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Statistical Experiments

Statistical Experiments. The set of all possible outcomes of an experiment is the Sample Space, S. Each outcome of the experiment is an element or member or sample point. If the set of outcomes is finite, the outcomes in the sample space can be listed as shown: S = { H, T }

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Statistical Experiments

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  1. Statistical Experiments • The set of all possible outcomes of an experiment is the Sample Space, S. • Each outcome of the experiment is an element or member or sample point. • If the set of outcomes is finite, the outcomes in the sample space can be listed as shown: • S = {H, T} • S = {1, 2, 3, 4, 5, 6} • in general, S = {e1, e2, e3, …, en} • where ei = each outcome of interest EGR 252 Spring 2014

  2. Tree Diagram • If the set of outcomes is finite sometimes a tree diagram is helpful in determining the elements in the sample space. • The tree diagram for students enrolled in the School of Engineering by gender and degree: • The sample space: S = {MEGR, MIDM, MTCO, FEGR, FIDM, FTCO} EGR 252 Spring 2014

  3. Your Turn: Sample Space • Your turn: The sample space of gender and specialization of all BSE students in the School of Engineering is … or • 2 genders, 6 specializations, • 12 outcomes in the entire sample space S = {FECE, MECE, FEVE, MEVE, FISE, MISE, FMAE, etc} S = {BMEF, BMEM, CPEF, CPEM, ECEF, ECEM, ISEF, ISEM… } EGR 252 Spring 2014

  4. Definition of an Event • A subset of the sample space reflecting the specific occurrences of interest. • Example: In the sample space of gender and specialization of all BSE students in the School of Engineering, the event F could be “the student is female” • F = {BMEF, CPEF, ECEF, EVEF, ISEF, MAEF} EGR 252 Spring 2014

  5. Operations on Events • Complement of an event, (A’, if A is the event) • If event F is students who are female, F’ = {BMEM, EVEM, CPEM, ECEM, ISEM, MAEM} • Intersection of two events, (A ∩ B) • If E = environmental engineering students and F = female students, (E ∩ F) = {EVEF} • Union of two events, (A U B) • If E =environmental engineering students and I = industrial engineering students, (E U I) = {EVEF, EVEM, ISEF, ISEM} EGR 252 Spring 2014

  6. Venn Diagrams • Mutually exclusive or disjoint events Male Female • Intersection of two events Let Event E be EVE students (green circle) Let Event F be female students (red circle) E ∩ F is the overlap – brown area EGR 252 Spring 2014

  7. Other Venn Diagram Examples • Five non-mutually exclusive events • Subset – The green circle is a subset of the beige circle EGR 252 Spring 2014

  8. Subset Examples • Students who are male • Students who are on the ME track in ECE • Female students who are required to take ISE 428 to graduate • Female students in this room who are wearing jeans • Printers in the engineering building that are available for student use EGR 252 Spring 2014

  9. Let’s Try It A U C = ? B’∩ A = ? A ∩ B ∩ C = ? (A U B) ∩ C’ = ? B A 2 6 7 1 4 3 5 C EGR 252 Fall 2015

  10. Sample Points • Multiplication Rule • If event A can occur n1ways and event B can occur n2ways, then an event C that includes both A and B can occur n1 * n2ways. • Example, if there are 6 different female students and 6 different male students in the room, then there are 6 * 6 = 36 ways to choose a team consisting of a female and a male student . EGR 252 Spring 2014

  11. Permutations • Definition: an arrangement of all or part of a set of objects. • The total number of permutations of the 6 engineering specializations in MUSE is … 6*5*4*3*2*1 = 720 • In general, the number of permutations of n objects is n! NOTE: 1! = 1 and 0! = 1 EGR 252 Spring 2014

  12. Permutation Subsets • In general, where n = the total number of distinct items and r = the number of items in the subset • Given that there are 6 specializations, if we take the number of specializations 3 at a time (n = 6, r = 3), the number of permutations is EGR 252 Spring 2014

  13. Permutation Example • Mercer is introducing a new scholarship competition program for computer engineers interested in Big Data analysis. First, second, and third place winners will receive a specified scholarship amount. If 12 students applied for the scholarship, how many ways can the winners be selected? • If the outcome is defined as ‘first place student, second place student, and third place student • Total number of outcomes is 12P3 = 12!/(12-3)! = 1320 • Order matters EGR 252 Spring 2014

