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IU / Chemistry / CHEM 127 / How different do two limited sets of data need to be before we can saf

How different do two limited sets of data need to be before we can saf

How different do two limited sets of data need to be before we can saf

Description

School: Indiana University
Department: Chemistry
Course: Principles of Chemistry and Biochem I Lab
Professor: Norman dean
Term: Fall 2016
Tags: chem-c127, chem c127, c127, Chemistry, Chem, density and data analysis, density and data analysis lab, and data analysis lab
Cost: 25
Name: CHEM-C127 Density and Data Analysis Lab Notes
Description: These notes cover the material from the lecture in preparation for the Density and Data Analysis Lab.
Uploaded: 02/15/2016
1 Pages 18 Views 5 Unlocks
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C127 Lecture 5 Notes- Density and Data Analysis 2-11-16 ∙ Learning goals


How different do two limited sets of data need to be before we can safely say they are different?



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

∙ �������������� (������) =�������� We also discuss several other topics like Migration, is what?

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∙ Lab Info

o 2 solutions with different amounts ��������


Systematic error always makes data?



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: Don't forget about the age old question of What is the popular sovereignty?

▪ 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


What is the percent error?



If you want to learn more check out What is a tony award and where did it get its name?

∙ 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 Don't forget about the age old question of How did stalin secure single-party rule for bolshevik party?
We also discuss several other topics like What defines a function?
Don't forget about the age old question of Is a higher or lower roe better?

o Percent error- when true value known:

▪ % ���������� = |��ℎ������������������−������������������������ 

�������� ���������� | ∙ 100

o When true value not known, use statistics

▪ Standard deviation �� = √∑(����−��̅)2 

��−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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