Publications by finnstats

COUNTIF Function in R

17.07.2021

COUNTIF Function in R, As we know if we want to count the length of the vector we can make use of the length function. In case you want to count only the number of rows or columns that meet some criteria, Yes we can do it easily. Basic syntax: sum(df$column == value, na.rm=TRUE) Let’s create a data frame for the COUNTIF Function in R. data <- ...

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How to perform ANCOVA in R

22.07.2021

ANCOVA in R, Analysis of covariance is used to measure the main effect and interaction effects of categorical variables on a continuous dependent variable while controlling the effects of selected other continuous variables which is co-vary with the dependent. ANCOVA in R We can take one of the simple examples to conduct ANCOVA in R. Identify the...

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How to Calculate Root Mean Square Error (RMSE) in R

23.07.2021

Root Mean Square Error In R, The root mean square error (RMSE) allows us to measure how far predicted values are from observed values in a regression analysis. In other words, how concentrated the data around the line of best fit. RMSE = √[ Σ(Pi – Oi)2 / n ] where: Σ symbol indicates “sum”Pi is the predicted value for the ith observatio...

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How to Calculate Phi Coefficient in R

23.07.2021

Calculate Phi Coefficient in R, first, we need to understand what is Phi Coefficient? It is a measurement of the degree of association between two binary variables. When it’s coming to inference it is similar to the correlation coefficient. eXtreme Gradient Boosting in R » Ultimate Guide » Rule of Thumb Based on a general rule of thumb fo...

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How to Make Boxplot in R-Quick Start Guide

27.07.2021

Boxplots in R, A boxplot is a plot that displays the five-digit summary of a dataset. The five-digit summary is the lowest value, the first quartile, the median, the third quartile, and the maximum value. We can use a boxplot to easily visualize a set of data. Principal component analysis (PCA) in R » Boxplots in R Let’s cre...

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How to Measure Heteroscedasticity in Regression?

27.07.2021

Heteroscedasticity in Regression, one of the easiest ways to measure heteroscedasticity is while using the Breusch-Pagan Test. The test is mainly used to identify if heteroscedasticity is present in a regression analysis. This tutorial explains how to execute a Breusch-Pagan Test in R. pipe operator in R-Simplify Your Code with %>% » Heterosce...

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How to Calculate Mean Absolute Error in R

30.07.2021

Mean Absolute Error in R, when we do modeling always need to measure the accuracy of the model fit. The mean absolute error (MAE) allows us to measure the accuracy of a given model. The formula for mean absolute error is MAE = (1/n) * Σ|yi – xi| where: Σ symbol Indicate that “sum” Yi indicates that ith observed value. Xi indicates that it...

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How to Calculate SMAPE in R

03.08.2021

How to Calculate SMAPE in R?, SMAPE indicates the symmetric mean absolute percentage error.SMAPE is mainly used to measure the predictive accuracy of models. Mathematical formula is SMAPE = (1/n) * Σ(|forecast – actual| / ((|actual| + |forecast|)/2) * 100 where: Σ indicates “sum” n – indicates sample size actual – indicates the actual...

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How to Calculate Mean Absolute Percentage Error (MAPE) in R

04.08.2021

How to Calculate MAPE in R, when want to measure the forecasting accuracy of a model the solution is MAPE. MAPE stands for mean absolute percentage error. The mathematical formula to calculate MAPE is: MAPE = (1/n) * Σ(|Original – Predicted| / |Original|) * 100 where: Σ –indicates the “sum” n – indicates the sample size actual – in...

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How to Create Pareto Chart in R

09.08.2021

Pareto Chart in R, A Pareto graph is a type of graph that displays the frequencies of the different categories with the cumulated frequencies of the categories. How to create a Pareto chart in R This tutorial describes how to create a Pareto chart in R. Step 1: Create the Data for Pareto Chart Let’s create a data frame with the prod...

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