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paper 111620220323

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  2. paper 111620220323
NM Young Engineer Competition Sample Papers 2023 University Level paper 111620220323
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  1. Question 1 of 24
    1. Question

    Erlang Distribution is also called General___________.

     

     

     

     

    Correct
    Incorrect
  2. Question 2 of 24
    2. Question

    Distributions are the only discrete memoryless random distributions.

     

     

     

     

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    Incorrect
  3. Question 3 of 24
    3. Question

    When can we use Gamma Distribution?

    • This response will be reviewed and graded after submission.

    Grading can be reviewed and adjusted.
    Grading can be reviewed and adjusted.
  4. Question 4 of 24
    4. Question

    A list of vectors is said to be linearly dependent if and only if  there is no vector in the list which is in the span of the preceding vectors.

     

     

    Correct
    Incorrect
  5. Question 5 of 24
    5. Question

    Write Kotlin S2 code to demonstrate use of quantile.

     

    Expected Similar Output:

    • This response will be reviewed and graded after submission.

    Grading can be reviewed and adjusted.
    Grading can be reviewed and adjusted.
  6. Question 6 of 24
    6. Question

    Write down the conditions for the Poisson distribution to be valid.

    • This response will be reviewed and graded after submission.

    Grading can be reviewed and adjusted.
    Grading can be reviewed and adjusted.
  7. Question 7 of 24
    7. Question

    The successive search directions in the steepest-descent methods may not relate to each other.

     

     

     

    Correct
    Incorrect
  8. Question 8 of 24
    8. Question

    Write Kotlin S2 code to show Gamma distribution.

    Expected Similar Output:

     

    • This response will be reviewed and graded after submission.

    Grading can be reviewed and adjusted.
    Grading can be reviewed and adjusted.
  9. Question 9 of 24
    9. Question

    The sign of covariance shows the tendency of __________relationship between the variables

     

     

     

     

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  10. Question 10 of 24
    10. Question

    _____________method is used to accelerate the gradient descent algorithm by taking into consideration the exponentially weighted average of the gradients.

     

     

     

     

    Correct
    Incorrect
  11. Question 11 of 24
    11. Question

    The Variance is a measure of dispersion that checks how ____________ apart the data in a distribution are from the mean.

     

    Correct
    Incorrect
  12. Question 12 of 24
    12. Question

    A list of vectors is said to be linearly independent if and only if  there is single vector in the list which is in the span of the preceding vectors.

    Correct
    Incorrect
  13. Question 13 of 24
    13. Question

    A fair six sided die is rolled with X being the number on the uppermost face, the variance of X is _________

     

     

     

     

    Correct
    Incorrect
  14. Question 14 of 24
    14. Question

    _______________converges slightly faster than the bisection method.

     

     

     

     

    Correct
    Incorrect
  15. Question 15 of 24
    15. Question

    Perform Scalar operation on any matrix in kotlin S2 

    Expected Similar Output:

     

    • This response will be reviewed and graded after submission.

    Grading can be reviewed and adjusted.
    Grading can be reviewed and adjusted.
  16. Question 16 of 24
    16. Question

    an eigenvector is a vector whose direction remains __________when a linear transformation is applied to it

     

     

     

     

     

    Correct
    Incorrect
  17. Question 17 of 24
    17. Question

    Sample_____________ is a measure of the tailedness of the probability distribution.

    Correct
    Incorrect
  18. Question 18 of 24
    18. Question

    Define a matrix and compute its inverse and transpose in kotlin S2

    Similar Expected Output:

    • This response will be reviewed and graded after submission.

    Grading can be reviewed and adjusted.
    Grading can be reviewed and adjusted.
  19. Question 19 of 24
    19. Question

    In kotlin S2 Determine whether   is a basis for .

    Expected Similar Output:

    • This response will be reviewed and graded after submission.

    Grading can be reviewed and adjusted.
    Grading can be reviewed and adjusted.
  20. Question 20 of 24
    20. Question

    Perform double exponential ,real line, half real line in kotlin S2.

    Expected Similar Output:

    • This response will be reviewed and graded after submission.

    Grading can be reviewed and adjusted.
    Grading can be reviewed and adjusted.
  21. Question 21 of 24
    21. Question

    Demonstrate Cholesky decomposition in kotlin S2 

    Expected Similar Output:

     

    • This response will be reviewed and graded after submission.

    Grading can be reviewed and adjusted.
    Grading can be reviewed and adjusted.
  22. Question 22 of 24
    22. Question

    Implement the polar decomposition using Kotlin S2.

    Expected Similar Output:

    • This response will be reviewed and graded after submission.

    Grading can be reviewed and adjusted.
    Grading can be reviewed and adjusted.
  23. Question 23 of 24
    23. Question

     generate standard normal samples and normal samples based on a specified mean μ and variance 

    • This response will be reviewed and graded after submission.

    Grading can be reviewed and adjusted.
    Grading can be reviewed and adjusted.
  24. Question 24 of 24
    24. Question

     reduce this given matrix to the row echelon form and also find the eigen pair using kotlin S2.

    Expected Similar Output:

    • This response will be reviewed and graded after submission.

    Grading can be reviewed and adjusted.
    Grading can be reviewed and adjusted.
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