# Tagged Questions

Questions on (linear or nonlinear) regression, the fitting of functions that best approximate empirical data.

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### Questions about derivation of linear regression.

I had few questions about linear regression derivation. SSE = Sum i=1toN (yi - bo - b1xi)^2 In above example, i simply found values bo and b1 where SSE is minimum by finding partial derivates of ...
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### How is the sum of squares of residuals divided by variance has a chi-square distribution with n-2 degrees of freedom?

I came across this while reading the Linear Regression chapter in Sheldon Ross's Book: So my doubt is that How can I prove that it is a chi-square distribution with degree n-2. I looked up a bit ...
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### Linear regression and standardization

I am trying to use a linear regression to model an expected value Y for an input X. X and Y have a large difference between them, so I was converting to standard (z) score, doing my calculation ...
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### Showing that a linear regression by method of leasts squares exists for any set of $n \geq 2$ points

As part of a project for school I am conducting a statistical study that involves the use of linear regressions on many sets of points. Before being able to apply my results using a computer programme ...
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### what does is mean by 'overfitting' of data?

I have the following equation that is to be estimated: y = a + bA + cB + dC + eF + dG + e and i got 2 other additional variables, fH and gI, that i do not wish to add in.. can i reason this out by ...
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### Fitting two parallel lines to a set of points

In two dimension I have a set of points X = $\{x_1,..., x_N\}$. I want to fit two parallel lines to these points like $l_1$ and $l_2$ $$l_1 = p_1 + \lambda n^\perp$$ $$l_2 = p_2 + \lambda n^\perp$$ ...
Let $\tilde{y}_*$ the prediction for a new observation at level $X = x_*$. Assume that $\sigma^2$ and $\tilde{y}_*$ are independent. Show that \frac{\tilde{y}_* - y_*}{se(\textrm{pred})(\tilde{y}_* ...