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Exploring Variables, Data Processing, and Graphing Techniques in Scientific Experiments

This unit focuses on understanding variables in scientific research, including independent and dependent variables, and constants. Sample research questions are provided to practice identifying these elements. It also delves into data processing—emphasizing the importance of data completeness, accuracy, and pattern recognition. The section guides on averaging data through multiple trials, demonstrated with an example calculation. Finally, it covers essential graphing techniques, highlighting the need for titles, axis labels, unit measurements, appropriate scaling, and legends for effective data visualization.

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Exploring Variables, Data Processing, and Graphing Techniques in Scientific Experiments

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Presentation Transcript

  1. Unit 1 Lecture 3 Variables Data Processing Graphs

  2. Variables

  3. Sample Problems • Research questions are listed below. For each question identify the independent variable, dependent variable and constants. • How much water flows through a faucet at different openings? • Does heating a cup of water allow it to dissolve more sugar? • Does fertilizer make a plant grow bigger? • Does an electric motor turn faster if you increase the voltage?

  4. Data Processing • Review your data and ask yourself these questions • Is it complete or did I forget something? • Do I need to collect more data? • Did I make any mistakes in collecting the data? • Is there a pattern to my data? • Did I perform multiple trials?

  5. Data Processing • For multiple trials average the data you collected to obtain a mean • Mean = (Trial 1 + Trial 2 + Trial 3 +...) Number of trials • Example: • In an experiment you recorded the following data: trial 1 = 10cm; trial 2 = 15cm; trial 3 = 30 cm; trial 4 = 20cm; trial 5 = 25cm • Calculate the mean for this experiment

  6. Graphs • All graphs should have • A title • Axis labels • Units • Appropriate scaling • A legend

  7. Types of graphs

  8. Graph Checklist

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