The interviewer is asking another technical question, but this time in a back-handed manner. By asking you to discuss the negative aspects of the topic, they anticipate that you will demonstrate your knowledge of the topic by providing both the negative and positive aspects. Be sure to stay as positive as possible when you answer this question. Being negative will reflect badly on you, even though you were asked to discuss the shortcomings.
William Swansen has worked in the employment assistance realm since 2007. He is an author, job search strategist, and career advisor who helps individuals worldwide and in various professions to find their ideal careers.
"While it is an effective methodology, there are also several drawbacks to a linear analysis model. One issue is that the linear analysis model makes strong assumptions that may not apply to the application used. Also, there is an assumption of a linear relationship, normality between the variables, minimal multicollinearity, and homoscedasticity. Finally, a linear model cannot be used for discrete or binary outcomes. As long as you avoid these pitfalls, the linear analysis model can be very useful to a data scientist."
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