Paper Reference(s) 6683/01 Edexcel GCE Statistics S1 Advanced/Advanced Subsidiary Wednesday 24 May 2006 ( Afternoon Time: 1 hour 30 minutes Materials required for examination Items included with question papers Mathematical Formulae (Green) Nil Candidates may use any calculator EXCEPT those with the facility for symbolic algebra, differentiation and/or integration. Thus
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journey times. [3] John's journey times had a mean of 79.7 minutes and a standard deviation of 6.22 minutes. Describe briefly, in everyday terms, how Janet and John's journey times compare. [2] 3. The random variable X is normally distributed, with mean and standard deviation each equal to a. It is given that P(X < 3) = 0.25. i. Find the value of a. [4] ii. Hence find P(X <12). [2] 4. A blue unbiased cubical
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Chapter 1 1. The specific statistical methods that can be used to summarize or to describe a collection of data is called: A. Descriptive statistics B. Inferential statistics C. Analytical statistics D. All of the above 2. The _________________ random variables yield categorical responses so that the responses fit into one category or another. A. Quantitative B. Discrete C. Continuous D. Qualitative 3. Which of the following is a qualitative/categorical variable? A. The number of pets
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* 7,000,000 – (22,999,999/23,000,000) * 1 = - $0.70 In the long run, if I buy $1 Lotto tickets in anticipation of winning the $7 million grand prize, I can expect to lose $0.70 for each Lotto ticket I purchase. 4. a) x is a binomial random variable because • The experiment consists of 5 identical trials of bottled water brands • There are only two possible outcomes for each trial (purified vs. tap water) • Probability of tap water brands remains the same from trial to trial (p =
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words, discuss the differences between discrete and continuous random variables because the statistical analysis of each type of variable is different. Discrete Variable – This type of variable is only in the form of a particular value, and does not consider any values that may fall in between each particular value. The example that I would provide here would be that I have two children. I do not have 2.8 children. Continuous Random Variable - This type of variable can take on any value that
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ECO 3410 19 June 2014 Answer 1 a) Consider the experiment of a worker assembling a product. We can define a random variable as x equals to the time in minutes to assemble the product b) The possible outcomes for this experiment is the worker may assemble the product from the first second to whatever how long it takes him or her to assemble the product. Therefore, the random variable x may assume any number greater than zero in minutes, meaning any positive number. It can be noted as x >
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A1 a-d A1a A1b A1c A1d Trial Random # Materials Cost Per Unit Trial Random # Labor Cost Per Unit Trial Random # Utilities Cost Per Unit Total Cost Per Unit 1 74 $38.00 1 2 $22.00 1 5 $3.00 $63.00 2 57 $38.00 2 77 $28.00 2 42 $4.00 $70.00 3 67 $38.00 3 15 $22.00 3 65 $6.00 $66.00 4 41 $35.00 4 31 $24.00 4 75 $6.00 $65.00 5 28 $35.00 5 44 $24.00 5 65 $6.00 $65.00 6
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SOCIETY OF ACTUARIES/CASUALTY ACTUARIAL SOCIETY EXAM C CONSTRUCTION AND EVALUATION OF ACTUARIAL MODELS EXAM C SAMPLE QUESTIONS The sample questions and solutions have been modified. This page indicates changes made to Study Note C-09-08. January 14, 2014: Questions and solutions 300–305 have been added. July 8, 2013: Questions and solutions 73A and 290–299 were added. Question and solution 73 were modified. Question 261 was deleted. August 7, 2013: Solutions to Questions 245, 295, and 297
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that are probabilistic. Steps: * Establish the probability distribution for each random variable. * Use random numbers to generate random values. * Repeat for some number of replications. Probability Distributions: Historical data Goodness-of-fit tests for common distributions: * Normal * Uniform * Exponential * Poisson * Binomial Role of Computers: * Built-in random number procedures for simulating from several different probability distributions.
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Chapter 5 Quiz Review: Probability Distributions & Expectation **Are the following valid probability distributions? (yes or no) If not, state a reason. 1) |X |30 |31 |32 |33 |34 | |P(X) |0.35 |0.21 |0.38 |0.25 |0.11 | Σ X = 0.35 + 0.21 + 0.38 + 0.25 + 0.11 = 1.3 ≠ 1 No, the sum of
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