Working with data (sometimes large number of variables, or large number of observations), requires adding and removal of variables. In this article, we’ll discuss 4 ways: With assigning a new column: Mutate: Using data.frame() command: Using the cbind() command: First, let’s define the dataset we’re working with: We’ll use the Read more…
Boxplot is a plot shaped as a box, which depicts the distribution of a variable using certain measures in this distribution, such as minimum, maximum, all quarterlies, inter quartile range (IQR) and even outliers of the distribution. In R programming, there are several ways to create a boxplot; In this Read more…
Let’s assume we have this table: At first, we’d build an aiding table to assist and simplify all the calculations; There’s the table: The mean is calculated as it is calculated for discrete tables. The mode is usually the mid-point of the class with the highest density (d); in some Read more…
Assume this is the frequency table we’re given: In this example, “x” is a variable representing something, and f(x) is the discrete frequency vector, of which each element is attributed to the according x value. In other words – we have 20 elements or units or subjects that their value Read more…
Jamovi enables a wide variety of descriptive statistics, and the work flow is very convenient and easy. For test case we use a fictitious data of 634 respondents. The dataset contains information about Age of respondents, Weight of respondents, Height of respondents, Yearly payment, City of residence and Job Seniority. Read more…