University of Phoenix Material Learning Team Summary Worksheet TWO (due week Five) Brenda Rivera As a learning team‚ complete the table with formulas‚ rules‚ and examples from each section of Chapters 4‚ 5‚ 6‚7‚8‚9‚10 and 11 in the textbook. The completed summary will help prepare you for the Final Exam in Week 5. Points will be awarded for completion of the project. Study Table for Weeks One and Two Chapter 4 Systems of Linear Equations; Matrices (Section 4-1 to 4-6)
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Discrete Time Models Stanley R. Pliska 2 Contents Preface iii Acknowledgments 1 2 viii Single Period Securities Markets 1.1 Model Specifications . . . . . . . . . . . . . 1.2 Arbitrage and other Economic Considerations 1.3 Risk Neutral Probability Measures . . . . . . 1.4 Valuation of Contingent Claims . . . . . . . . 1.5 Complete and Incomplete Markets . . . . . . 1.6 Risk and Return . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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when I simulated data in excel. In task 1 I find out how to calculate or forecast how much card should we print. I use a random variable with =RAND( function and use =VLOOKUP() function to find out demand from discreet variable called cumulative probabilities. This is discrete because we find out the range by frequency distribution. Then I use if function to calculate disposable cost with =IF (Demand>Production‚(Demand-Production)*Disposable cost‚ 0). This function works with logical criteria. It
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ERROR CODING Tutorial 2 Tutorial 2: Channel Capacity 1. Two identical binary symmetric channels with transition probability p are connected in cascade. i) Draw the original channel diagram. ii) Find the overall channel matrix of the resultant channel and then draw the equivalent channel diagram. 2. Find the value of conditional entropy for a noiseless binary channel. 3. A telephone line channel has a bandwidth of 3 kHz and a S/N = 1500 at the channel output
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regression line Week 5 (9/24‚ 9/26) • QUIZ 2 on Monday 9/23 on Chapters 5‚ 8‚ 9 (in lab) • Reading: chapters 13‚ 14‚15; SG 12‚ 17‚ 18‚ 19 • Probability‚ conditional probability‚ Bayes’ rule‚ binomial distribution Week 6 (10/1‚ 10/3) • Reading: chapter 15; SG 20‚ Notes on chance variables by Prof. Roger Purves • Continue probability‚ some discrete distributions (geometric‚ negative binomial‚ hypergeometric). Week 7 (10/8‚ ‚10/10) • MIDTERM 1 on Tuesday 10/8 on Chapters 1-5‚ 8-15
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Assignment Week 1 Answer the following questions: 1. Describe the rationale for utilizing probability concepts. For practical reasons‚ variables are observed to collect data. The sampled data is then analyzed to elicit information for decision making in business and indeed in all human endeavors. However‚ sampled information is incomplete and not free from sampling error. Its use in decision-making processes introduces an element of chance. Therefore‚ it is important for a decision-maker
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CHAPTER 3 ASSIGNMENT DESCRIBING DATA: NUMERICAL MEASURES Part I Select the correct answer and write the appropriate letter in the space provided. c 1. The arithmetic mean is computed by a. finding the value that occurs most often. b. finding the middle observation and dividing by 2. c. summing the values and dividing by the number of values. d. selecting the value in the middle of the data set. c 2. To compute the arithmetic mean at least the a. nominal level of measurement is required
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ECE 4110: Random Signals in Communications and Signal Processing ECE department‚ Cornell University‚ Fall 2013 Homework 2 Due September 20 at 5:00 p.m. 1. (Chebyshev Inequality) Let X1 ‚ . . .‚ X be independent Geometric random variables with parameters p1 ‚ . . . ‚ p respectively (i.e.‚ P (Xi = k) = pi (1 − pi )k−1 ‚ k = 1‚ 2‚ . . .). Let random variable X to be X= i=1 Xi . (a) Find µX = E[X]. (b) Apply the Chebyshev inequality to upper bound P (|X − µX | > a). Evaluate your upper bound
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Accordingly‚ reliability analysis and evaluation is applied to the Markov model of these changing systems operation states. In this model‚ the variability of system components reliability characteristics is pointed by introducing the components’ conditional reliability functions determined by the system operation states. The engine system of the vessel is simplified as shown in Figure 1 to illustrate the application. ME A/E S A/E P Figure 1. Simplified system reliability block diagram
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precise calculations and mechanical applications of formulas will be relegated to calculators and computer software. Course Learning Objectives At the end of the course‚ students should have mastered the syllabus topics‚ which cover fundamental probability and statistical concepts‚ theory‚ solution methods and application areas‚. Students will also learn to infer from the quantitative results to give a real-life interpretation to what the numbers mean‚ and how the results impact the decisions.
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