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For evaluating the condition (determining non-emptiness of the first parameter) the template uses parser function #if, producing 1 if the condition is true, and 2 otherwise. The template with name equal to "P" followed by the index value produced (hence Template:P1 or Template:P2), is called with as parameters A and B. This produces either A or ...
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The introduction of Lotus 1-2-3 in November 1982 accelerated the acceptance of the IBM Personal Computer. It was written especially for IBM PC DOS and had improvements in speed and graphics compared to VisiCalc on the Apple II, this helped it grow in popularity. [36] Lotus 1-2-3 was the leading spreadsheet for several years.
A device is set to measure the speed of passing vehicles. Suppose that the device will conduct three measurements of the speed of a passing vehicle, recording as a random sample X 1, X 2, X 3. The traffic police will or will not fine the drivers depending on the average speed ¯. That is to say, the test statistic
In computing, a roundoff error, [1] also called rounding error, [2] is the difference between the result produced by a given algorithm using exact arithmetic and the result produced by the same algorithm using finite-precision, rounded arithmetic. [3]
In 1970, L. A. Marascuilo and J. R. Levin proposed a "fourth kind of error" – a "type IV error" – which they defined in a Mosteller-like manner as being the mistake of "the incorrect interpretation of a correctly rejected hypothesis"; which, they suggested, was the equivalent of "a physician's correct diagnosis of an ailment followed by the ...
The critical value corresponds to the cumulative distribution function of the F distribution with x equal to the desired confidence level, and degrees of freedom d 1 = (n − p) and d 2 = (N − n). The assumptions of normal distribution of errors and independence can be shown to entail that this lack-of-fit test is the likelihood-ratio test of ...
The following table defines the possible outcomes when testing multiple null hypotheses. Suppose we have a number m of null hypotheses, denoted by: H 1, H 2, ..., H m. Using a statistical test, we reject the null hypothesis if the test is declared significant. We do not reject the null hypothesis if the test is non-significant.