11. A data value is 2 standard deviations above the mean. What is its z-score?

  • -2
  • 0
  • 2
  • 1

Test your knowledge: Probability distributions with Python

12. A data professional is working with a dataset that has a normal distribution. To test out the empirical rule, they want to find out if roughly 68% of the data values fall within 1 standard deviation of the mean. What Python functions will enable them to compute the mean and standard deviation?

  • mn() and std()
  • mean() and std()
  • mn() and stand()
  • mean() and standard()

13. What Python function is used to compute z-scores for data?

  • normal.zscore()
  • stats.zscore()
  • mean.zscore()
  • median.zscore()

Weekly challenge 2

14. A data professional is working for a large corporation. The marketing team asks them to predict the success of a new ad campaign. To make an informed prediction, they use statistics to analyze data on past ad campaigns. What type of probability are they using?

  • Independent
  • Objective
  • Dependent
  • Subjective

15. The probability of an event is close to 1. Which of the following statements best describes the likelihood that the event will occur?

  • The event is likely to occur.
  • The event is certain to occur.
  • The event is certain not to occur.
  • The event is unlikely to occur.

16. The probability of rain tomorrow is 40%. What is the probability of the complement of this event?

  • The probability of no rain tomorrow is 60%.
  • The probability of no rain tomorrow is 40%.
  • The probability of no rain tomorrow is 20%.
  • The probability of no rain tomorrow is 80%.

17. A first coin toss results in tails, and a second coin toss results in heads. What concept best describes these two events?

  • Non-random
  • Subjective
  • Dependent
  • Independent

18. What concept refers to the probability of an event before new data is collected?

  • Posterior probability
  • Conditional probability
  • Subjective probability
  • Prior probability

Shuffle Q/A 2

19. Which of the following statements accurately describes a key difference between discrete and continuous random variables?

  • Discrete random variables are negative numbers; continuous random variables are positive numbers.
  • Discrete random variables are positive numbers; continuous random variables are negative numbers.
  • Discrete random variables are typically decimal values that can be measured; continuous random variables are typically whole numbers that can be counted.
  • Discrete random variables are typically whole numbers that can be counted; continuous random variables are typically decimal values that can be measured.

20. Fill in the blank: The _____ distribution best models the number of heads in 10 fair coin flips.

  • Normal
  • Bernoulli
  • Poisson
  • Binomial
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