IB Math SL Probability and Stats Definitions Review
Chapter 3:
1. Sample space U: all possible outcomes
2. Event: an outcome from an experiment
3. Event A: a specific outcome
4. Event A’: outcomes not in set A
𝑛(𝐴)
5. Theoretical probability of an event A: 𝑃(𝐴) = 𝑛(𝑈)
6. The number of ways that event A can occur: 𝑛(𝐴)
7. The total number of possible outcomes: 𝑛(𝑈)
8. ∩: Probability of events’ intersection/probability of events A and B
9. ∪: Probability of events’ in union/probability of events A or B
10. If the probability of an event is P, and you take n trials, you would expect the event to
occur how many times? [n x P times]
11. Relative frequency: an estimate of probability
12. The larger the number of relative frequencies, the [closer/farther] the relative frequency
is to the probability. [closer]
13. Independent events: when the occurrence of one event (A or B) does not affect the chance
that the other one occurs.
14. When two events A and B are independent, 𝑃(𝐴 ∩ 𝐵) =? [𝑃(𝐴) ∗ 𝑃(𝐵)]
a. Bonus: what is this rule called? [Product rule for independent events,
multiplication rule]
15. Dependent events: events in which the outcome of one will affect the outcome of the
other
16. 𝑃(𝐴) + 𝑃(𝐴′ ) =? [1]
17. 1 − 𝑃(𝐴) =? [𝑃(𝐴′ )]
18. For any two events A and B, (𝐴 ∪ 𝐵) =? [𝑃(𝐴) + 𝑃(𝐵) − 𝑃(𝐴 ∩ 𝐵)]
19. In general, if A and B are mutually exclusive, then 𝑃(𝐴 ∩ 𝐵) =? [0]
20. In general, if A and B are mutually exclusive, then 𝑃(𝐴 ∪ 𝐵) =? [𝑃(𝐴) + 𝑃(𝐵)]
21. In general, for two events A and B the probability of A occurring given that B has
𝑃(𝐴∩𝐵)
occurred can be found using 𝑃(𝐴|𝐵) =? [ 𝑃(𝐵) ]
22. If A and B are independent events, 𝑃(𝐴|𝐵) =? [P(A)]
23. If A and B are independent events, 𝑃(𝐵|𝐴) =? [P(B)]
24. If A and B are independent events, 𝑃(𝐴|𝐵′) =? [P(A)]
25. If A and B are independent events, 𝑃(𝐵|𝐴′) =? [P(B)]
Chapter 8:
26. Quantitative data can be split up into two categories: discrete and continuous
27. An example of continuous variables are: variables that have exact numerical values (i.e.
height, length, time, speed, etc.]
28. An example of discrete variables are: variables that can only be integer values (i.e.
apples, owls, cars, books, etc.)
29. Population: includes all members of a defined group that we are studying for data driven
decisions.
30. Sample: a part of the population/subset of the population
31. How do we present continuous data? [Draw a histogram]
32. Mean: sum of the numbers divided by the number of values in a set of data
33. Mode: value that occurs most frequently in a set of data
34. Median: number present in the middle when the numbers in a set of data are arranged in
order of size
35. Range: difference between the largest and smallest values
36. Outlier: an extreme value in a data set
37. Lower/First Quartile (Q1): median of the lower half of a data set; 25% of population are
below this value
38. Median/Second Quartile (Q2): median of the entire set of data, is also called the 50th
percentile; 50& of population are below this value
39. Third/Upper Quartile (Q3): median of the upper half of a data set; 75% of population are
below this value
40. Interquartile Range (IQR): difference between the thir and first quartiles
41. Box and whisker plot: type of graph that shows the dispersion of data, including the five
number summary