Reliability vs. Validity

Transcription

1 Reliability vs. Validity Reliability (precision) is how _ the results are. Is there a large enough sample size? Are the measuring procedures accurate? Etc. Validity (accuracy) is whether the data measures. Are there any uncontrolled variables (besides the manipulated variable)? Could other factors be responsible for the results? Etc.

2 Data Table 1: Change in Temperature after Heating for 5 minutes Matter Trial 1 Trial 2 Trial 3 Trial 4 Trial 5 Average Sand 10 C 10.2 C 9.8 C 10.1 C 9.9 C 10 C Water 5 C 4.9 C 5.2 C 5.1 C 4.8 C 5 C Data Table 2: Growth of Radish Plant after 14 days Condition Plant 1 Plant 2 Plant 3 Plant 4 Plant 5 Average With Fertilizer Without Fertilizer 10 cm 7 cm 6 cm 14 cm 13 cm 10 cm 5 cm 6 cm 3 cm 7 cm 2 cm 5 cm Data table 1 is more reliable. However, this does not mean it has a greater validity. Experimental design must be analyzed. The greater range for the data in table 2 does not mean it is not a valid experiment. Results could be due to natural growth variation.

3 Discuss with your table partner: Determine whether each of the steps below would increase the reliability or validity of an experiment. Controlling an additional variable between the groups (e.g. using the same type of pen when testing the effect of color). Adding additional samples to each group in the experiment. Repeating the experiment in exactly the same way. _ Adding a control group to compare background measurements. _

4 Peer Review Scientists provide detailed procedures for peer review (evaluation by fellow scientists and others). - - _

5 Conclusions should: Conclusions - Be clearly stated. Explain what effect the manipulated (independent) variable had on the responding (dependent) variable. - Provide - Connect the data to the conclusion with explanatory language.

6 When writing a conclusion, do NOT use the word proved. In this class, we will never have a large enough sample size to prove anything. Scientists (even with much larger sets of data) use phrases like the data supported the conclusion that.

7 Discuss with your table partner: Analyzing Variables and Conclusions The following slides show a question from an EOC exam and give sample conclusions to the data. You will answer a few questions and review how well you understand the criteria for a conclusion by scoring the sample conclusions.

8 How Did That Plant Get Here? Directions: Use the following information to answer questions 1 through 7. Demetri did the following investigation in a local college laboratory to see how carbon dioxide (CO 2 ) affects plant growth. Demetri grew bean plants in growth chambers where he could control the amount of oxygen (O 2 ) and CO 2 in the air around the plants. He grew the bean plants in water with mineral nutrients instead of soil. Demetri had to completely dry the plants in an oven to get the plants dry mass. Question: What is the effect of different amounts of carbon dioxide (CO 2 ) in air on the dry mass of bean plants? Hypothesis: As the concentration of CO 2 in air increases, the dry mass of bean plants will increase because bean plants use CO 2 for growth. Materials: bean plants with the same mass water with mineral nutrients identical growth chambers labeled A, B, and C containers of CO 2 and O 2 gas monitors for CO 2 and O 2 gas oven balance

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10 Procedure: 1. Put 12 bean plants into Chamber A as shown in the Investigation Setup diagram. Do the same to Chambers B and C. 2. Make sure each chamber receives the same amount of light and water. Keep the chambers at a constant temperature and pressure. 3. Adjust the O 2 level of the air in each chamber to the normal amount of O 2 in the atmosphere. 4. Remove 4 bean plants from each chamber. Dry the plants in the oven and measure their dry masses. 5. Calculate and record the average dry masses as Day Set and keep the CO 2 level in Chamber A at 0 parts per million (ppm), Chamber B at 700 ppm, and Chamber C at 1,400 ppm. 7. Repeat steps 4 and 5 for Day 7 and Day 14.

11 Data: Amount of CO 2 vs. Bean Plant Dry Mass Amount of CO 2 (parts per million) Bean Plant Dry Mass (averages in grams) Day 1 Day 7 Day 14 0 (Chamber A) (Chamber B) ,400 (Chamber C)

12 Which two variables were controlled (kept the same) variables in this investigation? o A. Final bean plant dry mass and amount of light o B. Amount of CO 2 and type of growth chamber o C. Growth of plants and amount of O 2 o D. Type of plants and amount of O 2 Answer: _

13 Answer: _ Which variable was the responding (dependent) variable in this investigation? o A. Hours of light o B. Bean plant dry mass o C. Total days bean plants grew o D. Mineral nutrients in the water

14 Why did Demetri have growth chamber A adjusted to 0 ppm of CO 2? o A. To show bean plants can make their own CO 2 when none is available o B. To make the bean plants use oxygen for photosynthesis instead of CO 2 o C. To ensure the amount of CO 2 caused the differences in dry mass o D. To demonstrate that CO 2 is used by the bean plants for respiration Answer: _

15 Discuss with your table partner: On the following three slides are three sample conclusions from the data that was provided. Assess the following conclusions. Remember that a conclusion should : Clearly answer the investigative question Provide supporting data Explain how the data supports the conclusion

16 This experiment showed that carbon dioxide is good for plants. Plants that were grown with no CO 2 did not show an increase in mass after 14 days, while plants grown in the container that had 1400 ppm of CO 2 gained an average of 10 grams after 14 days. Attribute of Conclusion) Credit (0 or 1) Conclusive Statement: -_ Supporting Data for 0 ppm: Supporting Data for 1400 ppm Explanatory Language:

17 The effect of different amounts of CO 2 in the air on the dry mass of. bean plants differs with the level of CO 2. Higher levels of CO 2 make the plants grow more which raises the dry mass. This is shown when 1,400 ppm CO 2 renders an average dry mass of 10.8 g on the 14th day. Attribute of Conclusion) Credit (0 or 1) Conclusive Statement: Supporting Data for 0 ppm: Supporting Data for 1400 ppm Explanatory Language:

18 As the CO 2 increased in the air, the dry mass of the beans also increased. In Chamber A, the bean plants were exposed to no CO 2 and had a consistent mass of 0.8 grams. In Chamber. B, the beans were exposed to 700 ppm of CO 2 and had an average mass of 4.5 grams on day 7 and 8.6 grams on day 14. In Chamber C, the beans were exposed to 1400 ppm of CO 2, by far the most. Their mass on day 7 was 4.7 grams (on average) and their average mass on day 14 was 10.8 grams. This data shows a trend that as CO 2 levels the dry mass of the plant increased as well. Attribute of Conclusion) Credit (0 or 1) Conclusive Statement: _ Supporting Data for 0 ppm: Supporting Data for 1400 ppm: Explanatory Language:

19 Graphing Review Always place the responding (dependent) variable on the _ axis. Make sure the lines are numbered with When the data follows a trend but does not form a straight line, average out the variation by drawing a best fit line in which half the points are above and half the points are below the line.

20 Calculating the Slope of the Line Identify 2 points on the line. Calculate the change in the Y coordinates. (Rise) Calculate the change in the X coordinates (Run) _

21 Slope Units The unit for the slope is the _ The unit for the graph on the right would be One way to double check that you have set up the axes correctly is to see if the slope unit is correct.

22 Common Slope Calculation Mistake A common error in calculating the slope of a line is to count the number of lines up and over instead of finding the change in the Y and the X. This doesn t work on many graphs in science because the two axes often.