# What is Ols: Definition and 17 Discussions

Oleśnica (pronounced Oleshnitza [ɔlɛɕˈɲit͡sa]; German: Oels; Silesian: Ôleśnica) is a town in Lower Silesian Voivodeship, in south-western Poland, within the Wrocław metropolitan area. It is the administrative seat of Oleśnica County and also of the rural district of Gmina Oleśnica, although it is not part of the territory of the latter, the town being an urban gmina in its own right.
The town is famed for its large 16th-century castle, which has previously been the seat of several dukes and lords. The castle's inner courtyard arcades, a masterpiece of Renaissance architecture, are iconic in the region.

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1. ### I Nonlinear least squares vs OLS

hello, I understand that the method of ordinary least squares (OLS) is about finding the coefficients that minimize the sum ##\Sigma (y_{observed} -g(X))^2## where ##g(X)## is the statistical model chosen to fit the data. Beside OLS, there clearly other coefficient estimation methods (MLE...
2. ### I Linear Regression and OLS

Hello, Simple linear regression aims at finding the slope and intercept of the best-fit line to for a pair of ##X## and ##Y## variables. In general, the optimal intercept and slope are found using OLS. However, I learned that "O" means ordinary and there are other types of least square...
3. ### MHB Levels of Measurement, Basic OLS Regression Questions

Hello soon to be saviors, 😊I have two really simple questions that I have already answered but the teacher wants more info. I am really stumped and I am not looking for the answers so much as an explanation on how to better answer the questions. I will copy and paste the problems and my answers...
4. ### A Using standard deviation values as independent variables

Hey. I am planning on doing some research, where I predict a change based on different types of risk. The question is simple. Can I use values of standard deviation as independent variables in a linear regression analysis (OLS)? The standard deviation values over time will be calculated in...
5. ### A Robustness of time series analysis

I have a time series model constructed by using ordinary least square (linear). I am supposed to provide some general comments on how one would improve the robustness of the analysis of a time series model (in general). Are there any general advice apart from expanding data, making it more...
6. ### A Indirect effect and spuriousity

Say one has a regression result (ols) with significant coefficients for all independent variables. Then a new variable (Z) is added. This new variable is either something that reveals a spurious relationship among one of the initially included variables (x) and the dependent variable (y), or...
7. ### A Does centering variables for regression always result in unchanged coefficients?

I am studying mean-centering for multiple linear regression (ols). Specifically I'm talking about the situation when there is interaction. When centering variables for a regression analysis, my literature tells me that the coefficients do not change? But when there is some sort of interaction...
8. ### A Centering variables, linear regression

I am working with multiple regression with two independent variables, and interaction between them. the expression is: y = b1x1 + b2x2 and b3x1x2 The question is: does one center both independent variables at the same time, when checking for the significance of the effect of the independent...
9. ### The linear in linear least squares regression

It is my understanding that you can use linear least squares to fit a plethora of different functions (quadratic, cubic, quartic etc). The requirement of linearity applies to the coefficients (i.e B in (y-Bx)^2). It seems to me that I can find a solution such that a coefficient b_i^2=c_i, in...
10. ### MHB OLS standard error that corrects for autocorrelation but not heteroskedasticity

Question: By mapping the OLS regression into the GMM framework, write the formula for the standard error of the OLS regression coefficients that corrects for autocorrelation but *not* heteroskedasticity. Furthermore, show that in this case, the conventional standard errors are OK if the $x$'s...
11. ### How to Calculate OLS Estimator with Given β0 in 50 Data Points?

Homework Statement ΣiYi = 500; ΣiXi = 150; ΣiYi2 = 17000; ΣiXi2 = 4000; ΣiXiYi = 8000; n = 50. β0 = 3. Derive formula for OLS estimator of β1 and find estimateHomework Equations I'm new to OLS and I'm not sure where to go from: Σ(Yi - 3 - b1Xi)^2 I was able to walk through the steps in my...
12. ### OLS Estimator, derivation sigmahat(beta0hat)

Good day, in the lectures of emperical economic research of my uni, we got to the topic of Linear Regression with one regressor. There I encountered upon: {\hat{\sigma }_{\hat{\beta }_{0 }}}^{2 }=\frac{1 }{n }\cdot \frac{\text{var }{\left( {\left[ 1 -{\left( \frac{\mu _{x }}{E {\left( {X _{i...
13. ### Having trouble understanding variance of OLS estimator

So in computing the variance-covariance matrix for β-hat in an OLS model, we arrive at VarCov(β-hat)=(σ_ε)^2E{[X'X]^-1} However, I'm incredulous as to how X is considered non-stochastic and how we can just eliminate the expectation sign and have VarCov(β-hat)=(σ_ε)^2[X'X]^-1 I'm...
14. ### How to OLS several lines at once?

Hello PhysicsForums.com! I've got several sets of data that are all intended to represent the same ideal data set. I need to fit a regression to said sets of data - but have no idea of how to go about it. All multiple-regression literature I can find reads to the tune of: given...
15. ### OLS regression - using an assumption as the proof?

Hi, My question is about a common procedure used to find minimum and maximum values of a function. In many problems we find the first derivative of a function and then equate it to zero. I understand the use of this method when one is trying to find the minimum or maximum value of the...
16. ### Assumptions behind the OLS regression model?

Hi, In many statistics textbooks I read the following text: “A models based on ordinary linear regression equation models Y, the dependent variable, as a normal random variable, whose mean is linear function of the predictors, b0 + b1*X1 + ... , and whose variance is constant. While...
17. ### Difference of OLS and LAD

Hi I'mwondering what's the difference between least squares method with least absolute deviation method. Assume we have y=ax+b+s where s isdeviation. Is the step to calculate even a and b is different. I read that those two methods are almost the same but hardly found a real good explanation...