Lecture : Probability & Statistic

11/13/2015 03:37:00 PM 0 Comments




The use of statistical methods in manufacturing, development of food products, computer software, energy sources, pharmaceuticals, and many other areas involves the gathering of information or scientific data. Of course, the gathering of data is nothing new. It has been done for well over a thousand years. Data have been collected, summarized, reported, and stored for perusal. However, there is a profound distinction between collection of scientific information and inferential statistics. It is the latter that has received rightful attention in recent decades.

In the study of statistics, we are concerned basically with the presentation and interpretation of chance outcomes that occur in a planned study or scientific investigation. For example, we may record the number of accidents that occur monthly at the intersection of Driftwood Lane and Royal Oak Drive, hoping to justify the installation of a traffic light; we might classify items coming off an assembly line as “defective” or “nondefective”; or we may be interested in the volume of gas released in a chemical reaction when the concentration of an acid is varied. Hence, the statistician is often dealing with either numerical data, representing counts or measurements, or categorical data, which can be classified according to some criterion.



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Some say he’s half man half fish, others say he’s more of a seventy/thirty split. Either way he’s a fishy bastard.

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