Univariate analysis is the simplest form of analyzing data. "Univariate" refers to a single variable, and thus univariate analysis involves describing and understanding patterns within that single variable. The main goal of univariate analysis is to summarize and find patterns in data.

Types of Variables

• Continuous Variables: These can take any value within a range (e.g., height, weight, temperature).
• Categorical Variables: These have distinct categories or groups (e.g., gender, colors, types of fruits).

Descriptive Statistics

Descriptive statistics help in summarizing the main features of a dataset. They provide simple summaries about the sample and the measures.

Measures of Central Tendency

• Mean: The average of the data.
• Median: The middle value when data is ordered.
• Mode: The most frequently occurring value in the data set.

Measures of Dispersion

• Range: The difference between the maximum and minimum values.
• Variance: The average of the squared differences from the mean.
• Standard Deviation: The square root of the variance, indicating how spread out the values are.

Visualization Techniques

Visual representations are crucial in univariate analysis to understand the distribution and characteristics of the variable.

• Histograms: Show the frequency distribution of a continuous variable.
• Bar Charts: Used for displaying the frequency of categorical variables.
• Box Plots: Summarize data using the median, quartiles, and outliers.
• Pie Charts: Represent categorical data as proportions of a whole.
• Frequency Tables: Summarize the count of different values for categorical variables.