# All Questions

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### Where to find a guide to encoding categorical features?

I am facing an ML task with various categorical variables. Some examples include the following: Binary variables (0,1). Multilevel factors that can be ordered (low, medium, high). Multilevel factors ...
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### What does it mean in real-world terms that the Chi-Squared distribution is a special case of the Gamma distribution?

Among other applications, a gamma distribution answers the question: "If the average time (or other quantity) between events is β, what is the probability that x time will elapse before α events occur?...
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### How common is it to train each network independently then train end-to-end in a neural network?

Say that I had 3 autoencoders stacked on each other. How common is it to ...
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### When using a limited data set, how can I use excel to forecast future values?

To preface, I am a statistics novice, but I am faced with a problem that I cannot seem to be able to satisfactorily resolve. The problem is as follows: I am working to forecast future sales for one ...
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### SPSS Chi square test proportions (less than 5 expected)

Let's say I have a (fictive) sample: White: 25 Foreign: 1 General population: White: 30 Foreign: 9 Now I want to compare if my frequencies do not differ from the population. Normally I could use a ...
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### How to test significant interaction effect

If I have a model, lets say y = a + b1male + b2large + b3medium + b4malelarge + b5malemedium where male is dummy coded 1 for male and 0 for female and large and female are dummies (also 0,1 coded) for ...
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### Using sentiment data to predict stock prices

I have implemented a model to predict "last" price of stock of 5 days ahead. I have used RandomForestRegressor. In addition to this, I have a data set of sentiments. It is the data from social media ...
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### In Two Way Mixed ANOVA (with one IV as a Repeated Measure) what post hoc correction should I incorporate if my data has non-homogenous variance?

I have three groups of subjects (BS) which have been treated with 6 conditions (WS Repeated Measures). I have non-homogenous variance of data even if I square root transform it. I suppose I have to ...
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### Matrix Calculations and Multivariate Bayesian Methods

Suppose I have the matrix given by: $$X = \begin{bmatrix}1 & 0 & 0\\ 1 & 1 & 0 \\ 1 & 1 & 1 \end{bmatrix}$$ This matrix actually represents whether a user interacted with a ...
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### Robust M-estimator of location and dispersion by hand in R

I try to estimate a location and dispersion model with R, as described Maronna et al (2006, pp. 56). However, my estimate dispersion does not converge to the desired value. Do I have an error in the ...
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### Step by step guide for GRS test in R?

I'm new to R. I have basic knowledge in R. I'm testing a factor model. I have to use GRS test. But not sure how to do it. Please help me. I have found this recipe for GRS online. http://faculty....
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### statistics metrics or machine learning methods to quantify the relationship between a point and a group

There are several data groups: A1 = { A11, A12, A13, …, A1n} A2 = {A21, A22, A23, …, A2n} .. … … Am = {Am1, Am2, Am3, …, Amn} Here ...
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### multivariate normal distribution. And marginals distributions [duplicate]

if $X_1$ and $X_2$ are random variables that marginally have a normal distribution, is it true that the joint $(X_1,X_2)$ has a distribution according to a multivariate normal density distribution? ...
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### winsorization - reducing the effect of outliers

I have measured the response times each participant took to respond to 24 items, however, only times of the correct responses of each participant were considered, thus leaving me with distinct number ...
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### Making a forecast: Confidence/Prediction/Tolerance Interval?

I understand the the difference between these three types of intervals but I will summarize briefly: Confidence Interval: an interval that will contain the true mean value say, 95%, of the time. ...
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### Neural Networks for simple Regression: Y=X^2

All I'm trying to do is make a simple neural network to learn $y=x^2$ (Just as a toy example with x ranging over the integers between -100 and 100) with Tensorflow, but I'm having a surprising amount ...
By using singular value decomposition (SVD), I noticed from the derivation that ridge regression shrinks the coefficients by factor $\frac{D^2}{D^2+\lambda}$, where $D$ is the diagonal matrix of the ...