Q. Which of the following metrics can be used for evaluating regression models?
i) R Squared
ii) Adjusted R Squared
iii) F Statistics
iv) RMSE / MSE / MAE

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Q. How many coefficients do you need to estimate in a simple linear regression model (One independent variable)?

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Q. In a simple linear regression model (One independent variable), If we change the input variable by 1 unit. How much output variable will change?

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Q. Function used for linear regression in R is __________

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Q. In syntax of linear model lm(formula,data,..), data refers to ______

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Q. In the mathematical Equation of Linear Regression Y = β1 + β2X + ϵ, (β1, β2) refers to __________

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Q. ________ is an incredibly powerful tool for analyzing data.

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Q. The square of the correlation coefficient r 2 will always be positive and is called the ________

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Q. Predicting y for a value of x that’s outside the range of values we actually saw for x in the original data is called ___________

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Q. What is predicting y for a value of x that is within the interval of points that we saw in the original data called?

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Q. Analysis of variance in short form is?

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Q. ________ is a simple approach to supervised learning. It assumes that the dependence of Y on X1, X2, . . . Xp is linear.

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Q. Although it may seem overly simplistic, _______ is extremely useful both conceptually and practically.

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Q. When there are more than one independent variables in the model, then the linear model is termed as _______

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Q. The parameter β0 is termed as intercept term and the parameter β1 is termed as slope parameter. These parameters are usually called as _________

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Q. The sum of squares of the difference between the observations and the line in the horizontal direction in the scatter diagram can be minimized to obtain the estimates is generally called?

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Q. ______ regression method is also known as the ordinary least squares estimation.

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Q. __________ refers to a group of techniques for fitting and studying the straight-line relationship between two variables.

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Q. In order to calculate confidence intervals and hypothesis tests, it is assumed that the errors are independent and normally distributed with mean zero and _______

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Q. What do we do the curvilinear relationship in linear regression?

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