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(Pre-Finals) Quantitative Research Mocktest BSIT 402
28問 • 8ヶ月前
  • Xai Alexandrei Delos Reyes
    • 通報

    問題一覧

  • 1

    is a function whose domain is a sample space and whose range is some set of real numbers.

    Random Variable

  • 2

    is a random variable that may assume a finite or countable number of possible outcomes that can be listed.

    Discrete Random Variable

  • 3

    is a random variable that may assume an uncountable number of values or possible outcomes, represented by the intervals on a number line.

    Continuous Random Variable

  • 4

    provides the probabilities for all possible values that a discrete random variable (𝑥) can take on in the range of 𝑿.

    Probability Mass Function (pmf)

  • 5

    is a function that describes the shape, character, and relative likelihoods of obtaining the possible values that a random variable can assume.

    Probability Distribution

  • 6

    It is a relation in which each element of the domain is paired with exactly one element of the range. "Each element" implies that every element in the domain is related to some element in the range.

    function

  • 7

    of a function is defined as the set of all possible input values (commonly the x variable), which produces a valid output (y-value) from a particular function. In simple language, this is what can go into a function.

    domain

  • 8

    the ______ is the set of all possible output values (commonly the variable y, or sometimes expressed as f(x)), which results from using a particular function. In simple language, this is what actually comes out of a function.

    range

  • 9

    What is the formula of Probability Mass Function (pmf)?

    𝑓(𝑥) = 𝑃(𝑋 = 𝑥)

  • 10

    What is the formula of variance?

    𝛿2 = ∑(𝑋 − 𝜇𝑥)² ⋅ 𝑃(𝑋 = 𝑥)

  • 11

    is the summation of each value of the variable multiplied by its probability.

    Expected value of a random variable

  • 12

    What is the formula of standard deviation?

    𝛿 = √𝛅²

  • 13

    Which statement is NOT TRUE for the characteristics of Binomial Distribution

    The outcomes of interest are rare relative to the possible outcomes.

  • 14

    What does "n!" Mean in this formula?

    the number of trials (sample size)

  • 15

    What does "r" Mean in this formula?

    the number of successes in sample, (r = 0, 1, 2, ..., n)

  • 16

    What does "P" Mean in this formula?

    the probability of a success on any single trial

  • 17

    was developed by French mathematician Simeon Denis Poisson, the Poisson probability distribution is very useful in decision-making with respect to quality control situation, waiting line problems (queue), and other application to business. It is also useful for determining the probability of a number of occurrences (successes) over a given time or within a given area or volume

    Poisson Distribution

  • 18

    Which statement is NOT TRUE on the characteristics of the Poisson Distribution

    The probability of success is fixed for each trial of the experiment.

  • 19

    What is the definition of μ?

    is the mean number of occurrences per unit (time, volume, area, etc.)

  • 20

    What is the definition of e?

    is a constant approximately equal to 2.71828... (Actually, 𝑒 is the base of the natural logarithm system.)

  • 21

    What is the definition of x?

    number of occurrences (0, 1, 2, …)

  • 22

    What is the formula of standard deviation?

    𝛿 = √𝛅²

  • 23

    What is the formula of expected value?

    𝐸(𝑥) = [𝑥1 ⋅ 𝑃(𝑥1)] + [𝑥2 ⋅ 𝑃(𝑥2)] + ⋯ + [𝑥𝑛 ⋅ 𝑃(𝑥𝑛)]

  • 24

    Which of the following demonstrates a expected value where X has values 𝑥𝑥1, 𝑥𝑥2, …, 𝑥𝑥𝑛𝑛

    𝐸(𝑥) = [𝑥1 ⋅ 𝑃(𝑥1)] + [𝑥2 ⋅ 𝑃(𝑥2)] + ⋯ + [𝑥𝑛 ⋅ 𝑃(𝑥𝑛)]

  • 25

    In Binomial Distribution, Each repetition of the experiment is called a ____?

    Trial

  • 26

    In Binomial Distribution, the trials are _____?

    Independent

  • 27

    In Binomial Distribution, For each trial, there are how many outcomes?

