For Data Science Learners
R for Data Science
How to perform a one-sample t-test in R?. one-sample The t-test compares one sample’s mean to a known standard (or theoretical/hypothetical) mean. One-sample t-tests can only be used when the data is normally distributed. The Shapiro-Wilk test can be used to verify this. How to perform a one-sample t-test in R Typical research questions are:…
Test for Normal Distribution in R, Many statistical tests, such as correlation, regression, t-test, and analysis of variance (ANOVA), presuppose that the data has particular features. They demand that the data follow a normal or Gaussian distribution. These tests are known as parametric tests since their validity is determined by the data distribution. Normality and…
glm function in r, we’ll look at what generalized linear models are in R and how to make them. We’ll also go over Logistic and Poisson Regression in depth. So, let’s get this tutorial started In R, what are Generalized Linear Models? In R, generalized linear models are an extension of linear regression models that…
Create contingency tables in R, Contingency tables are helpful for condensing a huge number of observations into smaller, more manageable tables. We’ll learn about contingency tables and how to make them in this R tutorial. Complex/flat tables, cross-tabulation, and recovering original data from contingency tables will all be covered. As you can see, this course…
In this lesson, we’ll look at how to integrate R with Hadoop. For Big Data analysis, we’ll show you a variety of R and Hadoop integration strategies. When it comes to large data, R is the go-to tool for data scientists and analysts. It may be ideal for many data science jobs, but when it…
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Detecting and Dealing with Outliers, We’re going to look a little bit more at these mammals’ sleep data. Let’s take a summary of them. library(mice) summary(mammalsleep) species bw brw African elephant : 1 Min. : 0.005 Min. : 0.14 African giant pouched rat: 1 1st Qu.: 0.600 1st Qu.: 4.25 Arctic Fox : 1 Median…
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Dealing With Missing Values in R, one of the issues is that when you have a large matrix of data and some of the columns have a few missing values, it might be difficult to work with. Checking Missing Values in R – (datasciencetut.com) You won’t be able to perform a lot of multivariate or…
Checking Missing Values in R, we’ll undertake data wrangling, which is the pre-processing and preparation of data. In fact, practicing data science will consume more than 70% of your time. We’ll only look at a few of the most important commands to make things as simple as possible. However, you will devote a significant amount…
Best GGPlot Themes, This tutorial covers everything you need to know about the greatest ggplot2 themes, including. How to use the built-in ggplot2 themes to change the appearance of plots. How to change the appearance of plots using the ggthemes library’s predefined themes. How to change the plot panel background and gridlines, as well as…
Quantiles by Group calculation in R, Quantiles are numbers in statistics that divide a ranking dataset into equal groups. In R, we can use the following functions from the dplyr package to calculate quantiles grouped by a certain variable. library(dplyr) Identify the quantiles that you’re interested in. q<-c(0.25, 0.5, 0.80) Quantiles are calculated by grouping…
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