1.PERCENT ● DEFINITION OF PERCENT - Percent means parts per 100 The symbol is % Example: 25% means 25 per 100 ● CONVERSION TECHNIQUES - ✔Changing percent to decimal Change a percent to a decimal. Move the decimal point two places to the left. In a percent‚ the decimal point would come at the end of the last number (for 75%‚ envision that it looks like 75.) Examples: 75% converts to .75 40% converts to .40 3.1% converts to .031 ✔Changing decimal or whole number to percent Change a decimal
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ARITHMETIC LOGIC UNIT Submitted By‚ M.GOVINDHASAMY. K.GOWTHAM. K.A.GOWTHAMRAJ. ARITHMETIC LOGIC UNIT AIM: To verify the Function table of 4 bit ALU. APPARATUS REQUIRED:
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1 “Arithmetic vs. Geometric Means: Empirical Evidence and Theoretical Issues” by Jay B. Abrams‚ ASA‚ CPA‚ MBA Copyright 1996 There has been a flurry of articles about the relative merits of using the arithmetic mean (AM) versus the geometric mean (GM). The Ibbotson SBBI Yearbook took the first position that the arithmetic mean is the correct mean to use in valuation. Allyn Joyce’s June 1995 BVR article initiated arguments for the GM as the correct mean. The previous articles have centered
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Guessing the Bounce Plate Affect Abstract The goal behind this experiment was to estimate the distance a ball would travel after it falls a certain distance and bounces off a metal plate which has an angle of 45 degrees. To find this we had to take the basic equations for kinematics which are (1/2)at2=x and v=v0+at and combine them to make an equation that will help us solve for the distance the ball will travel after hitting the bounce plate. The equation came out to be R=g*(sqrt(2)/sqrt(g))*(sqrt(H)*sqrt(h))
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PART A: i) Male: Female: The mean value of life satisfaction for male is about 7.7459 while for female is 7.7101‚ which proves there is no significant different life satisfaction between male and female‚ thus gender does not affect life satisfaction a lot. But when it comes to sample variance‚ for male is 2.5684 while for female is 3.0081. From this pair of figures it is obvious that the life satisfaction for female is more flexible than male. Man’s life satisfactions are easy to be affected
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For each item below: Identify the type of data (quantitative - discrete‚ quantitative - continuous‚ or qualitative) that would be used to describe a response. Give an example of the data. • Quantitative – Discrete: Data obtained that are discrete numbers. e.g. 1‚ 2‚ 3... • Quantitative – Continuous: Data from a population that is assumed to be measured accurately. • Qualitative : Categorization or description attributes of a population. e.g. red‚ blue‚etc • Number of tickets sold to
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Answer the following problems showing your work and explaining (or analyzing) your results. 1. Describe the measures of central tendency. Under what condition(s) should each one be used? Mean- Works good when it comes to test scores Median- should be used when describing something like average income. Mode= is good is you want to see what is you best seeing product in a store situation. 2. Last year‚ 12 employees from a computer company retired. Their ages at retirement are listed below.First‚
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Section: Arithmetic Reasoning 1) At Joe’s Restaurant‚ one-fourth of the patrons are male and one-fifth of the patrons are from out of town. What proportion would you expect to be male and out of town? 1/5 1/10 1/20 1/25 1/50 2) There are 112 male and 78 females working at a hospital. What percentage of the hospitals workforce is female? 22% 32% 38% 41% 78% 3) What is the estimated product when 620 and 374 are rounded to the nearest hundred
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Chapter 3‚ Problem 3 Using published sources (for example‚ The Wall Street Journal‚ Barron’s‚ Federal Reserve Bulletin)‚ look up the exchange rate for U. S. dollars with Japanese yen for each of the past 10 years (you can use an average for the year or a specific time period each year). Japanese Yen to U. S. Dollar (Retrieved from http://research.stlouisfed.org/fred2/data/EXJPUS.txt ) Date Example - Japan Stock Price in Yen Example -
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Measuring Service Quality Using SERVQUAL Introduction Measuring the quality of a service can be a very difficult exercise. Unlike product where there are specific specifications such as length‚ depth‚ width‚ weight‚ colour etc. a service can have numerous intangible or qualitative specifications. In addition there is there expectation of the customer with regards the service‚ which can vary considerably based on a range of factors such as prior experience‚ personal needs and what other people
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