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Words 366

Pages 2

Photon Correlation Spectroscopy (PCS) is a technique that is used to determine the size distribution of small particles in suspension or polymers in liquid solution. It’s also known as dynamic light scattering. It can also be used to probe the behavior of complex fluids such as concentrated polymer solutions.

Principle

When light hits small particles, the light scatters in all directions as long as the particles are small compared to the wavelength. According to the Stokes Einstein’s theory, particle Brownian motion depending on the viscosity of the suspending fluid, temperature of the fluid, diffusion coefficients of polymeric samples, molecular weights of polymers and the size of particles suspending in the fluid. Thus, the graph of scattered light can be used to determine the diffusion of particles which correlates the particle sizes.

Application

PCS is used to characterize size of various particles including proteins, polymers, micelles, carbohydrates, and nanoparticles. If the system is mono-disperse, the mean effective diameter of the particles can be determined. This measurement depends on the size of the particle core, the size of surface structures, particle concentration, and the type of ions in the medium.

Since PCS essentially measures fluctuations in scattered light intensity due to diffusing particles, the diffusion coefficient of the particles can be determined. PCS software of commercial instruments typically displays the particle population at different diameters. If the system is mono-disperse, there should only be one population, whereas a poly-disperse system would show multiple particle populations. If there is more than one size population present in a sample then CONTIN analysis must be applied. For more than two populations CONTIN analysis at several scattering angles is required.

Stability…...

... 1. What does the correlation analysis study do? Explain with a numerical example. Deadline Tuesday 8pm. Answer: 1. Correlation Analysis Study gives us a medium for detecting and measuring the relationship between two variables. For instance: The table below shows the quantity of petrol consumed by each Salesman of a reputable pharmaceutical company along with the number of cartons (quantity) sold. 2. An independent variable is one that can be manipulated. In the equation y=f(x), y is considered as the dependent variable and x as the independent variable. For example; Resumption time at Work will be an independent variable where Volume of Traffic will be the dependent variable. In the example below Quantity Sold is the independent variable while Petrol consumed is the dependent variable. NDX | Salesman | Petrol Consumed (Litres) | Quantity Sold | 01 | A. J. Johnson | 50 | 200 | 02 | Peter Brown | 60 | 215 | 03 | T. Williams | 20 | 100 | 04 | S. Paulson | 60 | 250 | 05 | K. Okocha | 100 | 50 | 06 | T. Badoo | 25 | 120 | 07 | S. A. Brown | 7 | 30 | 08 | Saka Jojo | 60 | 300 | 09 | F. Dunka | 40 | 280 | 10 | K. Court | 50 | 280 | A direct observation of the data above shows a relationship between the petrol consumed by these salesmen and the quantity of products sold i.e. the more petrol used the higher the number of products sold. This may be generalistic though but it will be observed that some aberrations may be present for instance while K. Okocha......

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...Correlation Name: Institution: Correlation The main purpose of linear correlation is to show how strongly two variables affect each other. If the increase in one variable leads to no definite change in the other variable, we say that there is no correlation between the two variables. If the increase in one leads to the increase in the other, we say there is a positive correlation. However if the increase in one leads to a decrease in the other, there is negative correlation. The strength in of the relationship between two variables is show by the preciseness of the shift in one variable as the other increases. In a perfect linear correlation, all the points fall in a straight line. If the data however forms a straight vertical or horizontal line, there is no correlation as one variable has no effect on the other. An example of correlation in my daily life is the relationship studying and passing of exams. Students who study hard are more likely to pass as compared to those who do not. This does not mean a causality relationship as studying does not always result to high grades. Scientific methods involve the formulation of hypothesis, testing, and analyzing the results and formulating a new hypothesis based on the results. When trying to establish a causal relationship in the above example, one needs to be aware of the following factors. 1. The percentage of students who study hard for their exams. 2. The percentage of students who pass their......

