This is the Electti Review. Today, a bar plot and a histogram look like the same chart, and confusing them changes what your data is allowed to say. Both are rectangles on an axis. That is where the similarity ends. A bar plot compares categories, products, countries, treatment groups. Its horizontal axis carries labels, not measurements, and the gaps between its bars are honest. There is nothing between Germany and Italy. A histogram describes the distribution of one continuous variable, income, latency, temperature. Its axis is a number line, and its bars touch because the values are adjacent. Heights differ too. A bar's height is a number you supplied. A histogram's is a count the chart computed after slicing the range into bins. That slicing is the part nobody audits. Bin width is a choice and the only knob here that can manufacture a finding. Wide bins smooth two peaks into one hill. Narrow bins turn noise into structure. Same data, two conclusions, no warning label. Square root, Sturgis, Friedman diaconus are defaults, not evidence. If a claim about shape survives only one bin width, it is not a claim about the data. The common mistakes follow from the confusion. Sorting a histogram's bars by height destroys the axis that gives them meaning. Leaving gaps between histogram bars implies breaks in a continuum that has none. Reporting a bar plot of group means as if it described the group's hide spread, skew, and outliers. The things you were measuring. The decision rule is short. Ask what the horizontal axis is. Labels you could reorder without loss. Bar plot. Measurements where order and distance mean something. Histogram. If you want comparison, use bars. If you want shape, where the mass sits, how long the tail runs, whether two populations are pretending to be one, use a histogram and show more than one binwidth. The chart is not decoration, it is an argument. Choose it on purpose. That's the review.