number of draws is very large. a. we can use the binomial formula to compute the chance of getting exactly 3 ones in 10 draws. b. both (a) and (c) are true. a. both (a) and (b) are true. 3. When thinking about sample surveys we should remember, a. a parameter is a numerical fact about a sample, subject to chance variation. b. the researcher uses the population to compute a statistic. c. that the parameter may be subject to sampling bias. d. simple random sampling
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I took the Cumulative Probability and the Repair Time in Days, named it Repairs. This will assist me later in finding the random numbers for the number of days the possibility of the copier breaking down. I choose to do 30 days because all months except one have 30 days in them. I also used the process of VLOOKUP, the equation =VLOOKUP (F5, Repair,2). Taking the random function (=rand), I received this for the first day randomized number as well as the number of days it took to repair in the
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1.1 Intro to the Practice of Statistics Statistics is the science of collecting, organizing, summarizing, and analyzing information to draw conclusions or answer questions. In addition, statistics is about providing a measure of confidence in any conclusions. Process of statistics p.6 1. Identify the research objective 2. Collect the data needed to answer the question #1 3. Describe the data 4. Perform inference Parameter & Statistic Population - the entire group of individuals
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74537_05_ch05_p215-264.qxd 10/8/12 4:04 PM Page 215 CHAPTER Discrete Probability Distributions CONTENTS STATISTICS IN PRACTICE: CITIBANK 5.1 RANDOM VARIABLES Discrete Random Variables Continuous Random Variables 5.2 DEVELOPING DISCRETE PROBABILITY DISTRIBUTIONS 5.3 EXPECTED VALUE AND VARIANCE Expected Value Variance 5.4 BIVARIATE DISTRIBUTIONS, COVARIANCE, AND FINANCIAL PORTFOLIOS A Bivariate Empirical Discrete Probability Distribution Financial Applications Summary 5.5 BINOMIAL PROBABILITY
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events and their probabilities requires a framework for representing events of interest in terms of a random experiment. Our textbook tells us how to describe such an experiment in terms of a set of outcomes Ω called a sample space, and to represent events as subsets of Ω. A basic problem in this regard is as follows. Problem 1 Sample Spaces and Events as Sets Given a verbal description of a random experiment and certain events of interest, represent the sample space as a set Ω, and identify the events
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these are =SUM() = RAND() =AVERAGE() =STDV() =RANDINV() =VLOOKUP() and few more . These are widely used function 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
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STATISTICAL METHODS STATISTICAL METHODS Arnaud Delorme, Swartz Center for Computational Neuroscience, INC, University of San Diego California, CA92093-0961, La Jolla, USA. Email: arno@salk.edu. Keywords: statistical methods, inference, models, clinical, software, bootstrap, resampling, PCA, ICA Abstract: Statistics represents that body of methods by which characteristics of a population are inferred through observations made in a representative sample from that population. Since scientists
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DESCRIPTIVE STATISTICS & PROBABILITY THEORY 1. Consider the following data: 1, 7, 3, 3, 6, 4 the mean and median for this data are a. 4 and 3 b. 4.8 and 3 c. 4.8 and 3 1/2 d. 4 and 3 1/2 e. 4 and 3 1/3 2. A distribution of 6 scores has a median of 21. If the highest score increases 3 points, the median will become __. a. 21 b. 21.5 c. 24 d. Cannot be determined without additional information. e. none
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better idea is to bring 10 golf balls to class. Six should be white and 4 orange (yellow). Mark a big letter or number on each to correspond to Figure 2.3 and draw the balls from a clear bowl to make the point. You can also use the props to stress how random sampling expects previous draws to be replaced. Teaching Suggestion 2.6: Concept
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* Definition of overconfidence In business or trading, an overestimation of one's abilities and of the precision of one's forecasts. Overconfident people set overly narrow confidence intervals in making predictions. They tend to overweigh their own forecasts relative to those of others. The self-serving attribution bias, under which individuals attribute past successes to their own skills and past failures to bad luck, can lead to overconfidence. In the context of financial markets, the confidence
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