Curve fitting in R Quick Guide
Curve fitting in R, In this post, we’ll look at how to use the R programming language to fit a curve to a data frame. One of the most basic aspects of statistical analysis...
Category: R
68 95 99 Rule in R
68 95 99 Rule in R, The Empirical Rule, often known as the 68-95-99.7 rule, states that assuming a normal distribution dataset: Within one standard deviation of the mean, 68 percent of data values...
Difference between glm and lm in R
Difference between glm and lm in R, In R, how do you tell the difference between lm and glm? When building intervals in lm, the t-distribution is used, but in glm, the normal distribution...
How to Draw Grouped Barplot in R
When a variable has a few values, a frequency table, which may be displayed using a bar chart or barplot in R, is commonly used to summarise the data. We’ll go over the fundamentals...
How to Join Objects in R
In R, the cat() function can be used to concatenate several objects. The following is the fundamental syntax for this function: cat(…, file = “”, sep = ” “, append = FALSE)) where: …:...
Age structure diagram in R
Age structure diagram also known as a population pyramid, A population pyramid is a graph that depicts a population’s age and gender distribution. It’s a helpful chart for quickly grasping a population’s makeup as...
How to Calculate Cronbach’s Alpha in R-With Examples
Calculate Cronbach’s Alpha in R, Cronbach’s alpha is a metric for determining the internal consistency, or reliability, of a set of scale or test items. In other words, a measurement’s reliability refers to how...
Applying the Central Limit Theorem in R
Applying the Central Limit Theorem in R, The central limit theorem states that if the sample size is high enough, the sampling distribution of a sample mean is approximately normal, even if the population...
Post-Hoc Pairwise Comparisons in R -Quick Guide
Post-Hoc Pairwise Comparisons in R, To see if there is a statistically significant difference between the means of three or more independent groups, a one-way ANOVA is utilized. The following null and alternative hypotheses...
Removing Missing values in R-Quick Guide
Removing Missing values in R, To return values in R that are not NA values, use the following syntax. Removing Missing values in R Only values that aren’t NA are returned. x <- x[!is.na(x)]...
