Textbook and Syllabus

2. Probability and Statistics Textbook and Syllabus Textbook: “Probability and Statistics for Engineers & Scientists”, 9thEdition, Ronald E. Walpole, et. al., Pearson, 2010. • Syllabus: • Chapter 1: Introduction • Chapter 2: Probability • Chapter 3: Random Variables and Probability Distributions • Chapter 4: Mathematical Expectation • Chapter 5: Some Discrete Probability Distributions • Chapter 6: Some Continuous Probability Distributions • Chapter 8: Fundamental Sampling Distributions and Data Descriptions • Chapter 9: One- and Two-Sample Estimation Problems • Chapter 10: One- and Two-Sample Tests of Hypotheses

3. Probability and Statistics Grade Policy • Final Grade = 10% Homework + 20% Quizzes + 30% Midterm Exam + 40% Final Exam + Extra Points • Homeworks will be given in fairly regular basis. The average of homework grades contributes 10% of final grade. • Homeworks are to be submitted on A4 papers, otherwise they will not be graded. Probability and StatisticsHomework 2R. Suhendra00920210000821 March 2023No. 1. Answer: . . . . . . . . • Heading of Homework Papers (Required)

4. Probability and Statistics Grade Policy • Homeworks must be submitted on time, one day before the schedule of the lecture. Late submission will be penalized by point deduction of –10·n, where n is the number of lateness made. • There will be 3 quizzes. Only the best 2 will be counted. The average of quiz grades contributes 20% of the final grade. • Make up for quizzes must be requested within one week after the date of the respective quizzes. • Mid exam and final exam follow the schedule released by AAB (Academic Administration Bureau). • Make up for mid exam and final exam must be requested directly to AAB. • In order to maintain the integrity, the score of a make up quiz or exam, upon discretion, can be multiplied by 0.9 (i.e., the maximum score for a make up is then 90). • Extra points will be given if you raise a question or solve a problem in front of the class. You will earn 1, 2, or 3 points.

5. Probability and Statistics Grade Policy • You are responsible to read and understand the lecture slides. I am responsible to answer your questions. • Lecture slides can be copied during class session. It also will be available on internet around 1 days after class. Please check the course homepage regularly. • http://zitompul.wordpress.com • The use of internet for any purpose during class sessions is strictly forbidden. • You are expected to write a note along the lectures to record your own conclusions or materials which are not covered by the lecture slides.

6. Chapter 1 Introduction Chapter 1 Introduction

7. Chapter 1 Introduction What is Probability? • Probability is the measure of the likeliness that a random event will occur, or the knowledge upon an underlying model in figuring out the chance that different outcomes will occur. • By definition, probability values are between 0 and 1. • Probability theory is the study of the mathematical rules that govern random events. • If we flip a fair coin 3 times, what is the probability of obtaining 3 heads? • If we throw a dice 2 times, what is the probability that the sum of the faces is 10?

8. Chapter 1 Introduction What is Statistics? • Statistics is a tool to get information from data. Data Statistics Information Probability • Knowledge about the population concerning some particular facts • Facts (mostly numerical), collected from a certain population • Statistics is used because the underlying model that governs a certain experiments is not known. • All that available is a sample of some outcomes of the experiment. • The sample is used to make inference about the probability model that governs the experiment. • So, a thorough understanding of probability is essential to understand statistics.

9. Chapter 1 Introduction Branches of Statistics • Descriptive statistics, is the branch of statistics that involves the organization, summarization, and display of data when the population can be enumerated completely. • Inferential statistics, is the branch of statistics that involves using a sample of a population to draw conclusions about the whole population. A basic tool in the study of inferential statistics is probability. • Descriptive statistics: There are 45 students in the Probability and Statistics class. Twenty are younger than 24 years old. 16 are older than 36 years old. What can be concluded? • Inferential statistics: As many as 860 people in a Jakarta were questioned. People who drives bicycle daily have average age of 31 years old. For people who drives motorcycle, the average age is 21. What can be concluded?

10. Chapter 1 Introduction Steps in Inferential Statistics • Design the experiments and collect the data. • Organize and arrange the data to aid understanding. • Analyze the data and draw general conclusions from data. • Estimate the present and predict the future. • In conducing the steps mentioned above, Statistics use the support of Probability, which can model chance mathematically and enables calculations of chance in complicated cases.

