"Quartile deviation" Essays and Research Papers

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    calculate: =NORMDIST(5.5‚1.88‚1.99‚True) X= 5.5 Mean= 1.88 Standard Deviation=1.19 b) 32 to 35 weeks = 43.83% The NORMDIST formula was used to calculate: =NORMDIST (5.5‚5.73‚1.48‚True) X= 5.5 Mean= 5.73 Standard Deviation=1.48 c) 37 to 39 weeks = 4.66% The NORMDIST formula was used to calculate: =NORMDIST(5.5‚7.33‚1.09‚ True) X= 5.5 Mean= 7.33 Standard Deviation=1.09 d) 42 weeks and over = 2.75% The NORMDIST formula was used to

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    surplus/deficit. There is a huge standard deviation in the data given for GDP. In both 2009 and 2010 the standard deviation was over four and a half times larger than the average of GDP itself. This will make it hard to create general assumptions for all countries to assess whether different factors correlate with each other. Even other factors such as GDP growth have relatively large standard deviations. GDP growth has a very large standard deviation. An example of ambiguous data can be seen when

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    Chi-squared Analysis Problem Sets • Exercises 19 and 20 (Ch. 17) Chapter 10 31. A new weight-watching company‚ Weight Reducers International‚ advertises that those who join will lose‚ on the average‚ 10 pounds the first two weeks with a standard deviation of 2.8 pounds. A random sample of 50 people who joined the new weight reduction program revealed the mean loss to be 9 pounds. At the .05 level of significance‚ can we conclude that those joining Weight Reducers on average will lose less than 10

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    Big Data

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    Introduction to Basic Statistics Pat Hammett‚ Ph.D. 2005 Instructor Comments: This document contains an overview of basic probability and statistics. It also includes a practice test at the end of the document. Note: answers to the practice test questions are included in an appendix. 1 Pat Hammett University of Michigan Table of Contents 1. VARIABLES- QUALITATIVE AND QUANTITATIVE......................3 1.1 Qualitative Data (Categorical Variables or Attributes) .............

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    Merrill Finch Inc.

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    8 – 23 MERRILL FINCH INC. RISK AND RETURN a. (1) Why is T-bill’s return independent of the state of the economy? Do T-bill’s promise a completely risk-free return? Explain (2) Why are High Tech’s returns expected to move with the economy‚ whereas‚ Collections’ are expected to move counter to the economy? 1. The 5.5% T-bill return does not depend on the state of the economy because the Treasury must redeem the bills at par regardless of the state of the economy; therefore‚ T-bills are

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    Inferential Statistics

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    Inferential Statistics Drawing Conclusions based on Samples Introduction This chapter introduces how you can use data from a sample to draw conclusions about the larger population from which the sample was taken. Data often arises from the results of a survey of individuals. For example‚ the management of a fast food chain might be interested in determining the total number of dollars that Baylor students spend each year eating in Waco fast food restaurants. The fast food chain would

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    The average (mean) annual income was less than $50‚000‚ One-Sample Z: Income ($1000) Test of mu = 50 vs < 50 The assumed standard deviation = 14.64 95% Upper Variable N Mean StDev SE Mean Bound Z P Income ($1000) 50 43.74 14.64 2.07 47.15 -3.02 0.001 α 0.05= -1.645 H0 μ = 50‚000 Ha μ < 50‚000 The hypothesis test claims that the average annual income was less than $50‚000. H0 claims equal

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    Mutual Funds

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    FINANCE 411 – SUMMER 2012 ASSIGNMENT 2 DUE DATE: June 4‚ 2012 [Submit a Hard Copy and via Drop Box; Keep a copy ] http://www.globefund.com/ http://www.globefund.com/review/ http://globefunddb.theglobeandmail.com/gishome/plsql/gis.co_search 1. Choose 1 fund from the Globe and Mail 15-Year Mutual fund Review issue [on internet] as follows: 1. fund names start with the same letter as your surname [or as close as possible] 2. 1 Canadian

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    N * Population standard deviation = σ = sqrt [ Σ ( Xi - μ )2 / N ] * Population variance = σ2 = Σ ( Xi - μ )2 / N * Variance of population proportion = σP2 = PQ / n * Standardized score = Z = (X - μ) / σ * Population correlation coefficient = ρ = [ 1 / N ] * Σ { [ (Xi - μX) / σx ] * [ (Yi - μY) / σy ] } Statistics Unless otherwise noted‚ these formulas assume simple random sampling. * Sample mean = x = ( Σ xi ) / n * Sample standard deviation = s = sqrt [ Σ ( xi - x )2 /

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    Session III Quiz

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    quiz‚ paper‚ test]. 2 Pg 212 #14) A normal population has a mean of 12.2 and a standard deviation of 2.5. A) Compute the z value associated with 14.3. - z = (14.3 – 12.2)/2.5 z value is .84 B) What proportion of the population is between 12.2 and 14.3? - Looking for .84 on the curve ti would be .2995 C) What proportion is less than

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