Introduction: The purpose of this lab is to apply Mendel’s laws to predict the probability of the occurrence of a single event‚ of two independent events and of certain traits in offspring of parents exhibiting traits. Gregor Mendel was an Austrian monk in 1866‚ who studied how traits were passed using pea plants. From his studies of inheritance‚ he created three laws of inheritance: the law of dominance‚ the law of segregation‚ and the law of independent assortment. He called genes ‘’factors’’
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Executive Summary The report investigates on how Royal Dutch Shell should reduce the issues of oil spill by utilizing two managerial functions which are leading and controlling. This problem is primarily due to the operational failures‚ such as equipment failure and human error. It is found that Shell has been engaged in solving issue that significantly disadvantageous for Shell. In response to these incidents‚ Shell was forced to solve these issues as soon as possible. This report includes investigation
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classical and empirical probabilities. a. Classical probabilities are based on assumptions; Empirical probabilities are based on observations. b. Classical probabilities do not require an action to take place; Empirical probabilities have to have been “performed”. 2) Gather 16 to 30 coins. Shake and empty bag of coins 10 times and tally up how many head and tails are showing. Number of coins: 20 * Consider the first toss‚ what is the observed probability of tossing a head? Of
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Ans.1: Non-Probability Sampling: When the units of a sample are chosen so that each unit in the population does not have a calculable non-zero probability of being selected in the sample‚ this is called Non-Probability Sampling. Also‚ Non-probability sampling is a sampling technique where the samples are gathered in a process that does not give all the individuals in the population equal chances of being selected. In contrast with probability sampling‚ non-probability sample is not a product
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Chapter 6 Continuous Probability Distributions Case Problem: Specialty Toys 1. Information provided by the forecaster At x = 30‚000‚ [pic] [pic] Normal distribution [pic] [pic] 2. @ 15‚000 [pic] P(stockout) = 1 - .1635 = .8365 @ 18‚000 [pic] P(stockout) = 1 - .3483 = .6517 @ 24‚000 [pic] P(stockout) = 1 - .7823 = .2177 @ 28‚000 [pic]
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Question 1 – Develop an awareness of the client situation (a) List five (5) topics you would discuss with Sarah and Stan at your first meeting. Why are these topics important? Give a brief reason for the need to discuss each topic. (Each discussion topic: 1 mark each ‚ Reason: 1 mark each) 10 marks 1. Personal Details As a financial planning organisation we are subject to certain legislative and regulatory requirements which necessitate us to obtain personal information about Sarah
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Probability Games Walter J Mahoney MTH 157 1/20/2013 Andrea Hayes Probability is a fascinating math concept. It can be applied in many aspects of our students’ daily lives. As the world of technology continues to grow‚ teaching of many math
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Probability Distribution Memo To: Howard Gray‚ CEO; Jean Dubois‚ VP Mechanical Watch Division; Uma Gardner‚ VP Production; Amanda Hamilton‚ VP Marketing After identifying the business problem of falling sales and an increase in rejections by the Swiss Official Chronometer Control‚ conducting a study for research will prove to identify a solution. Researchers performed a study of a sample population of 500 people. The study reveals 60% of the watches purchased are certified and the average
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Even if the sample size is more than 1000‚ we cannot always use the normal approximation to binomial. Solution: If a sample is n>30‚ we can say that sample size is sufficiently large to assume normal approximation to binomial curve. Hence the statement is false. #2 A salesperson goes door-to-door in a residential area to demonstrate the use of a new Household appliance to potential customers. She has found from her years of experience that after demonstration‚ the probability of purchase
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Strict Liability for Defective Products - Part X of the CPA 1999 Section 68(1) provides that where any damage is caused wholly or partly by a defect product‚ the following persons shall be liable for the damage. The plaintiff only has to prove damage or defect in the product. Part X of CPA does not cover every product. Section 66 provides types of product such as goods and component parts and raw materials. Section 3 provides definition of goods. Only the goods which are purchased for private and
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