can be highly skewed and non-normal. Even if it is symmetrical it may not be normal but other distribution like t-distribution. A normal random variable is a popular example of a continuous random variable‚ but a continuous r.v. need not be normal. 6. The standard deviation of a standard normal distribution is always equal to 1. True. Its mean is zero and variance (or std deviation) equal to 1.7. If the sample size is as large as 1000‚ we can safely use the normal approximation to binomial even
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a. Is it reasonable that the distribution of checking account balances approximates a normal distribution? Yes. Its reasonable because the sample size is large and and n -( increases the distribution of checking account balances approximates normal distribution. b. Determine the mean and the standard deviation for the sample of 60 customers. |Mean = |1516.667 | |Variance= |2637500 | |Std dev= |1624.038 | c. Compare the actual distribution
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From this case‚ there are two types of errors‚ which the consortium can make. A Type I Error is referred to as a “false positive.” A Type I error would be made when the null hypothesis is rejected when it should be accepted. This error may occur if the consortium defends any lawsuit against them if they are using 6% (6/100) as their surveying result. The results of the sample size of 100 people indicate that the percentage range is from 1.35% to 10.65%. The test results can be higher than 10%‚ but
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rate‚ “every moment dies a man‚ and 11/16 is born‚ and according to the rate of death and birth rate‚ we can predict the total population in several years. Statistic can also be used in people’s daily life. The height of the women has a approx. normal distribution so we can predict the range of women’s height of a country. We can also find out the median and mean of the women’s height. Because we have statistic‚ people found out that smoking rate reflects the rate of cancer -- people have smoking
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com/a/putraintelek.edu.my/putrainfozone/documents Appendix – any attachments relevant to the assignment. Page margin: Top Bottom Left Right Font type: Font size: : : : : 2.5cm / 1inch 2.5cm / 1inch 3.0cm / 1.2inch 2.5cm / 1inch Times New Roman Normal fonts – 12 Title fonts – 14 Bold (No underline) Line spacing – 1.5 Paragraph: One paragraph must have at least 9 sentences. Justify the paragraph .................. .................. .................. .................. PUTRA INTELEK INTERNATIONAL
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Introductory Business Statistics Econ 231 CRN 32698 Summer 2013 Jan Wolcutt Text: Basic Statistics for Business & Economics‚ 7th Edition by Lind‚ Marchal‚ and Wathen. McGraw-Hill-Irwin‚ 2010. The study guide is optional. You will also be required to buy econnect to do homework assignments and download files from Blackboard. The cheapest way to do this is to buy directly from McGraw
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CONFIDENTIAL CS/JAN 2012/QMT500 UNIVERSITI TEKNOLOGI MARA FINAL EXAMINATION COURSE COURSE CODE EXAMINATION TIME STATISTICS FOR ENGINEERING QMT500 JANUARY 2012 3 HOURS INSTRUCTIONS TO CANDIDATES 1. This question paper consists of five (5) questions. 2. Answer ALL questions in the Answer Booklet. Start each answer on a new page. Do not bring any material into the examination room unless permission is given by the invigilator. Please check to make sure that this examination pack
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tests‚ such as a “two sample T-test”‚ a “paired sample T-test” or a “two sample Z test.” In order for a one way Analysis of Variance F test to be conducted‚ the following conditions must be met: (1) Each sample must be selected from a normal‚ or approximately normal‚ population. (2) The samples must be independent and randomly selected. (3) Each population must have the same variance. Looking at the conditions stated above‚ all the samples provided by the Toronto Real Estate Board reflect data from
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MFE MATLAB Function Reference Financial Econometrics Kevin Sheppard October 30‚ 2009 2 c 2001-2009 Kevin Sheppard Contents Notes v 1 Included but not documented functions 1 2 Cross Sectional Analysis 5 2.1 Regression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.1.1 3 Regression: ols Stationary Time Series 3.1 ARMA Simulation . . . . . . . . . . .
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head‚ to see patterns developing on the wall‚ I was totally confused. A little girl peeped her head around the old wall and ran to attack me. I knew it was one of my nieces. The first thing I had noticed was she obviously hadn’t developed the way a normal girl her age would have. I called the police and managed to stutter the address. During the mean time I was studying the forever changing patterns on the wall. The two girls were running their hands along the wall as if the wall
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