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Computer Science and Numerical Methods Flashcards

7 cards from real EIT practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.

Read the first 7 Computer Science and Numerical Methods flashcards as text
  1. Gaussian elimination is a direct method for solving:

    Answer: Systems of linear algebraic equations

    Gaussian elimination reduces an augmented matrix [A|b] to upper triangular form through row operations, then back-substitutes to find the solution vector.

  2. Using 8-bit two's complement representation, the range of signed integers is:

    Answer: -128 to 127

    With 8 bits in two's complement, the most negative value is -128 (10000000) and the most positive is 127 (01111111).

  3. The central difference approximation for the second derivative f''(x) is:

    Answer: [f(x+h) - 2f(x) + f(x-h)] / h²

    The second-order central difference formula for f''(x) combines f at x+h, x, and x-h with coefficients 1, -2, 1 divided by h².

  4. For the bisection method to guarantee finding a root on interval [a, b], which condition must hold?

    Answer: f(a) · f(b) < 0 (the function changes sign over the interval)

    By the Intermediate Value Theorem, if f is continuous and f(a) · f(b) < 0, then at least one root must exist between a and b.

  5. In object-oriented programming, inheritance primarily allows:

    Answer: A subclass to acquire the methods and attributes of a parent class

    Inheritance creates an is-a relationship where the child class automatically gains all accessible members of the parent, enabling code reuse.

  6. The condition number of a matrix is used to measure:

    Answer: The sensitivity of the linear system solution to small perturbations in inputs

    A high condition number indicates an ill-conditioned matrix where small errors in the input vector b can cause large errors in the solution x.

  7. The IEEE 754 standard specifies:

    Answer: Binary floating-point number representation and arithmetic rules

    IEEE 754 defines how floating-point numbers (single, double, extended precision) are stored in binary and how arithmetic operations behave, including rounding and special values like NaN and infinity.