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Over the last few decades, data collection has helped us solve many complex problems. But at the same time, it has turned into this data-hungry machine with an insatiable appetite that everyone frowns at and blames data scientists for. Of course, if you're currently one of the thousands of computer science students, this is not you.
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Descriptive statistics is the study of the act of expressing what a given set of data means or what it represents. Descriptive statistics are useful when analyzing a large data sample by logging patterns and anomalies in a data set. It also helps in identifying trends which helps predict the outcome of prescribed remedies and future outcomes.
Inferential statistics is the study of hypothesis testing. Inferential statistics takes sample data and makes generalized assumptions about a population parameter. Hypothesis testing can project or extrapolate an outcome from an overall correlation of findings from a data sample.
The accuracy of your inferential statistics might be questionable, but it's a good way to get the bigger picture if you know what I mean.
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The world of statistics provides us with a detailed way to understand our environments. It also opens up wonderful possibilities that are both exciting and scary depending on the side of the table you're sited at. Statistics is bound to be a regular fixture in our colleges for some time to come.
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