Error Analysis within an Experiment

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Error Analysis Lab

By: Lab Team 5

Introduction and Background: In the process of learning about the importance of measurement and data processing, lab teams were given prompts to design experiments as well as address the precision, accuracy, and error analysis within the experiment. Lab teams collaborated their data to find similarities and differences within their measurements. Through this process, students learned the importance of the amount of uncertainty as well as the different types of experimental errors that might have caused a margin of difference within the lab teams results. Measurement and data processing is a topic discussed in IB Chemistry SL; it is important within the scientific community as it discusses the reliability of the data presented. Uncertainty is used to determine a range of a value in a measurement or instrument. Uncertainty of an analogue instrument is plus or minus half of the smallest division present; while uncertainty of a digital scale is plus or minus the smallest division present. To identify the amount of uncertainty, significant figures (the digits in measurement up to and including the first uncertain digit) are used. Certain rules are used to discover the number of significant figures in a value: * 1-9 are always significant

* included zeroes (1009= 4 significant figures)
* leading zeroes never count (0.023= 2 significant figures) * trailing zeroes after the decimal count (1.9850= 5 significant figures) Experimental errors are the difference between recorded value and generally accepted or literature value. There are two types of experimental errors: random and systematic errors. Random errors are caused by the readability of a measuring instrument, the effects of changes in the surroundings, insufficient data, and observer misinterpretation. Systematic errors are errors that can not be reduced by repeating experiments or careful experimental design. These errors are caused by poor experimental design as well as improper measurement techniques. Accuracy is the difference between the experimental value and the accepted value. The greater the accuracy, the smaller the systematic error. Precision is the reproducibility of the experimental value. The greater precision, the less the random uncertainties.

Purpose: Design laboratories based upon ideas of accuracy, precision and error analysis through creating a procedure and addressing the prompts.

Materials:
* 13.5 cm x 10 cm sheet of aluminum foil
* Ruler
* Balance
* Laptop
* Micrometer
* Silver Cube of Unknown Solid
* H2O (via sink)
* Timer
* Thermometer (in degrees Celsius)
* 500 sheets of paper
* Caliper
* 100 mL graduated cylinder
* 10 mL graduated cylinder
* 25 mL flask

Procedures and Methodologies:

Station One (find volume, mass, and density of an unknown cube): 1 Find the height of the silver cube of unknown solid using the micrometer. 2 Find the length of the silver cube of unknown solid using the micrometer. 3 Find the width of the silver cube of unknown solid using the micrometer. 4 Find the mass of the silver cube of unknown solid using the balance. 5 Using the measured length, width and height of the cube of unknown solid, calculate the volume of the cube. 6 Divide the mass of the cube by the volume to find the density of the cube. 7 Using the laptop, identify the type of metal based on the density.

Station Two (find a way to measure 10.5mL of water):
1 Using the 10 mL graduated cylinder, measure out 10 mL of water. 2 Pour the measured water into the 100 mL graduated cylinder. 3 Using the 10 mL graduated cylinder, measure 0.5 mL of water. 4 Pour the measured water into the 100 mL graduated cylinder, combining with the previously measured 10 mL of water.

Station Three (measure the thickness of single sheet of paper and volume of 500 sheets): 1 Measure the height of the stack of...
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