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...Causation and Correlation Jennifer PSY/285 Darren Iwamoto July 17, 2013 Causation and Correlation Correlation does not imply causation. According to “statistical Language Correlation and Causation” (Correlation is a statistical measure (expressed as a number) that describes the size and direction of a relationship between two or more variables. A correlation between variables, however, does not automatically mean that the change in one variable is the cause of the change in the values of the other variable.) And (Causation indicates that one event is the result of the occurrence of the other event; i.e. there is a causal relationship between the two events. This is also referred to as cause and effect.) Causation and correlation can be difficult to discern from one another because they are so closely related to one another. Wealthy People are thin. Causation or correlation? The statement “Wealthy people are thin” is a correlation. Not all wealthy people are thin however there may be more thin wealthy people versus non wealthy people due to the fact that wealthy people can afford personal trainers, better food, and healthier lifestyles. People with long hair do better on audio memory tests. Causation or correlation? The statement “People with long hair do better on audio memory tests” is in fact a correlation, it is not a very strong correlation but it is indeed one. Ice cream melts when heated. Causation or correlation? The statement “Ice cream......

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...|CM2101 (Principles of Spectroscopy) | |Experiment 1: Rovibrational Spectrum of Hydrogen Chloride | AIM To measure the infra-red (IR) spectrum of gaseous HCl using Fourier Transform Infra-Red (FTIR) spectrometer, and analyse the rotational fine structures. ABSTRACT The experiment aims to identify various parameters of gaseous HCl related to quantum mechanics by using high-resolution IR spectrum and graphical method of analysis. The values that are being investigated specifically are νe (equilibrium vibrational frequency), νeχe (product of equilibrium vibrational frequency and anharmonicity constant), k (force constant), B0 (rotational constant at n = 0), B1 (rotational constant at n = 1), Be (rotational constant at equilibrium internuclear distance), α (Coriolis constant) and re (equilibrium internuclear distance). The spectrum obtained shows strong fundamental absorption band approximately between 3100 and 2600 cm-1, with the origin of the band approximately at 2880 cm-1. It is also characterised by the presence of P and R branches which spreads out from the origin, with the former being present at a lower wavenumber region than the latter. In addition, double peaks are observed due to the presence of two isotopes of chlorine: 35Cl and 37Cl. INTRODUCTION One of the areas being...

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...was developed later that combined quantum mechanics with relativity. In advanced topics of quantum mechanics, some of these behaviors are macroscopic (see macroscopic quantum phenomena) and emerge at only extreme (i.e., very low or very high) energies or temperatures (such as in the use of superconducting magnets). The name quantum mechanics derives from the observation that some physical quantities can change only in discrete amounts (Latin quanta), and not in a continuous (cf. analog) way. For example, the angular momentum of an electron bound to an atom or molecule is quantized.[1] In the context of quantum mechanics, the wave–particle duality of energy and matter and the uncertainty principle provide a unified view of the behavior of photons, electrons, and other atomic-scale objects. The mathematical formulations of quantum mechanics are abstract. A mathematical function known as the wavefunction provides information about the probability amplitude of position, momentum, and other physical properties of a particle. Mathematical manipulations of the wavefunction usually involve the bra-ket notation, which requires an understanding of complex numbers and linear functionals. The wavefunction treats the object as a quantum harmonic oscillator, and the mathematics is akin to that describing acoustic resonance. Many of the results of quantum mechanics are not easily visualized in terms of classical mechanics—for instance, the ground state in a quantum mechanical model is a......

