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A calendrical calculation is a calculation concerning calendar dates. Calendrical calculations can be considered an area of applied mathematics. Some examples of calendrical calculations: Converting a Julian or Gregorian calendar date to its Julian day number and vice versa (see § Julian day number calculation within that article for details).
Zeller's congruence is an algorithm devised by Christian Zeller in the 19th century to calculate the day of the week for any Julian or Gregorian calendar date. It can be considered to be based on the conversion between Julian day and the calendar date.
The basic approach of nearly all of the methods to calculate the day of the week begins by starting from an "anchor date": a known pair (such as 1 January 1800 as a Wednesday), determining the number of days between the known day and the day that you are trying to determine, and using arithmetic modulo 7 to find a new numerical day of the week.
The formula calculator concept can be applied to all types of calculator, including arithmetic, scientific, statistics, financial and conversion calculators. The calculation can be typed or pasted into an edit box of: A software package that runs on a computer, for example as a dialog box. An on-line formula calculator hosted on a web site.
The doomsday's anchor day calculation is effectively calculating the number of days between any given date in the base year and the same date in the current year, then taking the remainder modulo 7. When both dates come after the leap day (if any), the difference is just 365y + y / 4 (rounded down). But 365 equals 52 × 7 + 1, so after ...
For example, this is how 10 days absence could be shown: 1 instance of absence with a duration of ten days (1 × 1 × 10) = 10 points; 2 instances of absence, each of five days (2 × 2 × 10) = 40 points; 5 instances of absence, each of two days (5 × 5 × 10) = 250 points; 10 instances of absence, each of one day (10 × 10 × 10) = 1000 points
where is the grand mean, is the additive main effect of level from the first factor (i-th row in the contingency table), is the additive main effect of level from the second factor (j-th column in the contingency table) and is the non-additive interaction effect of treatment (,) for samples =,..., from both factors (cell at row i and column j ...
Let D 2 be the value rolled on dice 2. Probability that D 1 = 2. Table 1 shows the sample space of 36 combinations of rolled values of the two dice, each of which occurs with probability 1/36, with the numbers displayed in the red and dark gray cells being D 1 + D 2. D 1 = 2 in exactly 6 of the 36 outcomes; thus P(D 1 = 2) = 6 ⁄ 36 = 1 ⁄ 6: