Unit One – Scientific Investigations

1. Unit One – Scientific Investigations Covers SOL CH.1

2. Conducting Scientific Investigations • In Order to conduct a meaningful scientific investigation, experimental design, hypothesis formation, data gathering, data analysis and procedural error must be included.

3. Experimental Design of a Controlled Experiment • Experimental Design must include: • Hypotheses • Independent and Dependent variables • Constants and controls • Repeated trials.

4. Hypotheses • Hypotheses are ideas/statements formulated in preparation for an experiment which are purposely designed to solve a problem, prove or disprove a current thought in science. • Hypotheses in their most elementary form are an if, then sentence based on variables. • Such as If the IV, then the DV.

5. Variables • While often more than one variable is taken account for in an experiment, a controlled experiment manipulates one variable per test. • Variables that are considered in a controlled experiment are the independent and dependent variables. • Independent variable – the variable that is purposefully changed. This variable is controlled and careful consideration is paid to eliminate other factors. • Dependent variable – the result of the experiment.

6. Constants and Controls • Constants are all known variables that will factor into a change. By keeping these variables constant, the experimenter can identify change in the dependent variable or result of the experiment. • Controls are a benchmark or standard by which a test is measured.

7. Repeated Trials • Repeated trials in an experiment are used to verify the result. AGAIN TO VERIFY!!! • Repeated trials are used to look for procedural error as well.

8. Data Collection • Once an experiment is designed, data collection can begin. The use of proper equipment, calibrated equipment and identifying the proper data to collect are all vital portions of data collection. • The use of data tables for collecting data is a standard in conducting experiments. • Data tables are designed in advance and must coordinate with the independent and dependent variables. • Data that falls out of the realm of the IV and DV is placed in an observation section of the lab.

9. Observations • Data collection and anything that can be measured without subjection is a quantitative measurement. Basically, if it has numbers its quantitative. • Data collection that involves observations, the senses or has an element of being subjective is a qualitative measurement.

10. Data Analysis • Data Analysis is different from collection. Analysis occurs once all data is collected/observed. Mathematical analysis is often done to look for mean measurements, trends of an experiment and used to validate an experiment. Validation is through percent error to evaluate accuracy, significant digit measurements and accounting for any variation in data to discover and correct procedural error.

11. Percent Error • In order to calculate percent error a standard or theoretical yield must be established. • The result is then divided by the theoretical yield, multiplied by 100 and then subtracted from 100. • From percent error the experiment can be evaluated for accuracy.

12. Accuracy vs Precision • When percent error is 0% the accuracy and precision of the experiment are equal. • Accuracy is hitting the correct yield each time. • Precision is hitting the same yield each time. • An experiment may be precise but not accurate. • Many experiments are “proven” based on an incorrect accounting for precision and not accuracy. To correct for this error, the theoretical yield is a calculation NOT based on the data from the experiment.

13. Significant Measurements • A measurement may only be used if it is to the lowest gradient of the available equipment. Mixing equipment with varying gradients results in mathematical manipulation of those measurements.

14. Significant Measurements • For example: A student began an experiment using a 10 mL graduated cylinder which has a gradient of .1 mL. The same student finished the experiment using a 25 mL graduated cylinder using a gradient of 1 mL gradient. To use both measurements, the student must report all data to the lowest 1 mL gradient. Any measurement that is .5mL or higher must be rounded to the next mL. This can cause an error strand in the data.

15. Procedural Error • Procedural error occurs mainly through systemic experimental design error or through human error. • Systemic error involves a flaw in the design of an experiment. • Human error is through un-calibrated equipment, measurement errors, and carelessness.