Yes, both the slope and intercept can be negative in a linear regression model. A negative slope means that as the independent variable increases, the dependent variable decreases. A negative intercept means that the predicted value of the dependent variable starts at a value below zero.
Keep in mind that linear regression assumes a linear relationship between the variables. If the relationship is not linear, the interpretation of slope and intercept may not be meaningful.
Remember that these questions and answers are intended to provide a basic understanding of slope and intercept in data science interviews. Depending on the specific job role and company, the questions and level of detail required may vary. Be prepared to dive deeper into the concepts and demonstrate your understanding through real-world examples.
