Chemistry A
Welcome to Chemistry A.
This science course attempts to explain what matter is, how we organize it and how it behaves. At the end of the semester you will have attained basic chemical principles, problem-solving skills and proficiency in the use of scientific methodology.
The key to success in this class is simple, respect yourself and others and always try your best.
News for the Week
News for the week All the information that you need for the end of the Semester and this current week.
You can check the calendar for the Semester Test date.
Topic 1. Measurement and Data Processing
Guiding Questions
What is the relationship between accuracy and precision?
When a zero digit is not significant?
What is the difference between random and systematic errors?
What you should learn
Accuracy is how close a measurement is to the "true" value. Precision is how close several measurements of the same value are to each other.
Random errors are due to the accuracy of the equipment and systematic errors are due to how well the equipment was used or how well the experiment was controlled.
1. Random errors: Precision (Errors inherent in apparatus.)
A random error makes the measured value both smaller and larger than the true value.
2. Systematic error: Accuracy (Errors due to "incorrect" use of equipment or poor experimental design.)
A systematic error makes the measured value always smaller or larger than the true value, but not both.
More specifically... (Copy from the IB Chemistry Subject Guide)
1.1 Uncertainty and error in measurements
- Describe and give examples of random uncertainties and systematic errors.
- Distinguish between precision and accuracy.
- Describe how the effects of random uncertainties may be reduced.
- State random uncertainty as an uncertainty range (±).
- State the results of calculations to the appropriate number of significant figures.
1.2 Uncertainties in calculated results
- State uncertainties as absolute and percentage uncertainties.
- Determine the uncertainties in results.
1.3 Graphical techniques
- Sketch graphs to represent dependences and interpret graph behavior.
- Construct graphs from experimental data.
- Draw best-fit lines through data points on a graph.
- Determine the values of physical quantities from graphs.