Questions tagged [sums-of-squares]
sum of squares plays an important role in statistical models based on the normal distribution, like ANOVA.
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Why sum of squares to calculate dispersion [duplicate]
The variance gives an idea of the dispersion of a distribution. To calculate the variance the sum of the difference of each value with the mean, each of these differences squared, is required. The ...
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Sum of squares of xy bigger than sum of squares for x - how can that be?
I followed this tutorial to visualize R squared. First they define the formula to calculate sums of squares:
Then they apply the formula to get sums of squares of ...
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How does type II vs type III ANOVA work when there are more than two categorical predictors?
For a model with two categorical factors in the form:
X = A + B
Type I (used if the factors are balanced) calculates SS for each term in the model sequentially as follows:
SS(A) then
SS(B|A) = SS(A ...
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How to derive the Sum of Square for Latin Square with repetition
I am studying the Latin Square Design with n repetitions from https://online.stat.psu.edu/stat503/lesson/4/4.4
Let say we talk about the repetitions case 3 i.e. we ...
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Partial eta square values summing to greater than 1
I am trying to run a factorial ANOVA analysis with partial effects, but it seems that my partial eta square values are totalling above 1, particularly when I specify my contrast with Type II or Type ...
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How to resolve confusing ANOVA results using type II sums of squares?
Suppose we have the following data from the R package afex:
...
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Do I calculate the loss of a regression on the normalized or denormalized data?
I worked on implementing a simple MLP network, which should guess a numerical value based on different values. Basically it's a regression task. This was a few months ago.
Everything worked fine, the ...
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What is "explained" by the explained/regression sum of squares?
We are in a regression setting. Let's start by defining some notation and terminology.
$y_i$ is observation $i$ of some (response) variable $Y$.
$\hat{y}_i$ is the value of $y_i$ predicted by a ...
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How can you convert sum of squares deviation to an r-squared value?
I would like to calculate the r-squared value for some regressions. The model (its in a GUI) I am using gives me "goodness of fit" in terms of the sum of squares deviation. I am using ...
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Computing sum squared distances without computing center
Given an even number of sample points in a plane, I want to compute the sum of squared distances from the sample center as part of estimating the Rayleigh parameter. One way of doing it is to compute ...
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Cannot understand why total SS＝explained SS+unexplained SS
I cannot understand why total SS＝explained SS+unexplained SS because geometrically the sum of two small squares is not equal to a big square.
I wish someone could explain that to me. Thank you.
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Different results for type I and type II ANOVA
I am performing an ANOVA for a research question. I want to to test whether "Grade", "Nim" and "Tim" has a significant influence on "value". My question is ...
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Is there an interpretation for this identity from sum of squares?
So yesterday my professor wrote the following on the board:
$$\frac{1}{n}\sum_{i = 1}^{n}\left( x_i - \bar{X}\right)^2 = \frac{1}{n}\sum_{i = 1}^{n} x_i^2 - \bar{X}^2$$
where $\bar{X} = \frac{1}{n}\...
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Expected Value for Sum of Squares in Reduced Model
$\newcommand{\ol}[1]{\overline{#1}}\newcommand{\szdp}[1]{\!\left(#1\right)}
\newcommand{\szdb}[1]{\!\left[#1\right]}$I am studying Design and Analysis of Experiments, 2nd Ed., by Dean, Voss, and ...
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cannot reproduce the example for nested anova
I'm working on the example for nested ANOVA from the Handbook of Biological Statistics. Copy-pasteable data can be found at https://www.biostathandbook.com/nestedanova.html and below shows my ...
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What exactly do Anova sums of squares represent in lmer models?
In a lme4::lmer model, the anova function returns an sequential analysis of variance table.
As explained on page 34 of http://...
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Interpretation of default Type III Sums in Squares in R
Many posts (i.e. here and here) discuss how the Type III sums of squares produced by car::Anova() in R
are incorrect or nonsensical under R's default model parameterization, "contr.treatment"...
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How is the matrix of corrected sum of squares and products defined?
