Which type of chart plots observations to show their distribution such as time, weight, size, or temperature?

The correct answer is a histogram, which is specifically designed to display the frequency distribution of a set of continuous data. It provides a visual representation of how data points are distributed across different ranges or intervals, known as bins. Each bin represents a range of values and the height of the bar corresponding to each bin indicates how many observations fall within that range.

In quality improvement contexts, histograms are particularly valuable for identifying patterns, trends, and variations in data. For instance, you might use a histogram to analyze the distribution of patients' weights in a healthcare setting or the variation in temperature readings from a manufacturing process. This allows for insights into the central tendency and spread of the data, helping to inform decision-making and process improvements.

In contrast, a scatter plot is used to visualize the relationship between two variables, a line chart typically depicts data trends over time, and a Pareto chart focuses on identifying the most significant factors in a dataset, typically for prioritizing issues in quality improvement initiatives. Each of these charts serves different analytical purposes, making the histogram uniquely suited for displaying distributions.