In the area of inferential statistics, frequency distributions based on samples help you determine the type of analysis you should use to make inferences about the population. Along with descriptive statistics such as averages, ranges of values, and percentages or counts, the chart of a frequency distribution puts you in a stronger position to understand a set of people or things because it helps you visualize how a variable behaves across its range of possible values. Those two reasons help define the two general branches of statistics: descriptive statistics and inferential statistics.
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The other concerns how to make inferences about a population of people or objects on the basis of a sample. One concerns visualizing how a variable is distributed across people or objects.
It’s helpful to use frequency distributions in statistical analysis for two broad reasons. Figure 1.13 might represent personal longevity: Relatively few people die in their twenties, thirties and forties, compared to the numbers who die in their fifties through their eighties. This is another positively skewed distribution-quite a common situation in manufacturing process control.īecause true lower limits are more common than true upper limits, you tend to encounter more positively skewed frequency distributions than negatively skewed. Most would have zero, one, or two defects, several would have three or four, and a very few would have five or six. House prices therefore tend to bunch up between $100,000 and $300,000, with fewer between $300,000 and $400,000, and fewer still as you go up the scale.Ī quality control engineer might sample 100 ceramic tiles from a production run of 10,000 and count the number of defects on each tile. This distribution is positively skewed.Īnother variable, home prices, tends to be positively skewed, because although there’s a real lower limit (a house cannot cost less than $0) there is no theoretical upper limit to the price of a house. It’s normal to make a few mistakes (say, one or two), and it’s abnormal to make several (say, five or more). Figure 1.10 shows a typical frequency distribution.įigure 1.13 Negatively skewed distributions are not as common as positively skewed distributions.įigure 1.12 shows counts of the number of mistakes on individual federal tax forms. Using the examples just given, two people who weigh 100.2 and 100.4 pounds might each be classed as 100 pounds two cars that get 18.8 and 19.2 mpg might be grouped together at 19 mpg and any number of houses that cost between $220,001 and $225,000 would be treated as in the same price level.Īs it’s usually shown, the chart of a frequency distribution puts the variable’s values on its horizontal axis and the count of instances on the vertical axis.
It’s the visual representation of a frequency distribution, a concept that’s absolutely fundamental to intermediate and advanced statistical methods.Ī frequency distribution is intended to show how many instances there are of each value of a variable. In addition to charts that show two variables-such as numbers broken down by categories in a Column chart, or the relationship between two numeric variables in an XY chart-there is another sort of Excel chart that deals with one variable only. Learn More Buy Understanding Frequency Distributions Statistical Analysis: Microsoft Excel 2013
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