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The percent sign % (sometimes per cent sign in British English) is the symbol used to indicate a percentage, a number or ratio as a fraction of 100. Related signs include the permille (per thousand) sign ‰ and the permyriad (per ten thousand) sign ‱ (also known as a basis point), which indicate that a number is divided by one thousand or ten thousand, respectively.
The word promille is the cognate in Dutch, German, Finnish and Swedish, and is sometimes seen as a loanword in English with the same meaning as per mille. [7] [4] The symbol is included in the General Punctuation block of Unicode at U+2030 ‰ PER MILLE SIGN. [5] There is also an Arabic-Indic per mille sign at U+0609 ؉ ARABIC-INDIC PER MILLE SIGN.
In practice, the sample size used in a study is usually determined based on the cost, time, or convenience of collecting the data, and the need for it to offer sufficient statistical power. In complex studies, different sample sizes may be allocated, such as in stratified surveys or experimental designs with multiple treatment groups.
In most forms of English, percent is usually written as two words (per cent), although percentage and percentile are written as one word. [9] In American English, percent is the most common variant [10] (but per mille is written as two words). In the early 20th century, there was a dotted abbreviation form "per cent.", as opposed to "per cent".
Standardized mortality rate tells how many persons, per thousand of the population, will die in a given year and what the causes of death will be. Such statistics have many uses: [ citation needed ] Life insurance companies periodically update their premiums based on the mortality rate , adjusted for age.
One part per hundred thousand, per cent mille (pcm) or milli-percent denotes one part per 100,000 (10 5) parts, and a value of 10 −5. It is commonly used in epidemiology for mortality, crime and disease prevalence rates, and nuclear reactor engineering as a unit of reactivity.
The second way to calculate the utilization rate is to take the number of billable hours and divide by a fixed number of hours per week. For example, if 32 hours of billable time are recorded in a fixed 40-hour week, the utilization rate would then be 32 / 40 = 80%.
Bootstrapping depends heavily on the estimator used and, though simple, naive use of bootstrapping will not always yield asymptotically valid results and can lead to inconsistency. [17] Although bootstrapping is (under some conditions) asymptotically consistent, it does not provide general finite-sample guarantees. The result may depend on the ...