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...Correlation November 21, 2011 How does a College basketball team make it to the finals or win a championship? Could it be the coach’s plays or is it the player’s defense techniques at obtaining rebounds. That is a question a coach may ask his players when giving a motivational speech before a game or during practices. Either solution or both can be a determinant. If the coach has plays that involve gaining rebounds then the plays and defense techniques can work together. Obtaining the ball after a missed shot gives that team another chance at making a shot to gain more points to win the game. The more rebounds you have the better chance you have at winning the game. In an effort to determine if there is a correlation between games won and the number of rebounds obtained each game, 50 college teams from the 2010/2011 school year were analyzed to see if a high number of rebounds had an effect on the teams that made it to the finals or won a championship title. After gathering the needed information from well-known resources, the information was put into the computer software program Minitab. Minitab calculated a variety of equations and the construction of a scatterplot graph that was used to conclude if there was a correlation between games won and rebounds. The scatterplot graph with the regression line showed a positive correlation between the games won and rebounds, as rebounds increased games won also increased. The upward slope indicated a positive value, but......

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...Abstract: Fluorescence has many practical applications such as mineralogy and chemical sensors. In this experiment, the fluorescence spectrum of an organic dye, Fluorescein was obtained and compared with its absorption spectrum. It was found that Fluorescein has a maximum absorption wavelength at (486±2) nm and maximum fluorescence emission at (517±2) nm. The cause in the shift of the wavelength between the absorbed and the emitted photons, known as the stroke’s shift, was caused by the collisional and vibrational non-radioactive decay in which some of the energy from the absorbed photon is converted into heat to the surrounding molecules. Hence the emitted photons have less energy and longer wavelength as: E=hv (1) These processes occur before the fluorescence because they have a much shorter lifetime (10-12 s) compared to the lifetime of the fluorescence (10-8 s) and thus competes effectively with fluorescence. Introduction: The aim of this experiment is to obtain the absorption and fluorescence spectrum in the organic dye molecule, Fluorescein. First, the spectrum of a xenon lamp was obtained using a monochromator combined with a photomultiplier tube detector. Then a fluorescence dye was inserted between the xenon lamp and the detector in order to obtain the absorption spectrum of the fluorescein dye. The equipment set up was then altered to investigate the fluorescence spectrum of the dye. The absorption spectrum and the fluorescence......

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...Correlation and Causation The Link Between Sleep and Weight Correlation is the association between two variables, when there is an increase or decrease in one variable what effect does it has to the other variable (Triola, 2010). In this research the author looks on the relationship between a person who do not sleep or get quality sleep and their body weight. There was a study which highlighted a correlation between lack of sleep and increase in body weight. In the study with the women 40 – 60 years old, it was concluded that after studying their eating and sleeping pattern for 5-7 years women who had trouble falling asleep gained approximately 11 pounds. In the other study with the younger men, they studied their sleeping patterns for two consecutive days one day eight hour sleep and the other day four hour sleep. The researchers reported an increase in calorie intake (approximately 560 more) after sleeping for four days significantly more than the person who slept for eight hours. The two variables we have in this scenario is lack of sleep and increase in body weight, for these two variables to be correlated they must be linked or dependent on each other. Although the writer shows studies to show that when there is lack of sleep there is increase in appetite there can be other variables that determine the results such as location, body mass, individuals’ state of mind and age. According to the text the relationship between these two variables is weak and negative. The......

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...Week 7 SPECTROSCOPY Learning outcomes • Describe what a photon is, and calculate the energy, frequency and wavelength of a given photon in relation to electromagnetic radiation. • Describe the process where a UV/visible photon is absorbed by an atom or molecule. • Interpret the data from UV/visible spectrum: – Complete dilution calculations in order to produce a standard curve. – Determine an equation for the line of best fit to a linear set of data. – Use the equation, y = mx + c in order to determine the concentration of an unknown solution. Electromagnetic Radiation • Electromagnetic radiation consists of an oscillating electric and magnetic field that carries energy through space at the speed of light, c, Amplitude c= × C = speed of light, 3.00 x108 m/s = wavelength, m = frequency, (number of waves per second) s-1 Maxwell ‘s description of behaviour of light Longer Lower Wavelength (SI unit : meter) Frequency (SI unit : second-1/ Hz) 1 MHz = 106 Hz 1 GHz = 109 Hz 1 THz = 1012 Hz 1 m = 10-6 m 1 nm = 10-9 m 1 pm = 10-12 m Example 7.1 The wavelength of the green light from a traffic signal is centered at 522 nm. What is the frequency of this radiation? Solution c= × ������ = Try this: 7.9 The average distance between Mars and Earth is about 1.3 x 108 miles. How long (in minutes) would it take TV pictures transmitted from the Viking space vehicle on Mars’ surface to reach earth? (1 mile = 1.61......

