this lab of Determining the concentration of a unknown solution: Beers Law. We determined the concentration of a unknown CuSO4 solution by measuring its absorbance with the colorimeter. With all the calculations we were able to solve the linear regression Equation of absorbance vs. concentration and the alternate method. Materials Vernier LabPro or CBL 2 interface .40 M CuSO4 solution Computer or handheld CuSO4 unknown solution Vernier Colorimeter
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Date: 5th March 2010 Abstract Bone lengths can be used to provide stature estimations in case of unidentified skeletal remains‚ an important tool in forensic and bioarchaelogical cases. Where the bones are broken or fragmented‚ regression equations can be used to estimate total bone length from its fragments‚ which in turn can be used to estimate stature. The aim of this study was to test 2 new measurements of the femoral shaft to see if they could be used as predictors of maximum femoral length
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Regression Analysis The concepts and principles developed in dealing with simple linear regression (i.e. one explanatory variable) may be extended to deal with several explanatory variables. We begin with an example of two explanatory variables‚ both of which are continuous. The regression equation in such a case becomes: Y = α + β1x1 + β2 x2 It is customary to replace α with β 0‚ and so all future regression equations would be written as Y = β0 + β1x1 + β2x2 ……βnxn Regression with two explanatory
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chemical reactions. A certain run from the previous task was twice duplicated to for a “hot and cold” test for reaction rate. The prior run was again duplicated for a test with catalyst. The data obtained was graphed in a linear regression form‚ using the Arrhenius equation: lnk=-EaR-1T+lnA‚ reaction rate: rate = k[A]x[B]y and other principles held in chemistry. The graph from the results determined that there is a relation between rate and the previously mentioned factors. The results validated
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whether to produce a particular product at all. 2. Discuss demand respond to consumer income increase or decrease as a result of an economic expansion or contraction. 3. Specify the components of a regression model that can be used to estimate a demand equation. 4. Interpret the regression results (i.e.‚ explain the quantitative impact that changes in the determinants have on the quantity demanded). 5. Explain the meaning of R2. 6. Evaluate the statistical significance of the regression coefficients using
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technique that attempts to “explain” movements in one variable‚ the dependent variable‚ as a function of movements in a set of other variables‚ called the independent (or explanatory) variables‚ though the quantification of a single equation. The simplest single – equation linear regression model is: Y = β0 + β1X βs – coefficient that determine the coordinates of the straight line at any point β0 – is the constant or intercept term‚ it indicates the
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KINETICS OF THE ACID DECOMPOSITION OF THIOSULFATE Aqueous solutions of thiosulfate‚ S2O32-(aq) are stable if neutral or basic‚ but decompose quickly when the thiosulfate is dissolved in acid according to the equation: Sulfur dioxide is a gas at room temperature‚ but is very soluble in water. Sulfur‚ a water insoluble solid‚ forms a colloidal suspension. As a result‚ the solution first becomes cloudy and then opaque. We can take advantage of the developing opacity of the reaction system to do a
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Invertible matrix From Wikipedia‚ the free encyclopedia (Redirected from Nonsingular matrix) Jump to: navigation‚ search In linear algebra an n-by-n (square) matrix A is called invertible (some authors use nonsingular or nondegenerate) if there exists an n-by-n matrix B such that where In denotes the n-by-n identity matrix and the multiplication used is ordinary matrix multiplication. If this is the case‚ then the matrix B is uniquely determined by A and is called the inverse of A‚
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relative to a known reference length. As a load is applied to the sample (generally a round bar) its change in length can be recorded and compared to its initial length to determine normal strain. In this case‚ strain is found through the following equation: Where: Strain is commonly referred to as either tension or compression depending on the direction of the force applied to the sample. Tensile strain generally refers to elongation of a material as a result of a tensile test. Compressive
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Contents MODULE 2 1 Scatter graphs 1.1 Scatter graphs and relationships 1.2 Lines of best fit and correlation 1.3 Using lines of best fit Chapter summary Chapter review questions 1 1 5 6 10 10 4 Processing‚ representing and interpreting data 4.1 Frequency polygons 4.2 Cumulative frequency 4.3 Box plots 4.4 Comparing distributions 4.5 Frequency density and histograms Chapter summary Chapter review questions 51 51 56 64 65 68 73 73 2 Collecting and recording data 14 2.1 Introduction
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