Name: Bhumiben Shah
Date: 31st Jan ‘13
EXPERIMENT # 2RECRYSTALLIZATION; FILTRATION
OBJECTIVES:
1. To perform recrystallization and filtration of given impure organic compound. 2. To purify impure acetanilide using reflux condenser apparatus and Hirsch funnel filtration. 3. To determine percentage recovery of pure material (which is), purified by recrystallization and filtration.

SAFETY PRECAUTIONS:
1. Operate the aspirator with the maximum water-flow using a stop cock to control the amount of vacuum. 2. Do not leave the apparatus unattended for long if several students are using aspirators on same water line, because of the possible pressure fluctuations.

CHEMICALS: Impure acetanilide, charcoal, water.
EQUIPMENTS: Reflux condenser apparatus, 250 mL round bottomed flask, Hirsch funnel and filter flask.

PROCEDURE:

1. Take a 50-mL round-bottomed flask and a small condenser and set up a reflux apparatus. Arrange a ceramic fibre-centered wire gauze on an iron ring such that it remains two inches above the burner. Position the clamps on flask and condenser accordingly. 2. Weigh a 2.0-g of impure acetanilide and keep just pinch of it aside for melting point determination. Add rest of it to the 50-mL flask by temporarily removing reflux condenser. 3. Add one or two boileezers to the flask, reset the apparatus properly and add 30 mL of water through the top of the condenser. 4. Keep the water circulating through the condenser by attaching the lower end of its water jacket to a water outlet and the upper end to the sink with help of rubber tubing. 5. Adjust the burner to heat the water and let it boil gently such that the water refluxes in a steady drip from the bottom of the condenser. 6. Keep on heating the mixture till the solid stops to dissolve. Then remove the burner and cool the flask for a moment. 7. Remove the condenser carefully and add a very small amount of decolourizing charcoal to the...

...Kiandria Grissett
Business Math-7
4 / 20 / 2013
Estimation
1. Discuss at least two "real world" examples in which you use estimation in your daily life.
2. Discuss from your examples how estimating can have negative effects if you over or under estimated.
3. Think of an example in a real world scenario when a company or organization might use estimation and have negative or devastating results.
One real world example I would like to discuss is how many minutes it takes me to get up and be at the marina at 11am. I work on Baldhead Island which means I have to catch a ferry to get to work. Each ferry leaves every half hour and not a minute late and I have to be there before 11am. I usually estimate my time right on point I wake up at 9:30 am it usually takes me 20 to 30 minutes or less to take a shower, get dressed, brush my teeth, and do my hair. I leave my house no later than 10:15 am which puts me at the marina at 10:45 am waiting on the boat. Another example that I would like to discuss is getting my boyfriend back and forth to court when he has it being that he is from another county in the state of North Carolina and it takes us at least an hour and forty-five minutes to get there. When he does have court it usually takes in at 8am. We usually wake up at 6:20am (I know we are pushing it on the time) get dresses, feed the dogs and are out getting gas no later than 6:40am. We make this long drive down the interstate...

...
Demand Estimation
Seydou Diallo
Strayer University
ECO 550: Managerial Economics
Dr. Fereidoon Shahrokh
November 4, 2014
Background
I work for Snack-Eeze. We are the leading brand of low-calorie, frozen microwavable food. We estimate the following demand equation for our product using the data from 26 supermarkets around the country for the month of April.
QD = -2,000 - 100P + 15A + 25PX + 10I
(5,234) (2.29) (525) (1.75) (1.5)
R2 = 0.85 n = 120 F = 35.25
Your supervisor has asked you to compute the elasticities for each independent variable. Assume the following values for the independent variables:
Q = Quantity demanded of 3-pack units
P (in cents) = Price of the product = 200 cents per 3-pack unit
PX (in cents) = Price of leading competitor’s product = 300 cents per 3-pack unit
I (in dollars) = Per capita income of the standard metropolitan statistical area
(SMSA) in which the supermarkets are located = $5,000
A (in dollars) = Monthly advertising expenditures = $640
Compute the elasticities for each independent variable. Note: Write down all of your calculations.
McGuigan, Moyer, and Harris state that elasticity is merely a ratio of the percentage change in quantity to the percentage change in a determinant (2013). Therefore, we will use the following formula.
The formula for finding price elasticity of demand is...