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...MODULE 6 EXERCISE Linear Correlation IRINA QUENGA EG 381 STATISTICS 02/22/2015 ITT TECHNICAL INSTITUTE Task 1: Listed below are baseball team statistics, consisting of the proportions of wins and the result of this difference: Difference (number of runs scored) - (number of runs allowed). The statistics are from a recent year, and the teams are NY—Yankees, Toronto, Boston, Cleveland, Texas, Houston, San Francisco, and Kansas City. Difference 163 55 –5 88 51 16 –214 Wins 0.599 0.537 0.531 0.481 0.494 0.506 0.383 A) Construct a scatter plot, find the value of the linear correlation coefficient r, and find the critical values of r from Table VI, Appendix A, p. A-14, of your textbook Elementary Statistics. Use α = 0.05. B) Is there sufficient evidence to conclude that there is a linear correlation between the proportion of wins and the above difference? Task 2: A classic application of correlation involves the association between temperature and the number of times a cricket chirps in a minute. Listed below are the numbers of chirps in 1 minute and the corresponding temperatures in °F: Chirps in 1 Min 882 1188 1104 864 1200 1032 960 900 Temperature (°F) 69.7 93.3 84.3 76.3 88.6 82.6 71.6 79.6 A) Construct a scatter plot, find the value of the linear correlation coefficient r, and find the critical values of r from Table VI, Appendix A, p. A-14, of your textbook Elementary Statistics. Use α = 0.05. B) Is there a linear correlation between the number......

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...Business Statistics Topic: Correlation and Regression Recommended Readings: Lind D.A., Marchal W.G., and Wathen S.A. (2012), Statistical Techniques in Business and Economics, 15th International Ed., McGraw Hill [Chapter 13] Earlier edts are also suitable. Waters, D., (2008) Quantitative Methods for Business,4th Ed., Financial Times, Prentice Hall [Chapter 9] When we look at interval or ratio scale variables there is often a relationship, eg: price and quantity demanded; time spent studying and exam results obtained; gardai (police) on duty and number of crimes as well as alcohol consumed and sensibility! Regression and correlation analysis is useful because it allows us predict the value of one variable from the knowledge of another. The said relationship can be positive or negative. One first step in establishing if any of these relationships exist is to draw a scatter graph. A Scatter plot or diagram is a chart that portrays the relationship between the two variables. It is the usual first step in correlation analysis * The Dependent variable is the variable being predicted or estimated. * The Independent variable provides the basis for estimation. It is the predictor variable. Correlation Analysis From a scatter plot we have a first picture of the data. The next step is to calculate a measure which can assess the strength of that relationship. The correlation coefficient r which represents correlation in a sample is calculated as: r......

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...Correlation of English Proficiency between Academic Performances in Selected Bachelor of Science in Hotel and Restaurant Management Students in Laguna State Polytechnic University Los Baños – Campus Submitted to the Faculty, College of Hospitality Management and Tourism, Laguna State Polytecnic University Los Baños Campus, Los Baños, Laguna In Partial Fulfillment of the Requirements for Methods of Research Samantha L. Banasihan Mark L. Banasihan CHAPTER I THE PROBLEM AND ITS BACKGROUND Introduction The importance of English language for enhancing educational attainment through improved communication ability can never be over emphasized. Students who have so much difficulties with their communication skill in English language may not function effectively, not only in English language but in their academic and this is no reason than the fact that English language in Philippines today is the language of text-books and the language of instruction in schools. When English Language proficiency is high, it will definitely affect and improve the academic performance of such students. Nevertheless, where the proficiency in English is lacking in any academic setting, it will definitely lower the academic performance of such students. The competency in English significantly determines performances in intelligence or academic tests. The explanation above seem to suggest that mastery of English language is very importance even in students’ academic......

