Minimal number of points for a linear regression
Feb 10, 2023 · What would be a "reasonable" minimal number of observations to look for a trend over time with a linear regression? what about fitting a quadratic model? I work with composite indices of …
Support Vector Regression vs. Linear Regression - Cross Validated
Dec 5, 2023 · Linear regression can use the same kernels used in SVR, and SVR can also use the linear kernel. Given only the coefficients from such models, it would be impossible to distinguish …
regression - What is wrong with extrapolation? - Cross Validated
Jun 19, 2016 · A regression model is often used for extrapolation, i.e. predicting the response to an input which lies outside of the range of the values of the predictor variable used to fit the model. The …
Linear regression R-squared vs slope - Cross Validated
Apr 15, 2021 · " correlation only makes sense if the relationship is indeed linear. Second, the slope of the regression line is proportional to the correlation coefficient: slope = r* (SD of y)/ (SD of x) …
correlation - What is the difference between linear regression on y ...
So, to the answer the question: What is the difference between linear regression on y with x and x with y?, we can say that the interpretation of the regression equation changes when we regress x on y …
How to derive the standard error of linear regression coefficient
another way of thinking about the n-2 df is that it's because we use 2 means to estimate the slope coefficient (the mean of Y and X) df from Wikipedia: "...In general, the degrees of freedom of an …
Linear regression, conditional expectations and expected values
Jun 25, 2016 · In the probability model underlying linear regression, X and Y are random variables. if so, as an example, if Y = obesity and X = age, if we take the conditional expectation E (Y|X=35) …
Rules of thumb for minimum sample size for multiple regression
Would you suggest an alternative rule of thumb for minimum sample size for multiple regression? Alternatively, what alternative strategies would you suggest for determining minimum sample size for …
When should linear regression be called "machine learning"?
Mar 21, 2017 · Linear regression is a technique, while machine learning is a goal that can be achieved through different means and techniques. So regression performance is measured by how close it fits …
Linear Regression For Binary Independent Variables - Interpretation
Jan 18, 2019 · For linear regression, you would code the variables as dummy variables (1/0 for presence/absence) and interpret the predictors as "the presence of this variable increases your …