Descriptive statistics are one of the fundamental “must knows” with any set of data. It gives you a general idea of trends in your data including the mean, mode, median, variance and standard deviation, range, skewness, count, maximum and minimum. Using the descriptive statistics feature in Excel means that you won’t have to type in individual functions like MEAN or MODE — one button click will return a dozen different stats. If you want to calculate Excel descriptive statistics, you must have the Data Analysis Tookpak loaded in Excel. If you don’t have the Excel Data Analysis Toolpak loaded, you can find out how to by clicking here.
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If you are asked to determine a frequency in statistics, it doesn’t just mean that you should just count out the number of times something occurs.
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A frequency distribution table is one way you can organize data so that it makes more sense. For example, let’s say you have a list of IQ scores for a gifted classroom in a particular elementary school. The IQ scores are: 118, 123, 124, 125, 127, 128, 129, 130, 130, 133, 136, 138, 141, 142, 149, 150, 154. That list doesn’t tell you much about anything. You could draw a frequency distribution table, which will give a better picture of your data than a simple list. If you like our easy to follow explanations of statistics, check out our easy to follow book, which has hundreds more examples, just like this one.

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You’ll come across many terms in statistics that define samples: random samples, simple random samples, systematic samples, convenience samples, stratified samples and cluster samples. It can be overwhelming to learn all these new terms and to try and remember what each one means. Luckily, their names give away their meaning and (unlike many things in statistics), it’s a straightforward process to determine what kind of sample you have.
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How do you know whether to trust results from a survey or not? Do you believe an egg company when it tells you 90% of consumers in a taste test preferred their eggs? How about if a voluntary survey of U.S. Marines showed overwhelming support for massive pay increases for military personnel? Sometimes it isn’t enough to just accept the data as it is presented. Dig a little deeper and you might uncover one of these common problems with statistics.
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A statistic and a parameter are very similar. They are both descriptions of groups, like “50% of dog owners prefer X Brand dog food.” The difference is that statistics describe a sample, whereas a parameter describes an entire population.

For example, if you randomly poll voters in a particular election and determine that 55% of the population plans to vote for candidate A, then you have a statistic: you only asked a sample of the population who they are voting for, then you calculated what the population was likely to do based on the sample.

Alternatively, if you ask a class of third graders who likes vanilla ice cream, and 90% of them raise their hands, then you have a parameter: 90% of that class likes vanilla ice cream. You know this because you asked everyone in the population.

Here are some steps you take to be able to tell the difference between the two:
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In elementary statistics, you might be given a histogram and asked to determine the cumulative frequency distribution. Or, you might be given a frequency distribution table and asked to find the cumulative frequency. The method for both is the same, and the answer can be found in a couple of easy steps. If you like our easy to follow explanations of statistics, check out our easy to follow book, which has hundreds more examples, just like this one.
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In an introductory stats class, one of the first things you’ll learn is the difference between discrete and variable statistics. How to tell the difference between the two:
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This article will help you find the five number summary (minimum, Q1, median, Q3, and maximum) by reading a boxplot.
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Finding an interquartile range on a boxplot is easy! (If you only have numbers, see How to  find an interquartile range from a set of numbers). This how-to will show you how to find an interquartile range in a couple of easy steps.
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