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...Part 1: Regression Descriptive Statistics| |Mean|Std. Deviation|N| Family income prior month, all sources|$1,485.49|$950.496|378| Hours worked per week in current job|33.52|12.359|378| Correlations| |Family income prior month, all sources|Hours worked per week in current job| Pearson Correlation|Family income prior month, all sources|1.000|.300| |Hours worked per week in current job|.300|1.000| Sig. (1-tailed)|Family income prior month, all sources|.|.000| |Hours worked per week in current job|.000|.| N|Family income prior month, all sources|378|378| |Hours worked per week in current job|378|378| Variables Entered/Removeda| Model|Variables Entered|Variables Removed|Method| 1|Hours worked per week in current jobb|.|Enter| a. Dependent Variable: Family income prior month, all sources| b. All requested variables entered.| Model Summary| Model|R|R Square|Adjusted R Square|Std. Error of the Estimate| 1|.300a|.090|.088|$907.877| a. Predictors: (Constant), Hours worked per week in current job| ANOVAa| Model|Sum of Squares|df|Mean Square|F|Sig.| 1|Regression|30683447.737|1|30683447.737|37.226|.000b| |Residual|309914616.753|376|824241.002||| |Total|340598064.489|377|||| a. Dependent Variable: Family income prior month, all sources| b. Predictors: (Constant), Hours worked per week in current job| Coefficientsa| Model|Unstandardized Coefficients|Standardized Coefficients|t|Sig.|95.0% Confidence Interval for B| |B|Std.......

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...The distinction between causation and correlation is very important in scientific thought. Oftentimes the two concepts get mixed up, sometimes out of a misunderstanding and other times due to a desire to provide a plausible explanation for a scientific observation. Therefore, it is very important to be able to understand the difference between the two ideas. Correlation is defined by Merriam-Webster’s online dictionary to be: “the state or relation of being correlated; specifically : a relation existing between phenomena or things or between mathematical or statistical variables which tend to vary, be associated, or occur together in a way not expected on the basis of chance alone “ In other words, a correlation is a relationship between two or more things which change (variables) that can be described mathematically. Correlation refers to how closely two sets of information or data are related. Wealthy people are thin This association is fickly being that not all wealthy people are thin. The ones who are thinner may have a nutritionist or diet is on a healthier side. They also may be on a regular workout. People with long hair do better on audio memory tests. This would be an association as well. No association between the two. Ice cream melts when heated. The association of these two goes together because when ice cream get to heat it melts so the two variables relate. Students with fewer clothes perform worse on standardized tests. There is no......

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...Wk: 4 Correlation Response Paper Stacy Harris BSHS/382 0ctober 31, 2011 University of Phoenix Staci Lowe Correlation Describe at least two different methods of establishing correlation between variables and provide an example of each. According to the text, “There are four forms of Karl's Pearson's product-moment r. They are Pearson r, Spearman rho (rs), Point-biserial r(pb), and phi coefficient. Each method views variables not in isolation, but instead as systematically and meaningfully associated with, or related to, other variables. For example, using correlation coefficient which indicates the strength of association between two variables the (X,Y). it also describes correlation that reflect mutual relations between X and Y resemble a straight line also known as linearity. In addition, values of r of 1.0 (positive or negative) indicates an perfect linear relation, while 0 indicates that that neither X or Y can be predicted by a linear equation. In these types of cases when the r is positive then there is an increase in both X and Y. but if the r is negative its only an increase in the X and a decrease in Y. Another method that's commonly used is the dichotomous variable also known as the discrete variable which has two ......

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