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  • February 5, 2019Contributing

    How many solutions does a nonlinear system of equations have?

    How many solutions does a nonlinear system of equations have? two solutions A nonlinear system could be representative of two circles that overlap and intersect…

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  • February 5, 2019Guidelines

    What is time dependent propensity score matching?

    What is time dependent propensity score matching? A time-dependent propensity score based on the Cox proportional hazards model is proposed and used in risk set…

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  • February 5, 2019Blog

    How does Python handle heteroscedasticity?

    How does Python handle heteroscedasticity? How to fix the problem: Check if important explanatory variables are missing in your model and add them in. Switch…

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  • February 5, 2019Blog

    What are the conditions for a simple linear model?

    What are the conditions for a simple linear model? Simple Linear Regression Linearity: The relationship between X and the mean of Y is linear. Homoscedasticity:…

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  • February 5, 2019Helpful tips

    How do you classify data in a group?

    How do you classify data in a group? There are two major types of grouping: data binning of a single-dimensional variable, replacing individual numbers by…

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  • February 5, 2019Guidelines

    What does a scale-location plot tell us?

    What does a scale-location plot tell us? Scale-Location plot shows whether residuals are spread equally along the ranges of input variables (predictor). The assumption of…

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  • February 5, 2019Blog

    How do you find the probability of a cumulative probability?

    How do you find the probability of a cumulative probability? The cumulative probability for a value equals the cumulative probability for that value’s z-score. Here,…

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  • February 5, 2019Guidelines

    What is the value of the Pearson correlation?

    What is the value of the Pearson correlation? Pearson’s Correlation Coefficient is a linear correlation coefficient that returns a value of between -1 and +1.…

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  • February 5, 2019Popular

    What is normalized cross-entropy?

    What is normalized cross-entropy? Normalized Cross-Entropy is equivalent to the average log-loss per impression divided by what the average log-loss per impression would be if…

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  • February 5, 2019Miscellaneous

    What is difference between linear regression ridge regression and Lasso regression?

    What is difference between linear regression ridge regression and Lasso regression? Lasso is a modification of linear regression, where the model is penalized for the…

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