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Evaluative practice

Evaluative practice. What is Evaluation? The consideration of: The way the experiment was carried out The quality of the data a nd also: the processing of that data. The Experiment – Validity (or did it measure what you wanted it to?). Limitations Uncontrolled variables Results

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Evaluative practice

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  1. Evaluative practice • What is Evaluation? • The consideration of: • The way the experiment was carried out • The quality of the data • and also: the processing of that data

  2. The Experiment – Validity (or did it measure what you wanted it to?) • Limitations • Uncontrolled variables • Results • Effects of errors (systematic and random) • Reliability • Repeatability/reproducibility • Accuracy • Precision

  3. Definitions 1. Accuracy 2. Precision 3. Reliability 4. Validity 5. Independent variable 6. Dependent variable • How close our measurements are to the true value • Repeated values show little variation • If the test is repeated and the same results are obtained • Does the experiment measure the correct variable • The variable that is measured to see the response to the change in the independent variable. • The variable that we change or manipulate

  4. Limitations

  5. Systematic Errors • Errors that are the same throughout the investigation. • e.g. A measuring device that is ‘out’ by a certain value, one of the controlled variables is always incorrect by the same quantity. • Results may still be precise, but not accurate.

  6. Random Errors • Occur when procedure not carried out in the same way each time it is performed. • e.g. Reading the apparatus differently every time, using any of the equipment a different way each time or due to variations in biological material used in experiment. • Some results will be affected, but not all. May cause one or more anomalous results.

  7. Processing results • Calculating mean, median, mode • Mean – average of all data collected. (add all values up and divide by number of results) • Median – middle value when all collected data listed in order of size. For even number of results, find the mid point of the two middle values. • Mode – The most common data value. (often tally or bar chart helps to identify) • Range – Difference between the smallest and largest values, or between the replicates of an experiment. • Calculating reaction rate (1/t, or depending on size of number, 100/t or 1000/t; t=time taken for reaction) • Calculating relative reaction rate (Choosing one reaction and comparing the other reactions to it) • Graphs: • Use range bars to show range of results around the mean • Calculate standard deviation (not till A2) but can use provided SD values for error bars on graph, the SD is plotted above and below the point).

  8. Rate Calculations • Relative Rate (different to rate of reaction, see previous slide) • If you compare your reaction rate to one of the other reactions.... Say 10mmol is the maximum in this experiment. You wish to calculate the relative speed of the other reactions to this one. • So: 10 (sec) / 20 sec (for 8mmol) = 0.5 relative rate • OR, percentage relative activity of enzyme: • Enzyme activity is at 100% at 4mmol • So for 8mmol percentage relative activity is • 40 (sec for 4mmol)/20 (sec for 8mmol) *100 • = 200%

  9. Evaluate your experiment (do this sheet at home after your quantitative!) Brief background to experiment What did the experiment intend to show? Could you formulate a hypothesis? What limitations were there? What effect on the results? How could the method be changed to overcome the limitation? Is there some way to process your data to show how significant/reliable it is? What was the data like? Were there any anomalies? Why? What conclusion could you draw from your results? What evidence do you have to support this conclusion?

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