mass of the liquid‚ which was 14.21g per mole. The next part was used to determine the density of the volatile liquid. First the volatile liquid was placed in a pyncometer and massed; water was then placed in the same (now clean and empty) pyncometer and massed. The density equation was manipulated using the data for water to solve for the mL of the capillary tube. This new information was used to find the density of the liquid‚ which was 1.33g/mL. The last part of the experiment was used to determine
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478‚761 ways b. What is the probability of winning a prize of $200‚000 by matching the numbers on the five white balls? The probability of winning the $200‚000 prize is since the outcomes of an equal probability of winning c. What is the probability of winning the Powerball jackpot? The Probability of winning the Jackpot is 14. An experiment has four equally likely outcomes: E1‚ E2‚ E3‚ and E4. a. What is the probability that E2 occurs? b. What is the probability that any two of the outcomes
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variables‚ all of which are well known; see Hogg and Tanis [6]. A random variable X has a chi-square distribution with n degrees of freedom if it is a gamma random variable with parameters m = n/2 and = 2‚ i.e X ~ (n/2‚2). Therefore‚ its probability density function (pdf) has the form (1) f(t) = f(t; n) = In this case we shall say X is a chi-square random variable with n degrees of freedom and write X ~ (n). Usually n is assumed to be an integer‚ but we only assume n > 0. Proposition
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emerging techniques. These topics are introduced in brief below 1. Historical Background 1.1. Basic Definitions Software reliability is centered on a very important software attribute: reliability. Software reliability is defined as the probability of failure-free software operation for a specified period of time in a specified environment (ANSI‚ 1991). We notice the three major ingredients in the definition of software reliability: failure‚ time‚ and operational environment. We now define
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of the buffer is determined such that the probability of running out of stock during lead time (the period between placing and receiving an order) does not exceed a prespecified value. Let L = Lead time between placing and receiving an order [pic] = Random variable representing demand during lead time [pic] = Average demand during lead time [pic]= Standard deviation of demand during lead time B = Buffer stock size a = Maximum allowable probability of running out of stock during lead time
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predictor: the formation mechanism of this expectation takes into account the market equilibrium price while considering that the current price will converge to it only in the long run. The representative entrepreneur chooses the backward predictor with probability q ( 0 < q < 1 ) and
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Experiment 7: Relative Density Laboratory Report Marella Dela Cruz‚ Janrho Dellosa‚ Arran Enriquez‚ Alyssa Estrella‚ Zacharie Fuentes Department of Math and Physics College of Science‚ University of Santo Tomas España‚ Manila Philippines Abstract The experiment was conducted to show the different methods on how to determine an object’s composition through its density and to determine an object’s density by displacement method and the Archimedes Principle. Results show that. The materials
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Density Lab January 24‚ 2014 Benjamin I. Purpose- The purpose of this lab is to identify the unknown substances by calculating the densities of the given substances then comparing those densities to the actual densities on the table given. II. Materials- Graduated cylinders Triple beam balance Unknown substances from bag given by teacher Table of known densities Calculator Water III. Procedure- The first thing one must do to identify which substance is which is to calculate the
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acquaint the students with basic laboratory procedures‚ methods‚ and techniques; to introduce the use of basic laboratory measuring devices; to demonstrate different methods of manipulation of numerical quantities. DENSITY AND SPECIFIC GRAVITY Materials and Methods Part 1: Density of an Unknown Solid 1. We first were asked from our laboratory instructor to attain an unknown solid and were asked to note down the number of the solid. 2. Determine the mass of the unknown solid to the
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a continuous random variable: E ( X ) = ∫All x x f ( x ) dx If X is a discrete random variable: n E ( X ) = x1 p1 + ... + xn pn = ∑ xi pi xi i =1 = all possible values of X f(x) = the probability density function‚ p.d.f xi = all possible values of X pi = the probability associated with it n = the number of observations Note
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