4. Risk Analysis 4.1. Objectives of Risk Analysis Typically‚ a project’s qualitative risk assessment will recognize some risks whose occurrence is so likely or whose consequences are so serious that further quantitative analysis is warranted. A key purpose of quantitative risk analysis is to combine the effects of the various identified and assessed risk events into an overall project risk estimate. This overall assessment of risks can be used by the transportation agency to make go/no-go decisions
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means‚ which could be used to in conjunction ANOVA and t test reporting. The d=.90 can be revealed using Cohen’s d by dividing the mean difference in the boy and girl’s self-esteem scores by the standard deviation. In addition to this method‚ mean one less mean two divided by a pooled standard deviation could be used (Lind‚ 2011). Reference: Lind‚ D. (2011). Business Statistics for Business and Economics (7thth ed.). New York City‚ NY: McGraw Hill. Nelson‚ J. A. P.‚ Young‚ B. J
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True/False Questions 1. The standard deviation of any normal random variable is always equal to one. Answer: False Type: Concept Difficulty: Easy 2. For any normal random variable‚ the probability that the random variable will equal one is always zero. Answer: True Type: Concept Difficulty: Medium 3. The graph of a standard normal random variable is always symmetric. Answer: True Type: Concept Difficulty: Easy 4. The formula will convert any normal
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intelligence test is 100‚ and the standard deviation is 16. The mean for the creativity test is 115‚ and the standard deviation is 14. What statistic would you use to compare the two scores from these two different distributions (the intelligence test distribution and the creativity test distribution)? Compute this statistic and determine on which test‚ if either‚ the student performed better. Explain your answer. (10 pts) Intelligence test score = 123‚ mean = 100‚ standard diviation = 16 Creativity
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Statistics Course Project Part 1 Student: Zissis Koukoutaris Course : Statistics Professor: Dimitrios Fotiadis Semester: Fall-2012 Introduction This report is written by Koukoutaris Zissis a student from Northeastern University. Mr Fotiadis my professor of the MGSC 23021 assigned me the task. 1. Use methods of descriptive statistics to summarize the data. Comment on the findings 2. Develop estimated regression equations‚ first using annual income as the independent variable
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LAB 5: Coliform bacteria in surface waters I. Introduction Many organisms‚ including humans‚ have symbiotic bacteria in their guts that aid digestion. Symbiosis is an intimate relationship between different organisms in which both the host organism‚ e.g. the human‚ and the symbiote‚ e.g. bacteria‚ benefit from each other. In this case‚ the bacterium gets a favorable environment and food source in the intestines of a human. In return‚ these bacteria improve the digestibility of food through
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nominal variables will be explored and discussed in regards to a possible fractional value. In order to understand how to interpret the quantitative data collected‚ statistical methods are introduced in this lab. The use of methods such as mean‚ standard deviation‚ and range are used to interpret results of what may be closely related to the “true” value of a measurement. The mean is the average of a set of
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describe by ratio data that can be described by using mean‚ range‚ and standard deviation. it is also called as interval/ratio level data 3. What other statistic could have been used to describe the length of labor? Provide a rationale for your Answer. Nominal level data could be used to describe the length of labor. This would have done by using frequencies‚ percentages‚ and mode instead of using mean‚ range‚ and standard deviation 4. Were the distributions of scores similar for the experimental
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the 52nd percentile is .05 A normally distributed variable has a mean of 10 and a standard deviation of 2. The probability that a value between 7 and 9 is obtained is .2417 An accelerated life test on a large number of type-D alkaline batteries revealed that the mean life for a particular use before they failed is 19.0 hours. The distribution of the lives approximated a normal distribution. The standard deviation was 1.2 hours. About 95.44% of the batteries failed between what two values? 16.6
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level of measurements? Age‚ Income‚ Length of labor‚ Return to work and number of hours working per week. 2. What statistics were used to describe the length of labor in this study? Mean and standard deviation were used to describe the length of labor. These were appropriate since mean and standard deviation can be calculated on an interval level of measurement. 3. What other statistics could have been used to describe the length of labor? Provide a rationale for your answer? Range could also be
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