Yes. They could increase the width and thereby reduce the frequency densities (heights) of the one or both of the outermost classes.
Best to use a histogram i think! z scores can probably be used too however they seem more a method of how to transform outliers in workable scores.
I'm unable to see the histogram you're referring to. However, to describe a data distribution, you can look for characteristics such as its shape (normal, skewed, bimodal), center (mean or median), spread (range or standard deviation), and any outliers. If you provide details about the histogram, I can help you analyze it!
You don't do anything. There is none!!
Scaling a histogram is important because it allows for better visualization and comparison of data distributions, especially when datasets have different ranges or magnitudes. By adjusting the scale, one can enhance the interpretability of the histogram, making it easier to identify patterns, trends, and outliers. Additionally, scaling can help in normalizing data, which is crucial for statistical analysis and when applying machine learning algorithms. Overall, proper scaling ensures that the histogram accurately reflects the underlying data characteristics.
comparison between histogram equalization and histogram matching?
there are no limits to outliers there are no limits to outliers
A gap in a histogram indicates a range of values with no data points, suggesting that there may be a lack of observations or that the data may not exhibit values in that range. This can highlight potential outliers, data clustering, or natural breaks in the distribution. Analyzing gaps can help in understanding the underlying characteristics of the dataset and in identifying areas that may require further investigation.
What is a shape of a histogram?
A histogram is better suited for visualizing large datasets with continuous or interval data, as it effectively summarizes the distribution of values by grouping them into bins. This allows for a clearer representation of frequency distributions and helps identify patterns, trends, or outliers. In contrast, a dot plot is more appropriate for smaller datasets or discrete data, where individual data points can be easily distinguished. Therefore, when dealing with extensive data that requires a comprehensive overview, a histogram is the preferable choice.
Histogram is a noun.
The prefix of "histogram" is "histo-".
I don't know what is histogram