...Activity no.3C (Prelim) - Statistics General Instruction: 1. This is a group activity with maximum of 4 members per group. 2. Prepare an MS Word Document containing the following: a. Names of the members (in alphabetical order) b. Your answer in each number. Presentation of Data 1. The following are the number of customers a restaurant served for lunch on 50 weekdays: 50 64 55 51 60 41 71 53 63 64 49 59 66 45 61 57 65 62 58 65 55 61 60 55 53 57 58 66 53 56 64 46 59 49 64 60 58 64 42 47 59 62 56 63 61 68 57 51 61 51 a. Construct a FDT of the following data set and write a brief report about it. 2. A manufacturer of jeans has plants in California (CA), Arizona (AZ), and Texas(TX). A group of 25 pairs of jeans is randomly selected from the computerized database, and the state in which each is produced is recorded: CA | AZ | AZ | TX | CA | CA | CA | TX | TX | TX | AZ | AZ | CA | AZ | TX | CA | AZ | TX | TX | TX | CA | AZ | AZ | CA | CA | a. What is the variable being measured? Is it qualitative or quantitative? b. Construct an appropriate FDT and graph to describe the data. c. Write a complete discussion about it. (use the following question for your discussion) 1. What proportion of the jeans are made in California? Arizona? Texas? 2. What state produced the most jeans in the group? 3. If you want to find out whether the three plants produced equal numbers of jeans, or whether one produced more jeans...
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...i Computational Complexity: A Modern Approach Draft of a book: Dated January 2007 Comments welcome! Sanjeev Arora and Boaz Barak Princeton University complexitybook@gmail.com Not to be reproduced or distributed without the authors’ permission This is an Internet draft. Some chapters are more finished than others. References and attributions are very preliminary and we apologize in advance for any omissions (but hope you will nevertheless point them out to us). Please send us bugs, typos, missing references or general comments to complexitybook@gmail.com — Thank You!! DRAFT ii DRAFT About this book Computational complexity theory has developed rapidly in the past three decades. The list of surprising and fundamental results proved since 1990 alone could fill a book: these include new probabilistic definitions of classical complexity classes (IP = PSPACE and the PCP Theorems) and their implications for the field of approximation algorithms; Shor’s algorithm to factor integers using a quantum computer; an understanding of why current approaches to the famous P versus NP will not be successful; a theory of derandomization and pseudorandomness based upon computational hardness; and beautiful constructions of pseudorandom objects such as extractors and expanders. This book aims to describe such recent achievements of complexity theory in the context of the classical results. It is intended to both serve as a textbook as a reference for self-study. This means...
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