What Are the Different Types of Trend Analysis Statistics?

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  • Written By: Osmand Vitez
  • Edited By: PJP Schroeder
  • Last Modified Date: 09 May 2020
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Statistical analysis is a common process for individuals and companies who look to glean information from a large series of numbers or other data. Trend analysis statistics are a part of this larger analysis group, though the purpose of the study is to discover a record of performance. The two most common types of statistics are descriptive and inferential, both of which can make these statistics more meaningful. The use of these statistics can help a company make informed decisions regarding situations based on the data. Researchers need to be careful, however, as baseline statistical indicators can change over time.

Descriptive statistics typically summarize a given set of data or other statistics derived from a larger group. The information types here include central tendency numbers like mean, median, and mode, along with other statistics like standard deviation, range, and variance or maximum random variables. This data set is most often popular with researchers who conduct trend analysis statistics for a purpose. These ranges and values may be the most important for certain information types, such as revenues, profits, costs, and similar financial data. The use of this data, however, most likely focuses on past events or data with little guidance toward future figures or estimates.

The second type of trend analysis statistics that may have the most meaning is inferential statistics, which tends to rely more on probability statistics. This type tends to make inferences from large data groups by selecting samples from the larger population. This statistical analysis works best with industry trends or other large reviews that include a number of competitors in an industry. A researcher often uses these statistics to determine the probability that a larger group operates in the same fashion as the sample. These methods tend to be heavy in mathematics when making the studies to review information in trend analysis statistics.

When a researcher uses statistics for any sort of study or paper, he or she must understand that the outcome is only as good as the inputs. Faulty information placed into statistical models — whether descriptive or inferential — can produce wildly skewed information at the final stage. This can make trend analysis statistics very dangerous to work with when conducting a review. In many cases, it is necessary to have more than one individual review statistical studies. This increases the likelihood that it is valid and accurate.

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