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Histograms are one of the fundamental tools in Exploratory Data Analysis (EDA) and are specifically designed to show the distribution of a single continuous variable. A histogram breaks the data into bins (intervals), showing the frequency of data points within each bin. By observing the shape of the histogram, one can understand how the data is distributed, whether it is skewed, whether it has multiple peaks (bimodal), or if it follows a normal distribution. This provides important insights into the underlying structure of the data, such as identifying the presence of outliers, skewness, and overall spread. Why Other Options Are Incorrect: • A: Scatter plots, not histograms, are used to display the relationship between two continuous variables. • C: Categorical data is typically displayed using bar charts, not histograms. • D: While histograms can give an overall sense of distribution, they do not directly assess central tendency (like mean or median). • E: Variance can be assessed through other statistical measures, such as standard deviation or variance calculation, but not through histograms.
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