11. Chapter 1 Introduction Why do ITs need Probability and Statistics? • Security Design • How safe is your password? • Risk Analysis • As IT has become increasingly important to the competitive position of firms, managers have grown more sensitive to potential losses incurred by companies because of problems with their sophisticated IT systems. • Data Mining • An application of various statistical methods to huge databases. The goal is to filter available records to produce association, rules, or pattern, that may be used to the benefit of the user. <Ex: online store, software testing, stock exchange> • Randomized Algorithm • Some algorithms benefit from using random steps rather than deterministic steps. <Ex: optimization, numerical method> • Queuing and Reliability • The mathematical study of waiting time. Based on statistical data, the optimum resource can be allocated to satisfy optimum number customers. <Ex: supermarket, computers, public transports> ! And many more....

12. Chapter 2 Probability Chapter 2 Probability

13. Chapter 2.1 Sample Space Some Terminologies • Data: result of observation that consists of information, in the form of counts, measurements, or responses. • Parameter: numerical description of a population characteristics. • Statistic: numerical description of a sample characteristics. • Population: the collection of all outcomes, counts, measurements, or responses that are of interest. • Sample: a subset of a population.

14. Chapter 2.1 Sample Space Sample Space • Experiment: any process that generates a set of data. • Sample space: the set of all possible outcomes of a statistical experiment. It is represented by the symbol S. • Element or member: each outcome in a sample space. Sometimes simply called a sample point. The sample space S, of possible outcomes when a coin is tossed may be written as where H and T correspond to “heads” and “tails”, respectively. The sample space can be written according to the point of interest. Consider the experiment of tossing a die. The sample space can be

15. Chapter 2.1 Sample Space Sample Space Suppose that three items are selected at random from a manufacturing process. Each item is inspected and classified defective, D, or nondefective, N. As we proceed along each possible outcome, we see that the sample space is • Sample spaces with a large or infinite number of sample points are best described by a statement or rule. For example, if the possible outcomes of an experiment are the set of cities in the world with a population over million, the sample space is written If S is the set of all points (x,y) on the boundary or the interior of a circle of radius 2 with center at the origin, we write

16. Chapter 2.2 Events Events • A set is a collection of unique objects. • A set A is a subset of another set B if every element of A is also an element of B. We denote this as AÍ B. • Event: a subset of a sample space. We are interested in probabilities of events. The event A that the outcome when a die is tossed is divisible by 3 is the subset of the sample space S1, and can be expressed as The event B that the number of defectives is greater than 1 in the example on the previous slide can be written as Given the sample space S = {t|t ≥ 0}, where t is the life in years of a certain electronic components, then the event A that the component fails before the end of the fifth year is the subset A ={t|0 ≤ t < 5}.

17. Chapter 2.2 Events Events • Null set: a subset that contains no elements at all. It is denoted by the symbol Æ. • The complement of an event A with respect to S is the subset of all elements of S that are not in A. We denote the complement of A by the symbol A’. Let R be the event that a red card is selected from an ordinary deck of 52 playing cards, and let S be the entire deck. Then R’ is the event that the card selected from the deck is not a red but a black card. S A A’

18. Chapter 2.2 Events Events • The intersection of two events A and B, denoted by A ÇB, is the event containing all elements that are common to A and B. • Two events A and B are mutually exclusive, or disjoint if A ÇB = Æ, that is, if A and Bhave no elements in common. S S A A B B A ÇB = Æ A ÇB

19. Chapter 2.2 Events Events • The union of two events A and B, denoted by A ÈB, is the event containing all elements that belong to A or B or both. Let A = {a, b, c} and B = {b, c, d, e}; then AÇB = {b, c} AÈB = {a, b, c, d, e} S If M = {x |3 < x < 9} and N = {y | 5 < y < 12}; then MÈN = {z | 3 < z <12} MÇN = ? A B A È B

20. Chapter 2.2 Events Events If S = {x|0 < x < 12}, A = {x|1 ≤ x < 9}, and B = {x|0 < x < 5}, determine AÈB AÇB A’ ÈB’ AÈB = AÇB = A’ ÈB’ = {x | 0 < x < 9} {x | 1 ≤ x < 5} (AÇB)’ = {x | 0 < x < 1, 5 ≤ x <12}

21. Chapter 2.2 Events Venn Diagram • Like already seen previously, the relationship between events and the corresponding sample space can be illustrated graphically by means of Venn diagrams. {1, 2} {1, 3} {1, 2, 3, 4, 5, 7} {4, 7} {1} {2, 6, 7} AÇB = BÇC = AÈC = B’ ÇA = AÇ BÇC = (AÈ B) Ç C’ = S A B 2 7 6 1 3 4 5 8 C

22. Chapter 2.3 Counting Sample Points Counting Sample Points • Goal: to count the number of points in the sample space without actually enumerating each element. • |Multiplication Rule| If an operation can be performed in n1 ways, and if for each of these a second operation can be performed in n2 ways, then the two operations can be performed together in n1·n2 ways. How may sample points are in the sample space when a pair of dice is thrown once?

