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CHEM-C127 Density and Data Analysis Lab Notes

by: Kathryn Brinser

CHEM-C127 Density and Data Analysis Lab Notes Chemistry C127

Marketplace > Indiana University > Chemistry > Chemistry C127 > CHEM C127 Density and Data Analysis Lab Notes
Kathryn Brinser
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About this Document

These notes cover the material from the lecture in preparation for the Density and Data Analysis Lab.
Principles of Chemistry and Biochem I Lab
Dr. Norman Dean
Class Notes
chem-c127, chem c127, c127, Chemistry, Chem, density and data analysis, density and data analysis lab, data analysis lab
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This 1 page Class Notes was uploaded by Kathryn Brinser on Sunday February 14, 2016. The Class Notes belongs to Chemistry C127 at Indiana University taught by Dr. Norman Dean in Fall 2016. Since its upload, it has received 285 views. For similar materials see Principles of Chemistry and Biochem I Lab in Chemistry at Indiana University.


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Date Created: 02/14/16
C127 Lecture 5 Notes- Density and Data Analysis 2-11-16  Learning goals o Learn how to design an experiment to give best possible results o Learn how to use standard deviation to examine quality of data sets o Learn how to use t-test in Excel to decide if 2 experiments gave same or different results  Safety/Waste Disposal o Goggles and appropriate clothing required o All solutions can be put down sink with plenty of water  ???????????????????????????? ( ???? ) = ???????????????? ???????? ????????????????????????  Lab Info o 2 solutions with different amounts ???????????????? o Measure 2 unknowns, use t-test to make hypothesis to say whether solutions are the same density o For this lab, density concept not very important; focusing on analyzing data sets o To get accurate data we need:  Accurate mass- analytical balances (with doors on sides) go to 4 decimal places- keep in mind they have mass limit  Accurate volume- choose glassware based on what is available/best-suited  Beakers- mass produced; measurements very very approximate; never measure with beakers  Same goes for Erlenmeyer flasks  Graduated cylinder- not best overall choice (not calibrated), but good; pick one closest in size to amount of liquid you need  Volumetric pipets/flasks- best choices for accurate and reproducible volume; made to be accurate and precise through individual calibration; known as Class A glassware  Quality of Data o All data has error o Exclude data if there is some major mistake; repeat step(s) to replace bad data o Random error- equally likely to give high result as low; cannot get rid of it o Systematic error- always makes data high or always makes it low; cannot identify unless you know what a value should be (ie. theoretical yield, you spilled something); can be reduced as much as possible o ALWAYS ON EXAMS- random error always present; will ask about differences between two kinds and how to know if systematic is present o Percent error- when true value known:  % ???????????????????? = | ????ℎ????????????????????????????????????−????????????????????????????????????| ∙ 100 ???????????????? ???????????????????? o When true value not known, use statistics 2  Standard deviation ???? =√ ∑(????????−????) ????−1   When scale on axis based on numbers (not ????), wider curve = more random error, narrower curve = less; always looks same based on ????  Our data sets will be much smaller; not a nice curve  For us, justified to throw out data beyond ±2???? due to small sample size instead of typical ±3???? o How different do two limited sets of data need to be before we can safely say they are different? (use T-test)


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