In the article Johns, S. "On identifying the population of origin of each observation in a mixture of observations from two normal populations." Technometrics 12.3 (1970): 553-563, the ...
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Summation of terms in survival function giving negative probability
The following expression represents a survival function for a group size (n), where survival is a percentage on a scale of 0 to 100.
$$
p(x) = 100 - \beta(x \cdot x) = 100 - \beta\sum_{i=1}^{n}x_i^2
$$...
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Does Residual Sum of Squares always decreases with an additional independent variable? [duplicate]
^ What the question says. Trying to determine whether this statement is true or false.
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Synonyms of Residual Sum of Squares
As a novice, I'm finding it difficult to learn statistics, partly because there are often many different words for the same thing. When I'm reading about stats, I don't realize that the thing I'm ...
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"Normalized mean squared error" says WHAT?
I know that mean squared error is a public and popular metric to evaluate the efficiency of the model and architecture. Also, it is the tool to evaluate the result in such if, the ...
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Why type III sum of squares is not recommended to use when there is significant interaction?
I did notice that in the following example, I obtained a insignificant main effect for treatment when including interaction, although the treatment is clearly effective.
Any intuitive explanation?
...
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Why calculate Mean Squared Error for Regression?
Once we fit the model to the points why is it necessary to find the mean squared error? What happens if I don't calculate Mean Squared Error?
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Which type of sum of squares corresponds to the partition of variance formula for two-way ANOVA?
Does anyone have a good reference for the formula for type I and type III sum of squares in two-way ANOVA?
I learned the following formula for partition of total sum of squares in two-way ANOVA. Is it ...
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The number of clusters in the K-means and the within-cluster SS
Given a collection of observatons $\{X_i\}_1^N$ and prespecify the number of clusters K. The K-means solves
$$
\underset{\{C_k\}_1^K}{\arg\min} \sum_{k=1}^K \sum_{i \in C_k}|| X_i - \mu_k||^2
$$
where ...
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Conceptual/Math/brainteaser Question: Multiple Linear Regression
This is kind of a brainteaser and I'm struggling to solve it, any ideas on approaching this would be valued:
I thought about using substitution of the different x and z into the third regression ...
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Confused: Why is lme4 changing techniques from Wald F tests to Wald Chisquare?
I've constructed some LMEMs that use dichotomous variables and their interactions as regressors, and I've become confused by the output. When I only assess a single interaction, using the code below (...
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Fitting data to sums of squares of sinusoids
I am given some time series data $(t, y(t))$ sampled at regular intervals $t=0,s,2s,3s,\ldots,1$ for some step size $s$, obtained from a function
$$
y(t) = y(t, \vec A, \vec \delta) = \sum_{i=1}^N ...
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Which type of sums of squares does lm-function in R use?
I ran a two-way ANCOVA in R:
ancova = lm(DV ~ IV1*IV2 + CV1 + CV2 + CV3, data = Data)
summary.aov(ancova)
Anybody know if this uses type III sums of squares?
I ...
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How unbalanced is unbalanced for factorial ANOVA?
Colleagues and I conducted an experiment with participants randomly allocated to each condition using survey software. Unfortunately, the cell sizes ended up being more unbalanced than we anticipated: ...
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Is least squares means (lsmeans) statistical nonsense?
I recently came accross this quote from Brian Ripley, who seems to be well-regarded as a statistician.
"Some of us feel that type III sum of squares and so-called ls-means are statistical ...
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Proof that Regression Sum of Squares and Residual Sum of Squares are independent random variables
Having consulted a number of sources, I still can't find a complete proof that Regression Sum of Squares ($SS_{regression}$) and ($SS_{residual}$) are independent random variables. I'll be doubly ...
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Shortcut for computing RSS at different split point when building regression trees?
I'm coding regression trees from scratch in R. For a given ordered predictor variable, $X$, obviously I have to compute the RSS at each unique ordered value of $X_i$. When moving over to the next ...
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Why contrast in ANOVA has one degree of freedom?