23. Chapter 2.3 Counting Sample Points Counting Sample Points Sam is going to assemble a computer by himself. He has the choice of ordering chips from two brands, a hard drive from four, memory from three and an accessory bundle from five local stores. How many different ways can Sam order the parts? Since n1 = 2, n2 = 4, n3 = 3, and n4 = 5, there are n1·n2·n3·n4 = 2·4·3·5 = 120 different ways to order the parts

24. Chapter 2.3 Counting Sample Points Counting Sample Points How many even four-digit numbers can be formed from the digits 0, 1, 2, 5, 6, and 9 if each number can be used only once? For even numbers, there are n1 = 3 choices for units position. However, the thousands position cannot be 0. If units position is 0, n1 = 1, then we have n2 = 5 choices for thousands position, n3 = 4 for hundreds position, and n4 = 3 for tens position. In this case, totally n1·n2·n3·n4 = 1·5·4·3 = 60 numbers. If units position is not 0, n1 = 2, then we have n2 = 4, n3 = 4, and n4 = 3. In this case, totally n1·n2·n3·n4 = 2·4·4·3 = 96 numbers. The total number of even four-digit numbers can be calculated by 60 + 96 = 156. ? How if each number can be used more than once?

25. Chapter 2.3 Counting Sample Points Permutation • A permutation is an arrangement of all or part of a set of objects. Consider the three letters a, b, and c. There are 6 distinct arrangements of them: abc, acb, bac, bca, cab, and cba. There are n1 = 3 choices for the first position, then n2 = 2 for the second, and n3 = 1 choice for the last position, giving a total n1·n2·n3 = 3·2·1 = 6 permutations.

26. Chapter 2.3 Counting Sample Points Permutation • In general, n distinct objects can be arranged inn(n–1)(n–2) · · · (3)(2)(1) ways. • This product is represented by the symbol n!, which is read “n factorial.” • The number of permutations of n distinct objects is n! • The number of permutations of n distinct objects taken r at a time is

27. d Chapter 2.3 Counting Sample Points Permutation Consider the four letters a, b, c, and d. Now consider the number of permutations that are possible by taking 2 letters out of 4 at a time. The possible permutations are ab, ac, ad, ba, bc, bd, ca, cb, cd, da, db, and dc. There are n1 = 4 choices for the first position, and n2 = 3 for the second, giving a total n1·n2 = 4·3 = 12 permutations. Another way, by using formula,

28. Chapter 2.3 Counting Sample Points Permutation Three awards (research, teaching and service) will be given one year for a class of 25 graduate students in a statistics department. If each student can receive at most one award, how many possible selections are there?

29. Chapter 2.3 Counting Sample Points Permutation A president and a treasurer are to be chosen from a student club consisting of 50 people. How many different choices of officers are possible if There are no restrictions A will serve only if he is president B and C will serve together or not at all D and E will not serve together • 50P2 • 49P1 + 49P2 • 2P2 + 48P2 • 50P2 – 2 or {2·2P1·48P1 + 48P2} ? For detailed explanation read the e-book.

30. Chapter 2.3 Counting Sample Points Permutation • The number of distinct permutations of n things of which n1 are of one kind, n2 of a second kind, …, nk of a kth kind is How many distinct permutations can be made from the letters a, a, b, b, c, and c?

31. Chapter 2.3 Counting Sample Points Permutation In a college football training session, the defensive coordinator needs to have 10 players standing in a row. Among these 10 players, there are 1 freshman, 2 sophomore, 4 juniors, and 3 seniors, respectively. How many different ways can they be arranged in a row if only their class level will be distinguished?

32. Probability and Statistics Homework 1A Disk of polycarbonate plastic from a supplier are analyzed for scratch and shock resistance. The result from 100 disks are summarized as follows. Let A denote the event that a disk has high shock resistance, and let B denote the event that a disk has high scratch resistance. Determine the number of disks in AÇ B, A’, and AÈB. (Mo.2.26) Construct a Venn Diagram that represents the analysis result above. Can you indicate all the events mentioned in (a)? Two balls are “randomly drawn” from a bowl containing 6 white and 5 black balls. What is the probability that one of the drawn balls is white and the other black? (Ro.E3.5a)

33. Probability and Statistics Homework 1B You are given two boxes with balls numbered 1 to 5. One box contains balls 1, 3, and 5. The other box contains balls 2 and 4. You first pick a box at random, then pick a ball from that box at random. What is the probability that you pick the ball number 2? (Utah.L2)