...
Demand Estimation
ECO 550: Managerial Economics and Globalization
/2015
Jason M Brown
1. Compute the elasticity for each independent variable.
When P=500 Px-600 I=$5,500 A=$10,000 and M=5,000, using the regression equation:
QD = -5,200 -4,200(500) +5.2(600) +5.2(5,500) +0.20) (10,000) +0.25(5,000) =17,650
Price Elasticity = (P/Q) (∆Q/∆P)
From the regression equation: ∆Q/∆P=-42
So price elasticity (EP) = (p/Q) (-42) (500/17650) =-1.19
Ec=20(600/17650) =0.68
EA= (P/Q) (0 .20) (10,000/17,650) =0.11
EI= (P/Q) (5.2) (5,500/17,650) = 1.62
EM= (P/Q) (0.25) (5,000/17,650) =0.07
2. Determine the implications for each of the computed elasticity for the business in terms of short term and long-term pricing strategies. Provide a rationale in which you cite your results.
Price Elasticity is -1.19. That is a 1% increase in price of the product will make quantity demanded to drop by 1.19%. Thus, the demand for this product is somewhat elastic. Consequently, increase in income may drive consumers away.
Cross-price elasticity is 0.68 that is if the price of the competitor’s product goes up by 1% then quantity demanded of this product will increase by 0.68%. This product is fairly inelastic to a competitor’s price and there exist no need to be concerned about the competitor since their pricing won’t affect sales.
Income-elasticity is 1.62. This indicates that a 1% rise in the average area income will boost the quantity demanded by 1.62%. In this aspect, the...

...September 29, 2013
Estimation Paper
In our group we have me, Kelip and J.R., and individually we both played our separate parts. Even though we did not have a perfect time to really meet up because of unscheduled events, I still think we managed to work as a team. To start off, the question that we chose to find an estimation answer on was “How many softballs can fit in our lecture room?” The first couple of class time was spent on J.R. and Kelip measuring the walls and indents of the classroom, while sending me the measurements. So our first thought is that we needed to find out the volume of the classroom with the indents and the volume of a 12 inch softball. Within the measurements of the walls and the indents we immediately wanted to subtract the indents within the walls because it was easier and we did not have much math to do. A factor that could be involved is that there are different sizes of softballs so it would be a variety of different volumes because of the size. Another factor would have been the wrong measurements of the actual classroom because of how the tape measure could have been moved a little bit or read wrong. Thirdly, a factor is the wrong calculations on the calculators or if others have rounded their answers. Finally, the last factor I could have thought was that we could have double checked to make sure we still would have the same answers without the indents. A list of that would have been useful to gather is...

...antenna that uses selectable radiation patterns depending on the situations. These antennas provide the ability to sense the direction of incoming signals. Smart antennas are the antenna arrays with smart signal processing algorithms used to identify spatial signal signature such as the Direction of arrival (DOA) and used to calculate the beam forming vectors, to tract and locate the antenna beam on the mobile/target. Smart has the main function of DOA estimation.
Keywords: Smart antenna, DOA ,Wireless communication.
1. Introduction: The smart antenna system estimates the direction of arrival of the signal, using techniques such as MUSIC (Multiple Signal Classification), estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithms. They Involve finding a spatial spectrum of the antenna/sensor array, and calculating the
DOA from the peaks of this spectrum. These calculations are computationally intensive.
2.Direction Of arrival Estimation Algorithms
The array-based direction-of-algorithm estimation techniques can be broadly divided into four different types conventional techniques, subspace based techniques, maximum likelihood techniques and the integrated techniques which combine property restoral techniques with subspace based techniques. Conventional methods are based on classical beam forming techniques and require a large number of elements to achieve high resolution. Subspace...

