::Scattered Plot In Excel::

Objectives

• Enter and format data in an Excel spreadsheet in a form appropriate for graphing
• Create a scatter plot from spreadsheet data
• Insert a linear regression line (trendline) into the scatter plot
• Use the slope/intercept formula for the regression line to calculate a x value for a known y value
• Explore curve fitting to scatterplot data
• Create a connected point (line) graph
• Place a reference line in a graph
  
  
  Part 1 - Beer's Law Scatter Plot and Linear Regression 
  
  Beer's Law states that there is a linear relationship between concentration of a colored compound in solution and the light absorption of the solution. This fact can be used to calculate the concentration of unknown solution, given their absorption readings. First, a series of solution of known concentration are tested for their absorption level. Next, a scatter plot is made of this empirical data and a linear regression line is fitted to the data. This regression line can be expressed as a formula and used to calculate the concentration of unknown solutions.
  
  
  

  

  Beer's Law

   Part 2 - Titration Data Plottin

  Creating a Scatter Plot of Titration Data

  

  Titration graph with the legend

  In this next part of the tutorial, we will work with another set of data. In this case, it is of a strong acid-strong base titration. With this titration, a strong base (NaOH) of known concentration is added to a strong acid (also of known concentration, in this case). As the strong base is added to solution, its OH- ions bind with the free H+ions of the acid. An equivalence point is reached when there are no free OH- nor H+ ions in the solution. This equivalence point can be found with a color indicator in the solution or through a pH titration curve. This part of the tutorial will show you how to do the latter. 

  
  

  
  

  
  

  
  

  

  Titration graph with the absent of legend

  Tutorial task during the class

  1. Finding the line of best fit

  
  

  The table shows the temperature at the start of the race and the percentage of runners injured in eight running of the Boston Marathon.

  
  

  Temperature (in °C)	8	22	15	13	12	21	20	9
  Percentage injured p	4.7	12.3	6.5	5.9	6.6	10.3	8.4	4.0

  
  

  
  

  1. Use Excel to plot a scatter graph and find an equation of the regression line for the data.

  
  

  2. Use regression equation to estimate the percentage of runners that would be injured if the marathon was run on a day when the temperature was 27°C.

  
  

  3. Use the regression equation to estimate the temperature at the start of the race for a race in which 10% of the runners were injured.

  
  

  Answer:
  
  

  

  Temperature

  1. Quadratic regression

  
  

  The following table shows the number of new housing starts (in thousand) for 1990 through 1997.

  
  

  Year (x)	1990	1991	1992	1993	1994	1995	1996	1997
  Housing starts (y)	1193	1014	1200	1288	1457	1354	1477	1474

  
  

  1. Use Excel to plot a scatter graph and find an equation that gives the number of new housing starts in terms of the year.

  
  

  2. Predict the number of new housing starts in 2001.

  
  

  
  

   Answer:

  
  

  

  House

  
  

  
  

  
  

   Wallahu'alam

::SMILES::

Simplified molecular input line entry specification 

(SMILES)

Is it a SMILES?

   The simplified molecular input line entry specification or SMILES is a specification for unambiguously describing the structure ofchemical molecules using short ASCII strings. SMILES strings can be imported by most molecule editors for conversion back into two-dimensional drawings or three-dimensional models of the molecules.

   The original SMILES specification was developed by Arthur Weininger and David Weininger in the late 1980s. It has since been modified and extended by others, most notably by Daylight Chemical Information Systems Inc. In 2007, an open standard called"OpenSMILES" was developed by the Blue Obelisk open-source chemistry community. Other 'linear' notations include the Wiswesser Line Notation (WLN), ROSDAL and SLN (Tripos Inc).

   In July 2006, the IUPAC introduced the InChI as a standard for formula representation. SMILES is generally considered to have the advantage of being slightly more human-readable than InChI; it also has a wide base of software support with extensive theoretical (e.g., graph theory) backing.

Some examples of SMILES