Publications by finnstats »
Analysis of Variance in R: 3 Steps
Analysis of Variance in R, You will be able to identify reasons for employing an Analysis of Variance (or ANOVA) test in your data analysis after completing this tutorial. You’ll also learn how to analyze the findings of an ANOVA f-test. Let’s imagine you want to look at a category variable and see how it relates to other variables. Take, fo...
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Simple Linear Regression in r
Simple linear regression in r, we want to create models to investigate and forecast the relationship between variables, and the most basic relationship that we can think of is a straight line. Visit finnstats.com for up-to-date and accurate lessons. Let’s take a look at the first linear relationship that we are going to create. Intraclass Cor...
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Model Selection in R (AIC Vs BIC)
Model Selection in R, Let’s look at a linear regression model using mtcars dataset. Visit finnstats.com for up-to-date and accurate lessons. First, we need to brush up on our knowledge by looking at the mtcars dataset. head(mtcars) M mpg cyl disp hp drat wt qsec vs am gear carb Mazda RX4 21.0 6 160 110 3.90 2...
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Importance of Statistical Analysis in Business
Statistical Analysis in Business, Businesses cannot survive without consumer spending. Statistical analysis can help businesses identify trends among consumers so they can better meet their needs. It is no secret that statistical analysis is integral to any business. Statistical analysis refers to the use of mathematical and statistical metho...
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Regression in R-Ultimate Guide
Regression in R, In a recent article, we discussed model fitting and selection. However, we haven’t considered how we’ll choose which variables to include in our model. Simple Linear Regression in r » Guide » Let’s go over our linear regression model for the mtcars data.frame again. Regression in R mtcars.lm <- lm(mpg ~ disp, data=mtcars...
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Cross Validation in R with Example
What Does Cross-Validation Mean? Cross-validation is a statistical approach for determining how well the results of a statistical investigation generalize to a different data set. Cross-validation is commonly employed in situations where the goal is prediction and the accuracy of a predictive model’s performance must be estimated. We explored ...
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What’s Neural Network?
What’s Neural Network?. A neural network is a biologically inspired method for computers to learn through analyzing data. When does a neural network become a deep neural network? Here’s a neural network, and it’s not particularly deep!. Although it just has three layers, the term “deep” usually refers to dozens, if not hundreds, of ...
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error: No CurrentVersion entry in Software/JavaSoft registry!
error: No CurrentVersion entry in Software/JavaSoft registry!. When receiving the following problem while trying to install package xlxs in R. Error: package or namespace load failed for ‘xlsx’: .onLoad failed in loadNamespace() for 'rJava', details: call: fun(libname, pkgname) error: No CurrentVersion entry in Software/JavaSoft registry...
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How to Plot Observed and Predicted values in R
Plot Observed and Predicted values in R, In order to visualize the discrepancies between the predicted and actual values, you may want to plot the predicted values of a regression model in R. This tutorial demonstrates how to make this style of the plot using R and ggplot2. Approach 1: Plot of observed and predicted values in Base R The followin...
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String Manipulation in R
String Manipulation in R, In this article, we’ll show you how to manipulate strings in the R programming language using many methods. To begin, we’ll read text from a file into the computer to demonstrate the string operations. data<-readLines("D:/RStudio/Binning/TextData.txt") head(data) The “data” variable will have a vector with five ...
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