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News / Blog: #statistics

What is desk research?

12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Desk research is a process of gathering information from existing, publicly available sources. It is a method of primary market research in which data is collected by analyzing publications, websites, reports, statistics and other available sources. Desk research has the advantage of being quick, inexpensive, and a suitable method for researching a wide range of topics.
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What is time series analysis?

12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Time series analysis is a statistical method used to study changes in a given datum over a period of time. This method is often used to understand how different variables change over time and can be used, for example, to study trends, patterns, or seasonal variations.
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What is a variable (statistics)

12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
In statistics, a variable is a characteristic of a target group that is used for analysis. A variable can be both a qualitative (e.g. gender) and a quantitative (e.g. age) characteristic of a target group. Variables can then be related to each other in order to make a specific statement about a target group.
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What is a function (statistics)?

12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
A function (statistic) is a mathematical model that represents a relationship between one or more input variables and an output variable. It describes how the output variable changes, if at all, because of the input variable. In statistics, functions are used to extrapolate and generalize individual data points, resulting in a description of the trend behind the data.
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What is a Robust Estimate?

12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Robust estimates are statistical procedures used to reduce uncertainty in the results of analyses. They are used to minimize the risk that a coincident estimate will be applied. Robust estimates are often less sensitive to outliers than are concordant estimates, meaning that they are less prone to failure when a small number of data are unusual.
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