Table of contents

1. Intro to General Chemistry3h 48m
2. Atoms & Elements4h 16m
3. Chemical Reactions4h 10m
4. BONUS: Lab Techniques and Procedures1h 38m
5. BONUS: Mathematical Operations and Functions48m
6. Chemical Quantities & Aqueous Reactions3h 53m
7. Gases3h 49m
8. Thermochemistry2h 37m
9. Quantum Mechanics2h 58m
10. Periodic Properties of the Elements3h 9m
11. Bonding & Molecular Structure3h 29m
12. Molecular Shapes & Valence Bond Theory1h 57m
13. Liquids, Solids & Intermolecular Forces2h 23m
14. Solutions3h 1m
15. Chemical Kinetics2h 53m
16. Chemical Equilibrium2h 29m
17. Acid and Base Equilibrium5h 1m
18. Aqueous Equilibrium4h 47m
19. Chemical Thermodynamics1h 50m
20. Electrochemistry2h 42m
21. Nuclear Chemistry2h 36m
22. Organic Chemistry5h 7m
23. Chemistry of the Nonmetals2h 39m
24. Transition Metals and Coordination Compounds3h 16m

4. BONUS: Lab Techniques and Procedures

Experimental Error

General Chemistry

4. BONUS: Lab Techniques and Procedures

Experimental Error

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Multiple Choice

Which of the following best describes how data tables can support or refute a scientific prediction in an experiment?

Data tables automatically calculate the accuracy of predictions without further analysis.

Data tables are used solely for recording qualitative observations, not for supporting predictions.

Data tables provide a visual representation of experimental results, allowing for comparison with the predicted outcomes.

Data tables eliminate all sources of experimental error, ensuring predictions are always correct.

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Verified step by step guidance

Understand the role of data tables in scientific experiments: Data tables are used to organize and present data collected during an experiment in a structured format, making it easier to analyze and interpret the results.

Recognize that data tables do not automatically calculate accuracy: Data tables themselves do not perform calculations or analyses. They serve as a tool to display data, which can then be used to manually or computationally analyze the accuracy of predictions.

Acknowledge the purpose of data tables in supporting predictions: Data tables provide a clear and organized way to compare experimental results with predicted outcomes, helping to visually assess whether the predictions align with the observed data.

Clarify that data tables are not limited to qualitative observations: While data tables can include qualitative data, they are also used to record quantitative measurements, which are crucial for evaluating scientific predictions.

Understand that data tables do not eliminate experimental error: Data tables help in organizing data but do not address or correct experimental errors. It is important to consider potential sources of error when interpreting data and comparing it to predictions.