One Pager Cheat Sheet

• Analyzing data with Univariate, Bivariate, and Multivariate methods is an important part of Exploratory Analysis, which helps to uncover patterns, anomalies and inform model selection.
• Univariate Analysis involves analyzing one feature of our dataset to determine the output, as shown by plotting the sepal_length feature for each species and finding their ranges.
• The petal_length of the species Versicolor ranges from 7.1 - 8.0.
• Bivariate Analysis is used to analyze two variables in a dataset to determine the species, with non-linear classification methods preferred due to the overlap of points.
• Bivariate analysis is a statistical analysis that looks at the correlation between two variables, whereas Multivariate analysis looks at the relationships between three or more.
• Multivariate analysis is a technique used to analyze multiple variables and their relationships by plotting them in a graph to explore their correlation with each other and with the output, and can help to identify what features are most useful.
• The Pairplot graph highlights that Setosa has the smallest petal width and petal length from the clear patterning of the data points as well as from the layered kernel density estimates.
• Exploration of a dataset can involve Univariate, Bivariate, and Multivariate Analysis of variables and their relationships.