    2

  • 28

    In a Poisson Distribution, The number of outcomes of interest is ____

    random

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    問題一覧

  • 1

    is a function whose domain is a sample space and whose range is some set of real numbers.

    Random Variable

  • 2

    is a random variable that may assume a finite or countable number of possible outcomes that can be listed.

    Discrete Random Variable

  • 3

    is a random variable that may assume an uncountable number of values or possible outcomes, represented by the intervals on a number line.

    Continuous Random Variable

  • 4

    provides the probabilities for all possible values that a discrete random variable (𝑥) can take on in the range of 𝑿.

    Probability Mass Function (pmf)

  • 5

    is a function that describes the shape, character, and relative likelihoods of obtaining the possible values that a random variable can assume.

    Probability Distribution

  • 6

    It is a relation in which each element of the domain is paired with exactly one element of the range. "Each element" implies that every element in the domain is related to some element in the range.

    function

  • 7

    of a function is defined as the set of all possible input values (commonly the x variable), which produces a valid output (y-value) from a particular function. In simple language, this is what can go into a function.

    domain

  • 8

    the ______ is the set of all possible output values (commonly the variable y, or sometimes expressed as f(x)), which results from using a particular function. In simple language, this is what actually comes out of a function.

    range

  • 9

    What is the formula of Probability Mass Function (pmf)?

    𝑓(𝑥) = 𝑃(𝑋 = 𝑥)

  • 10

    What is the formula of variance?

    𝛿2 = ∑(𝑋 − 𝜇𝑥)² ⋅ 𝑃(𝑋 = 𝑥)

  • 11

    is the summation of each value of the variable multiplied by its probability.

    Expected value of a random variable

  • 12

    What is the formula of standard deviation?

    𝛿 = √𝛅²

  • 13

    Which statement is NOT TRUE for the characteristics of Binomial Distribution

    The outcomes of interest are rare relative to the possible outcomes.

  • 14

    What does "n!" Mean in this formula?

    the number of trials (sample size)

  • 15

    What does "r" Mean in this formula?

    the number of successes in sample, (r = 0, 1, 2, ..., n)

  • 16

    What does "P" Mean in this formula?

    the probability of a success on any single trial

  • 17

    was developed by French mathematician Simeon Denis Poisson, the Poisson probability distribution is very useful in decision-making with respect to quality control situation, waiting line problems (queue), and other application to business. It is also useful for determining the probability of a number of occurrences (successes) over a given time or within a given area or volume

    Poisson Distribution

  • 18

    Which statement is NOT TRUE on the characteristics of the Poisson Distribution

    The probability of success is fixed for each trial of the experiment.

  • 19

    What is the definition of μ?

    is the mean number of occurrences per unit (time, volume, area, etc.)

  • 20

    What is the definition of e?

    is a constant approximately equal to 2.71828... (Actually, 𝑒 is the base of the natural logarithm system.)

  • 21

    What is the definition of x?

    number of occurrences (0, 1, 2, …)

  • 22

    What is the formula of standard deviation?

    𝛿 = √𝛅²

  • 23

    What is the formula of expected value?

    𝐸(𝑥) = [𝑥1 ⋅ 𝑃(𝑥1)] + [𝑥2 ⋅ 𝑃(𝑥2)] + ⋯ + [𝑥𝑛 ⋅ 𝑃(𝑥𝑛)]

  • 24

    Which of the following demonstrates a expected value where X has values 𝑥𝑥1, 𝑥𝑥2, …, 𝑥𝑥𝑛𝑛

    𝐸(𝑥) = [𝑥1 ⋅ 𝑃(𝑥1)] + [𝑥2 ⋅ 𝑃(𝑥2)] + ⋯ + [𝑥𝑛 ⋅ 𝑃(𝑥𝑛)]

  • 25

    In Binomial Distribution, Each repetition of the experiment is called a ____?

    Trial

  • 26

    In Binomial Distribution, the trials are _____?

    Independent

  • 27

    In Binomial Distribution, For each trial, there are how many outcomes?

    2

  • 28

    In a Poisson Distribution, The number of outcomes of interest is ____

    random