  14. Combinations • Selections of subsets without regard to order. • Example: How many ways can we select 3 winners (w/out regard to placing) from the 12 students? • Total number of outcomes is 12C3 = 12! / [3!(12-3)!] = 220 EGR 252 Spring 2014

  15. Let’s Try It • Registrants at a large convention are offered 6 sightseeing tours on each of 3 days. In how many ways can a person arrange to go on a sightseeing tour planned by this convention? Multiplication Rule: On each of 3 days, you have a choice of 6 tours. Event A: The particular day, can occur 3 ways Event B: The specific tour, can occur 6 ways n1 * n2 = 18 ways EGR 252 Fall 2015

  16. Let’s Try It • Find the number of ways that 7 faculty members can be assigned to 4 sections of EGR 252 if no faculty member is assigned to more than one section. Permutation: Order matters 7 faculty members selected 4 at a time: EGR 252 Fall 2015

  17. Introduction to Probability • The probability of an event, A is the likelihood of that event given the entire sample space of possible events. • P(A) = target outcome / all possible outcomes • 0 ≤ P(A) ≤ 1 P(ø) = 0 P(S) = 1 • For mutually exclusive events, P(A1U A2U … U Ak) = P(A1) + P(A2) + … P(Ak) EGR 252 Spring 2014

  18. Calculating Probabilities • Examples: • There are 26 students enrolled in a section of EGR 252, 3 of whom are BME students. The probability of selecting a BME student at random off of the class roll is: P(BME) = 3/26 = 0.1154 2. The probability of drawing 1 heart from a standard 52-card deck is: P(heart) = 13/52 = 1/4 EGR 252 Spring 2014

  19. Additive Rules Experiment: Draw one card at random from a standard 52 card deck. What is the probability that the card is a heart or a diamond? Note that hearts and diamonds are mutually exclusive. Your turn: What is the probability that the card drawn at random is a heart or a face card (J,Q,K)? EGR 252 Spring 2014

  20. Your Turn: Solution Experiment: Draw one card at random from a standard 52 card deck. What is the probability that the card drawn at random is a heart or a face card (J,Q,K)? Note that hearts and face cards are not mutually exclusive. P(H U F) = P(H) + P(F) – P(H∩F) = 13/52 + 12/52 – 3/52 = 22/52 EGR 252 Spring 2014

  21. Card-Playing Probability Example • P(A) = target outcome / all possible outcomes • If an experiment can result in any of N different equally likely outcomes, and if exactly n of those outcomes correspond to event A, then the probability Event A is P(A) EGR 252 Spring 2014

  22. Card Playing Probability Example • In a poker hand consisting of 5 cards, find the probability of holding 2 aces and 3 jacks. Combination…order does not matter. The number of ways of being dealt 2 aces from 4 cards is combinations(2 aces) = → The number of ways of being dealt 3 jacks from 4 cards is combinations(3 jacks) = → Per the multiplication rule, there are n = 6*4 = 24 possible hands with 2 aces and 3 jacks given the number of aces and jacks available in a 52 card deck. EGR 252 Fall 2015

  23. Card Playing Probability Example Con’t The total number of 5-card poker hands are equally likely therefore N = Likely Outcomes (N) = → Per rule 2.3: P(A) = The probability of getting 2 aces and 3 jacks in a 5-card poker hand is 0.9 X 10-5 EGR 252 Fall 2015

  24. Your Turn • A box contains 500 envelopes, of which 75 contain $100 in cash, 150 contain $25, and 275 contain $10. An envelop may be purchased for $25. • (a) What is the sample space for the different amounts of money? • (b) Assign probabilities to the sample points • (c) Find the probability that the first envelop purchased will contain less than $100. EGR 252 Fall 2015

  25. Your Turn: Solution • (a) S = {$10, $25, $100} • (b) P($10) = 0.55, P($25) 0.3, P($100) = 0.15 • (c) P($10) + P($25) = 0.55 + 0.3 = 0.85 or, 1 – P($100) = 1 – 0.15 = 0.85 EGR 252 Fall 2015

  26. Homework Reading • Read section 2.6 and Chapter 3 of your textbook EGR 252 Fall 2015

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