Statistics: 1001 Practice Problems For Dummies (+ Free Online Practice)
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Like every subject, statistics has its own language. The language is what helps you know what a problem is asking for, what results are needed, and how to describe and evaluate the results in a statistically correct manner. Here's an overview of the types of statistical terminology:

  • Four big terms in statistics are population, sample, parameter, and statistic:

    • A population is the entire group of individuals you want to study, and a sample is a subset of that group.

    • A parameter is a quantitative characteristic of the population that you're interested in estimating or testing (such as a population mean or proportion).

    • A statistic is a quantitative characteristic of a sample that often helps estimate or test the population parameter (such as a sample mean or proportion).

  • Descriptive statistics are single results you get when you analyze a set of data — for example, the sample mean, median, standard deviation, correlation, regression line, margin of error, and test statistic.

  • Statistical inference refers to using your data (and its descriptive statistics) to make conclusions about the population. Major types of inference include regression, confidence intervals, and hypothesis tests.

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