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  2. Type conversion - Wikipedia

    en.wikipedia.org/wiki/Type_conversion

    The integer is: 16777217 The float is: 16777216.000000 Their equality: 1 Note that 1 represents equality in the last line above. This odd behavior is caused by an implicit conversion of i_value to float when it is compared with f_value. The conversion causes loss of precision, which makes the values equal before the comparison. Important takeaways:

  3. Decimal data type - Wikipedia

    en.wikipedia.org/wiki/Decimal_data_type

    In the floating-point case, a variable exponent would represent the power of ten to which the mantissa of the number is multiplied. Languages that support a rational data type usually allow the construction of such a value from two integers, instead of a base-2 floating-point number, due to the loss of exactness the latter would cause.

  4. Average - Wikipedia

    en.wikipedia.org/wiki/Average

    Average of chords. In ordinary language, an average is a single number or value that best represents a set of data. The type of average taken as most typically representative of a list of numbers is the arithmetic mean – the sum of the numbers divided by how many numbers are in the list. For example, the mean or average of the numbers 2, 3, 4 ...

  5. Integer overflow - Wikipedia

    en.wikipedia.org/wiki/Integer_overflow

    Integer overflow can be demonstrated through an odometer overflowing, a mechanical version of the phenomenon. All digits are set to the maximum 9 and the next increment of the white digit causes a cascade of carry-over additions setting all digits to 0, but there is no higher digit (1,000,000s digit) to change to a 1, so the counter resets to zero.

  6. Arbitrary-precision arithmetic - Wikipedia

    en.wikipedia.org/wiki/Arbitrary-precision_arithmetic

    Some programming languages such as Lisp, Python, Perl, Haskell, Ruby and Raku use, or have an option to use, arbitrary-precision numbers for all integer arithmetic. Although this reduces performance, it eliminates the possibility of incorrect results (or exceptions) due to simple overflow.

  7. Computer number format - Wikipedia

    en.wikipedia.org/wiki/Computer_number_format

    The representation has a limited precision. For example, only 15 decimal digits can be represented with a 64-bit real. If a very small floating-point number is added to a large one, the result is just the large one. The small number was too small to even show up in 15 or 16 digits of resolution, and the computer effectively discards it.

  8. Arithmetic coding - Wikipedia

    en.wikipedia.org/wiki/Arithmetic_coding

    The radix is used to express any finite integer in a presumed multiplier in polynomial form. For example, the number 457 is actually 4×10 2 + 5×10 1 + 7×10 0, where base 10 is presumed but not shown explicitly. Initially, we will convert DABDDB into a base-6 numeral, because 6 is the length of the string.

  9. Floating-point arithmetic - Wikipedia

    en.wikipedia.org/wiki/Floating-point_arithmetic

    A floating-point number is a rational number, because it can be represented as one integer divided by another; for example 1.45 × 10 3 is (145/100)×1000 or 145,000 /100. The base determines the fractions that can be represented; for instance, 1/5 cannot be represented exactly as a floating-point number using a binary base, but 1/5 can be ...