text: ## Continuous Random Variables
  
  First, this section talks about how to describe continuous distributions and compute related probabilities, including some basic facts about the normal distribution. Then, it covers how to compute probabilities related to any normal random variable and gives examples of using $z$-score transformations. Finally, it defines tail probabilities and illustrates how to find them.
  
  ### Probability Computations for General Normal Random Variables
  
  1. a. $0.6628$
  b. $0.0359$
  c. $0.7881$
  
  d. $0.0150$
  
  3. a. $0.5959$
  b. $0.2899$
  
  C. $0.3439$
  
  5. a. $0.0000$
  
  b. $0.9131$
  
  7. a. $0.0013,0.0013$
  b. $0.1587,0.1587$
  c. $0.0001,0.0001$
  
  d. $0.0099,0.0099$
  
  9. a. $0.4412$
  b. $0.1236$
  C. $0.1676$
  d. $0.0208$
  
  11. a. $0.9772$
  b. $0.5000$
  
  13. $0.1830$
  
  15. $0.4971$
  
  17. $0.9980$
  
  19. $0.6771$
  
  21. $0.0359$
  
  23. a. $0.4038$
  b. $0.0266$
  
  25. a. $0.9082$
  b. $0.5612$
  
  27. $0.089$
explanation: The document appears to be a section from a textbook or study guide on continuous random variables, specifically focusing on probability computations for normal random variables. It contains a series of numbered items, each with multiple parts, and each part provides a numerical answer. However, the questions themselves are not explicitly stated in the text.
distilabel_metadata.content: Evaluate the user given text extract and determine if it contains a math question and optionally and answer to this question.
  
  Output rules:
  
  1. Briefly describe the document and mention if it contains a question or a question and answer.
  2. Finalize the output with: Label: no-question,question,question-and-answer,multiple-question,multiple-question-and-answer
distilabel_metadata.role: system
distilabel_metadata.content: ## Continuous Random Variables
  
  First, this section talks about how to describe continuous distributions and compute related probabilities, including some basic facts about the normal distribution. Then, it covers how to compute probabilities related to any normal random variable and gives examples of using $z$-score transformations. Finally, it defines tail probabilities and illustrates how to find them.
  
  ### Probability Computations for General Normal Random Variables
  
  1. a. $0.6628$
  b. $0.0359$
  c. $0.7881$
  
  d. $0.0150$
  
  3. a. $0.5959$
  b. $0.2899$
  
  C. $0.3439$
  
  5. a. $0.0000$
  
  b. $0.9131$
  
  7. a. $0.0013,0.0013$
  b. $0.1587,0.1587$
  c. $0.0001,0.0001$
  
  d. $0.0099,0.0099$
  
  9. a. $0.4412$
  b. $0.1236$
  C. $0.1676$
  d. $0.0208$
  
  11. a. $0.9772$
  b. $0.5000$
  
  13. $0.1830$
  
  15. $0.4971$
  
  17. $0.9980$
  
  19. $0.6771$
  
  21. $0.0359$
  
  23. a. $0.4038$
  b. $0.0266$
  
  25. a. $0.9082$
  b. $0.5612$
  
  27. $0.089$
distilabel_metadata.role: user
distilabel_metadata.raw_output_q_a_detector_0: The document appears to be a section from a textbook or study guide on continuous random variables, specifically focusing on probability computations for normal random variables. It contains a series of numbered items, each with multiple parts, and each part provides a numerical answer. However, the questions themselves are not explicitly stated in the text.
  
  Label: multiple-question-and-answer