I thought I understood the degree of freedom after reading Wikipedia explanation, but came across the sum of squares for contrasts $\{c_i\}$ $$SS_C = \frac{(\sum_i {c_i \bar{y_i}})^2}{\sum_i c_i^2 /...
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Contrasts in ANOVA - need intuitions to understand its sum of squares and its degree of freedom
I have two questions about contrasts in ANOVA for testing the hypothesis that $\sum_i c_i y_i = 0$.
How is the sum of squares for contrasts $\{c_i\}$, $SS_C = \frac{(\sum_i {c_i \bar{y_i}})^2}{\sum_i ...
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Distribution of the squared length of a multivariate normal vector [duplicate]
Let $\mathbf{X} \sim \mathcal{N}(\mathbf{\mu}, \mathbf{\Sigma})$ be a multivariate Normal variable with $d$ dimensions. I'm interested in the marginal distribution of $\|\mathbf{X}\|^2 = \sum_{i=1}^d ...
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In a PCA setting, is there any relationship with the sum of squares of the scores (t1) with the eigenvalue of that principal component?
When one computes the vector of scores (t1) using the principal component (p1) the data is being projected over the direction of biggest variation. One could measure the distance between the point ...
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What is the lowest sum of squared errors (sse) of a dataset?
Given $X \subset R^d$ a set of data points, $z \in R^d$ a vector, $SSE(X)=\sum_{i=1}^{|X|}||X_i-z||^2$, I wonder what is the best value of $z$ so that $SSE$ is the lowest?
I suspect that $z$ is the ...
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How are terms in SS (corrected sum of squares) independent?
What does the highlighted test mean? How are the terms not independent? Can someone elaborate in detail?
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Source for BIC with residual sum of squares?
Wikipedia states that under certain circumstances, $\mathrm{BIC} $ can be calculated as:
$$\mathrm{BIC} = n \ln(\mathrm{RSS}/n) + k \ln(n),$$
where $\mathrm{RSS}$ is the residual sum of squares. ...
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Kruskal–Wallis one-way analysis of variance is related to what kind of regression?
One-way anova is similar to regular linear regression because both use the F-test which involves sums of squares among other reasons.
Is Kruskal–Wallis one-way analysis of variance similar to some ...
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Difficulty with averaging corrected sample variances of different degrees of freedom:
I have a number of measurement samples of which some have 2 measurements and some have 3. I wish to make the most accurate estimation of population variance I can, and understand that ignoring data ...
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Residual sum of squares in a regression
I understand that in a linear regression model, the residual sum of squares will either remain same or fall with the addition of a new variable.
What if the two models were
$$
I \colon y_i=\...
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Simplifying the Matrix Form of the Solution to Ridge Regression
I'm trying to understand how to obtain the solution to an objective function by solving for the parameter vector $\theta$ in ridge regression. I found an example here from Naomi which takes an example ...
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What is the correct implementation of BIC with residual sum of squares?
BIC is most often calculated by maximizing the log likelihood function. However, it is also possible to calculate BIC with residual sums of squares. This is pretty easy to find online and not an issue ...
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Formula for type III sum of squares of the intercept term in linear multiple regression
assume we have the regression model:
$$Y = b_0 + b_1 x_1 + \dots + b_k x_k + \varepsilon $$
I know the formulas for all type III sum of squares for the regression terms except the formula for SS of ...
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Coefficient of determination relationship?
$R^2 = \frac{SSREG}{SSTOT}$ or $R^2 = 1-\frac{SSRES}{SSTOT}$
If $X$ is the predictor random variable for science SAT
and $Y$ is the predictor random variable science GPA
given by equation $$\hat Y =...
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Sum of Squared Error Chi-Square distribution degree of freedom in Multilinear Regression
In this link it says that $Y$ variables has zero covariance (because covariance matrix has only diagonal terms) which implies they are independent.
Actually in linear regression $Y$ takes its ...
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What is the difference between the residual, lack of fit and pure error In F test for Regression Analysis?
What is the difference between the residual, lack of fit and pure error and how to calculate each of them in ANOVA F test for nonlinear regression?
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