Privacy Policy This privacy policy applies to the Statistic Distributions CDF app (hereby referred to as "Application") for mobile devices that was created by Misbah Aiad (hereby referred to as "Service Provider") as a Free service. This service is intended for use "AS IS". Information Collection and Use The Application does NOT collect any type of information, neither online (account based) nor offline (user device). The Application does not connect to the internet at all, nor stores anything entered by the user on their device. Third Party Access Only aggregated, anonymized data is periodically transmitted to external services to aid the Service Provider in improving the Application and their service. The Service Provider may share your information with third parties in the ways that are described in this privacy statement. Please note that the Application utilizes third-party services that have their own Privacy Policy about handling data. Below are t...
Also called Gaussian distribution. OK, many things in this world tends, and should do, to be normally distributed. Any distribution is a representation of how the information or data is distributed. We mainly look for its central tendency ( mean ) and variability ( variance ). That's why the normal distribution is usually written as: N ~ (Mu, Sigma^2) For example: the weight of most adult (who still youth) people will normally be centered around some values. Yes, you right there is a diversity: some are slim and some are obese. We may expect the average weight for people (example: ages 20 to 30) to be between 70 to 74 kg. OK, let's consider it as 72 (this is the mean value). Let x represents the weight of a random person. Thus, Expected Value [x] = mean [x] = Mu = 72 kg If we have a sample, we can compute the variance (sigma^2) to indicate variability. But we may here think as following: Variance = Sigma^2 = Expected Value [(x-Mu)^2] Sta...
A good fact to submit is that we can't easily know the exact truth values/parameters of a population. Mostly, population parameters also change slightly by time and/or affected by different surrounding factors. Example: a production line for the 500 ml bottles is assumed to produce a population of bottles such that mean value of bottles capacity is exactly 500 ml. Nice, but what happens in realty? In realty, several factors will mostly affect the production: human factors, machine factors, environment temperature...etc. Also, each new bottle will contribute in the population mean value. This means a continuous slight change, either up or down, of the mean capacity. Here comes the hypothesis! As you see, the ground truth value for population mean is difficult to be exactly determined. However, we have general assumptions/expectations. OK, constructing a hypothesis should always be driven by our initial knowledge and expectations about the population. ...
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