For Data Science Learners
R for Data Science
optim Function in R, we will explore how to apply a general-purpose optimization using the optim function in R programming language. We will create example data and then demonstrate the usage of the optim function to minimize the residual sum of squares. optim Function in R First, let’s create the example data we will use…
Compare numeric vectors in R, we explore the usage of the ‘near’ function from the ‘dplyr’ package in R programming. The article is divided into two examples, with the first one demonstrating the basic application of the ‘near’ function and the second one showcasing its flexibility with user-defined tolerance. Compare numeric vectors in R To…
Extract values from vector in R, we will delve into extracting specific values from a vector using the nth, first, and last functions from the dplyr package in R programming language. The article is structured into four examples that demonstrate the extraction of vector elements. Extract patterns in R? ยป Data Science Tutorials Extract values…
How to add Axes to Plot in R, In the world of data visualization, creating visually appealing and informative plots is crucial for effectively communicating insights. The R programming language offers a plethora of tools to customize your plots, including the ability to add user-defined axis ticks using the axis() function. In this article, we…
Understanding the Student’s t-Distribution in R, The Student’s t-distribution, also known as the t-distribution, is a significant concept in statistics, especially in hypothesis testing and constructing confidence intervals. This probability distribution is particularly useful when dealing with small sample sizes or unknown population variances. In this article, we will discuss the t-distribution’s properties and how…
Read More “Understanding the Student’s t-Distribution in R” »
Solving Systems of Equations in R, Solving systems of linear equations is a crucial task in various fields, such as mathematics, engineering, and economics. In this article, we will demonstrate how to solve systems of equations using R, an open-source programming language. We will use R’s built-in functions and datasets to provide clear examples for…
Calculating Conditional Probability in R, Conditional probability is a crucial concept in statistics and probability theory. It allows us to update our beliefs about the likelihood of an event occurring based on new information. In this article, we will explore the concept of conditional probability, its formula, and how to calculate it using the R…
Normal Distribution in R, also known as the Gaussian distribution, is a probability distribution that is frequently used in statistics and probability theory to describe continuous random variables. It has a bell-shaped curve, which is symmetrical around its peak, and has a single mode, mean, and median. In a normal distribution, the majority of the…
Confidence Intervals in R, A Confidence Interval (CI) is a statistical tool used to estimate the range within which a population parameter, such as the mean or standard deviation, is likely to reside. It offers a measure of uncertainty associated with an estimate derived from sample data. CIs are commonly reported alongside point estimates of…
Type II Error in R, we will discuss the concept of Errors in Hypothesis Testing, explore the different types of errors that may arise during this process, and learn how to calculate them. Hypothesis testing involves forming assumptions about a model or data set, which serve as the foundation for further analysis. The term ‘Error’…
