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Calculates and displays a ratio at N:1 {{Calculate ratio|5|3}} gives 1.7:1 {{Calculate ratio|5|3|2}} gives 1.67:1 Template parameters [Edit template data] This template prefers inline formatting of parameters. Parameter Description Type Status 1 1 Number being divided Example 5 Number required 2 2 Number being converted to 1 Example 3 Number required 3 3 Number of decimals Default 1 Example 2 ...
For example, if the static compression ratio is 10:1, and the dynamic compression ratio is 7.5:1, a useful value for cylinder pressure would be 7.5 1.3 × atmospheric pressure, or 13.7 bar (relative to atmospheric pressure). The two corrections for dynamic compression ratio affect cylinder pressure in opposite directions, but not in equal strength.
The shooting ratio in filmmaking and television production is the ratio between the total duration of its footage created for possible use in a project and that which appears in its final cut. [ 1 ] A film with a shooting ratio of 2:1 would have shot twice the amount of footage than was used in the film.
Outputs the ratio character (U+2236) between two optional arguments or instead of any colon character in a single argument. Template parameters [Edit template data] Parameter Description Type Status width 1 width or larger of both dimensions Number optional height 2 height or smaller of both dimensions Number optional Example Usage Source Output Comment {{ratio}} ∶ 4{{ratio}}3 4∶3 {{ratio ...
A clean print at a typical movie theater may have a contrast ratio of 500:1, [8] a transmissive digital projector is around 200:1, and a reflective digital projector (i.e. DLP) is around 500:1 under nearly ideal circumstances. [9] [better source needed] A modern computer LCD monitor is typically at 1000:1, [10] and TVs might be over 4000:1. [11]
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The ratio estimates are asymmetrical and symmetrical tests such as the t test should not be used to generate confidence intervals. The bias is of the order O(1/n) (see big O notation) so as the sample size (n) increases, the bias will asymptotically approach 0. Therefore, the estimator is approximately unbiased for large sample sizes.
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