CNHS Statistics and Probability Third Quarter

Which type of random variable can take on an infinite number of values within a certain range?

• Continuous variable

• discrete variable

• qualitative variable

• quantitative variable

Which statement best explains why a person's weight is classified as a continuous random variable?

• Weight can only be measured in whole numbers.

• Weight can take any value within a range and be measured with high precision

•   Weight is always the same for every individual.

• Weight is counted rather than measure

   

Why is the number of students in a classroom considered a discrete random variable, while the height of students is considered a continuous random variable?

•  The number of students can only take values between 0 and 100, while height can

  take any value greater than 0.

• The number of students can vary from 0 to 1,000, but the height of students can only

  take values between 0 and 10 feet

• The number of students is always measured in whole numbers, while the height of

  students can be measured to any level of precision, including fractions or decimals

• The number of students is typically recorded in decimal values, while height is recorded

  as a whole number

A company wants to analyze customer behavior. They collect the following data: (1) The number of products purchased, (2) The amount of time spent shopping. How should these variables be classified?

• Both are discrete random variables

• Both are continuous random variables

• The number of products is discrete, while shopping time is continuous.

•  The number of products is continuous, while shopping time is discrete

  A coin is tossed twice. What is the probability of getting exactly one head (out of the two tosses)?

• 1/4

• 1/2

• 1/3

• 1/5

  A box contains 5 red balls, 3 green balls, and 2 blue balls. If one ball is drawn at random, let X represent the number of green balls drawn. What are the possible values of X?

• 0,1

• 0,1,2

• 0,1,2,3

•    1, 2, 3

Which of the following properties is true for a probability distribution of a discrete random variable?

• Each probability in the distribution must be between 0 and 1.

• The probabilities can be negative

• The probabilities do not need to add up to 1

• The sum of all probabilities in the distribution must be greater than 1

In a factory, the number of defective items in a sample of 10 is modeled by the following probability distribution:

0 defective items: 0.5, 1 defective item: 0.3, 2 defective items: 0.2

What is the probability that exactly 1 defective item will be found in the sample?

• 0.2

• 0.3

• 0.5

• 0.7

1If a discrete random variable X takes values 1, 2, and 3 with probabilities 0.2, 0.5, and 0.3   respectively, what is the probability of X being greater than 1?

• 0.2

• 0.5

• 0.8

• 0.9

in a study, the random variable X represents the number of books checked out by a patron at the library. The following probability distribution is give

Create a new probability distribution where the probability of X = 1 is changed to 0.4. What should the new probability of X = 0 be to maintain a valid distribution?

• 0.0

• 0.1

• 0.2

• 0.15