"Calculate the mean and standard deviation of the probability distribution created by rolling a die either show work or explain how your answer was calculated" Essays and Research Papers

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    What is the mean age of this sample? What is the standard deviation? The mean age is 47.5 years old. The standard deviation is 10.74832 years. http://www.calculator.net/standard-deviation-calculator.html Sample Standard Deviation‚ s: 10.748316881702 Sample Standard Variance‚ s2 115.52631578947 Total Numbers‚ N 20 Sum: 950 Mean (Average): 47.5 Population Standard Deviation‚ σ 10.476163419878 Population Standard Variance‚ σ2 109.75 If it follows the normal distribution The 68.3%

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    STANDARD DEVIATION The standard deviation is a popular measure of variability. It is used both as a separate entity and as a part of other analyses‚ such as computing confidence intervals and in hypothesis testing. The standard deviation is the square root of the variance. The population standard devia¬tion is denoted by σ. Like the variance‚ the standard deviation utilizes the sum of the squared deviations about the mean (SSx). It is computed by averaging these squared deviations (SSX/N) and

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    Standard deviation is the square root of the variance (Gravetter & Wallnau‚ 2013). It uses the mean of the distribution as a reference point and measures variability by considering the distance of each score from the mean. It is important to know the standard deviation for a given sample because it gives a measure of the standard‚ or average‚ range from the mean‚ and specifies if the scores are grouped closely around the mean or are widely scattered (Gravetter & Wallnau‚ 2013). The standard deviation

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    Statistics Chapter 5 Some Important Discrete Probability Distributions 5-1 Chapter Goals After completing this chapter‚ you should be able to:  Interpret the mean and standard deviation for a discrete probability distributionExplain covariance and its application in finance  Use the binomial probability distribution to find probabilities  Describe when to apply the binomial distribution  Use Poisson discrete probability distributions to find probabilities 5-2 Definitions Random Variables  A

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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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    Remington’s Steakhouse Project Brian Jones Research Methods & Applications Dr. Jones August 25‚ 2011 Table of Contents Table of Contents 2 List of Tables 3 Introduction 4 The Research Objectives 4 The Research Questions 5 Literature Review 6 Answers to Research Questions 8 Recommendations to Remington’s 15 References 18 Annotated Bibliography 19 Appendix(ces) 22 List of Tables Table 1 Demographic Description of the Average Remington’s Patron9 Table 2 Reported Income by Remington’s Questionnaire

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    95‚ 101‚ 94‚ 92‚ 99‚ 101‚ 97‚ 94‚ 97‚ 102‚ 61. The claim can be rejected; correct answer may be either above 98 or below it. 2. Salaries for Actuaries nationwide graduates entering the actuarial field earn $40‚000. A college placement officer feels that this number is too low. She surveys 36 graduates entering the actuarial field and finds the average salary to be $41‚000. The population standard deviation is $3000. Can her claim be supported at 0.05? x¯=14.7‚ μx¯=13.77‚ ox¯=5.34‚ n=29

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    Shows the values that a variable can take and the number of observations associated with each value b. Expresses the arithmetic average of a frequency distribution c. Indicates the typical value of a frequency distribution d. Represents the midpoint of a frequency distribution e. Comparing quantities where x and y are completely independent of each other or x can be included in y f. Represents the simplest measure of spread (or variability) g. Indicates the most frequent observation in a frequency

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    The Poisson probability distribution‚ named after the French mathematician Siméon-Denis. Poisson is another important probability distribution of a discrete random variable that has a large number of applications. Suppose a washing machine in a Laundromat breaks down an average of three times a month. We may want to find the probability of exactly two breakdowns during the next month. This is an example of a Poisson probability distribution problem. Each breakdown is called an occurrence in Poisson

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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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