combination of items we call a market basket. Consumption of the bundle of goods in a market basket brings satisfaction to the buyer. Buyers choose between different bundles of goods‚ different market baskets‚ on the basis of the satisfaction they are expected to bring. A model of consumer ’s as buyers is based on three assumptions. 1. Axiom of Completeness Given two market baskets‚ A and B‚ a consumer will know whether she prefers A to B (written as A » B)‚ does not prefers A to B (A « B) or is
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Acid-base titration Aim To study the titration curve of a strong base-strong acid‚ strong base-weak acid and weak acid-strong base titrations Introduction Acid-base titrations are based on the neutralization reaction between the analyte and an acidic or basic titrant. When an acid and a base are present in a stoichiometric amount e.g. 1 mole HCl added to 1 mole NaOH‚ this means that the equivalent point has been reached in an acid-base system. The end point of an acid-base titration can be
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many potential suppliers and constraints to consider that we constructed a linear programming model to identify our best option and check our solution’s sensitivity to changes in our situation. We’ve analyzed our potential suppliers for each gauge‚ taking into account their capacity‚ cost of production for each plant‚ and transportation costs (The model and our objective function can be found in the appendix.) Our goal was to allocate spinning production (at Filatoi Riuniti and six local mills)
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Assignment 1: Learning Curve “A” Case Assignment questions 1. 10.8 – 6 = 4.8 6 hours for one unit x .8 = 4.8 learning curve therefore is 80% 10.8 x .8 = 8.64 / 2 units = 4.32 average hours per unit 19.2 x .8 = 15.36 / 4 units = 3.84 average hours per unit 35.2 x .8 = 28.16 / 8 units = 3.52 average hours per unit 64 x .8 = 51.2 / 16 units = 3.2 average hours per unit 115.2 x .8 = 92.16 / 32 units = 2.88 average hours per unit
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MATH 1003 Calculus and Linear Algebra (Lecture 1) Albert Ku HKUST Mathematics Department Albert Ku (HKUST) MATH 1003 1 / 18 Outline 1 About MATH 1003 2 Mathematics of Finance 3 Simple Interest Albert Ku (HKUST) MATH 1003 2 / 18 About MATH 1003 About MATH 1003 Lecturer: Albert Ku (Office: Rm 3492. E-mail: maybku@ust.hk) Teaching assistant: Dy Chun Yin‚ Li Xing‚ Lau Hing Sang and Wong Kwok Pang Office hours at Learning Commons: Fri 10:00-noon Textbook:
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Aireen G. Tiamzon Dr. N. Racho M.A in Philosophy “Is Process Cyclical or Linear?” Process? Some say it is the mode of change whether physical‚ organic or psychological‚ while some defined it as the sequentially structured sequence of successive stages or phases. Whatever the definition or characterization on the matter a person accepts‚ still we can not deny process because it is the pervasive predominant feature of the real. At present time‚ no one will argue about the reality of change
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topics is still a controversial topic. Many years ago and still to this day‚ adults want to keep their children away from the dangers of the world‚ but little do they know that their kids could have an impact on the event. The sources‚ “Imagine This Was Your School” by Teri Kanefield
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can describe the relationship between x and y using a simple linear regression model of the form µy = β 0 + β1 x 1000 900 Sale Price (in Thousands of Dollars) 800 700 600 500 400 300 200 100 0 0 100 200 300 400 500 600 700 800 900 1000 Appraised Value (in Thousands of Dollars) response variable y : sale price explanatory variable x: appraised value relationship between x and y : linear strong positive We can estimate the simple linear regression model using Least Squares (LS) yielding the following
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4‚ 5‚ 6‚7‚8‚9‚10 and 11 in the textbook. The completed summary will help prepare you for the Final Exam in Week 5. Points will be awarded for completion of the project. Study Table for Weeks One and Two Chapter 4 Systems of Linear Equations; Matrices (Section 4-1 to 4-6) | Examples | Reference (Where is it in the text?) | | | | DEFINITION: Systems of Two Linear Equations in Two VariablesGiven the linear system ax + by = hcx + dy = kwhere a ‚ b ‚ c ‚ d ‚ h ‚ and k are real constants
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MultipleChoice Questions (Choose the best answer‚ and briefly explain your reasoning.) 1. Assume we have a simple linear regression model: . Given a random sample from the population‚ which of the following statement is true? a. OLS estimators are biased when BMI do not vary much in the sample. b. OLS estimators are biased when the sample size is small (say 20 observations). c. OLS estimators are biased when the error u captures perseverance and self‐ control‚ and you believe that people who are perseverant and have more self‐
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