...Sodium chloride, also known as salt, common salt, table salt, or halite, is an ionic compound with the formula NaCl. Sodium chloride is the salt most responsible for the salinity of the ocean and of the extracellular fluid of many multicellular organisms. As the major ingredient in edible salt, it is commonly used as a condiment and food preservative.
[edit] Properties
Thermal conductivity of pure NaCl as a function of temperature has a maximum of 2.03 W/(cm K) at 8 K and decreases to 0.069 at 314 K (41 °C). It also decreases with doping.[3]
[edit] Production and use
Modern rock salt mine near Mount Morris, New York, United States
Salt is currently mass-produced by evaporation of seawater or brine from other sources, such as brine wells and salt lakes, and by mining rock salt, called halite. In 2009, world production was estimated at 260 million metric tons, the top five producers (in million tonnes) being China (60.0), United States (46.0), Germany (16.5), India (15.8) and Canada (14.0).[4]
As well as the familiar uses of salt in cooking, salt is used in many applications, from manufacturing pulp and paper, to setting dyes in textiles and fabric, to producing soaps, detergents, and other bath products. It is the major source of industrial chlorine and sodium hydroxide, and used in almost every industry.
Sodium chloride is sometimes used as a cheap and safe desiccant because it appears to have hygroscopic properties,...

...ISE: The Determination of Chloride
Unknown: #34
I. Purpose:
In experiment V, “ISE: The Determination of Chloride”, the concentration of an Unknown Chloride solution, and the Wt% of NaCl in a sample of celery salt, were both determined. To determine the concentration of an Unknown Chloride solution, a Calibration plot is first prepared.
The Calibration plot is made by first measuring a series of known concentrations of Cl- (with the same activity of the unknown solution) and obtaining a set of E-values for these standards -A graph is then plotted from the corresponding E-values vs. the logarithm of the concentration of Cl-. Once all the data points have been plotted, the slope of the line is determined (found by using a least squares calculation) -which is then used (the slope) to find the concentration of the unknown from the measured E-value of the unknown chloride solution. In the determination of the Wt% of NaCl in a sample of celery salt, the method of standard additions was used to find the Wt% of NaCl in our celery sample.
II. Experimental Parameters:
A. Theoretical Equations
B. Standard Additions Method
III. Sample Calculations
A. Concentration of Chloride in the Calibration Solution
B. Calculation of Slope, Intercept and Equation of for the Calibration Line
i. LLS Table
ii. Calculations
C. Theoreical Electrode Slope & Relative Error of Measured...

...
Demand Estimation
Dhruvang kansara
Eco 550, Assignment 1
Professor: Dr, Guerman Kornilov
January 27, 2014
1. Compute the elasticity for each independent variable. Note: Write down all of your calculations.
According to our Textbooks and given information, When P = 8000, A = 64, PX = 9000, I = 5000, we can use regression equation,
QD = 20000 - 10*8000 + 1500*64 + 5*9000 + 10*5000 = 131,000
Price elasticity = (P/Q)*(dQ/dP)
From regression equation, dQ/dP = -10.
So, price elasticity EP= (P/Q) * (-10) = (-10) * (8000 / 131000) = -0.61
Similarly,
EA = 1500 * 64 / 131000 = 0.73
EPX = 5 * 9000 / 131000 = 0.34
EI = 10* 5000 / 131000 = 0.38
2. Determine the implications for each of the computed elasticities for the business in terms of short-term and long-term pricing strategies. Provide a rationale in which you cite your results.
Price elasticity is -0.61 which means a 1% increase in price of the product causes quantity demanded to drop by 0.61%. So, the demand of the product is relatively inelastic. Therefore, increase in price may not have large impact on the customers.
Advertisement elasticity is 0.73, meaning 1% increase in advertising expenses increases quantity demanded by only 0.73%. So, demand is relatively inelastic to advertising. Therefore, more advertisement won’t necessarily mean that firm can raise the price because it still could drive customers away.
Cross-price elasticity is 0.34 which...