1. Results and Discussion Let’s revisit this assignment!

2. Find 1 person to work with and move your desks together O Take out the paper that you turned in (I returned them to you in your folder today). O Make sure that at least one of you has the assignment sheet and grading rubric. O Read through the assignment sheet and write down in your research notebook (left side) anything (words, or concepts) from the assignment that you are unclear about.

3. Start with experimental design… O First, can you explain exactly what you did in your experiment? O What was your IV? Did you have multiple IVs? O What was your DV? O How many trials did you perform? O Based on your background research (take a look at that paper too!), what would you expect to happen in your experiment? O What were your null and alternate hypotheses?

4. Now let’s look at the data… O What trends do you notice in your RAW data? How does this compare to what you expected to happen? O How do your descriptive statistics (mean, median, mode, range, variance and standard deviation) describe your data? O What is your p-value? What does the p- value tell us?

5. Logic of Statistical Testing O Inferring from samples – INFERENTIAL STATISTICS O Scientists collect data from a sample and determine whether or not that sample provides EVIDENCE AGAINST the null hypothesis. O If the null hypothesis is true, what is the probability we would have randomly chosen a sample with the values we observed? O Analysis: O By looking at our probability of obtaining 80% or 8 heads in a sample of 10 flips, we can make a decision. O PROBABILITY IS OFTEN CALLED THE P value

6. Statistical Significance O Need a cut point for the p-value O Common “cut points”: 0.05, 0.01,.001 O If P value < 0.05, you say the result is “statistically significant” and you reject the null hypothesis. If the null hypothesis is true, the probability of randomly getting the observed sample is unlikely. This provides evidence against the null hypothesis and we would REJECT the null hypothesis, suggesting one of the alternative hypotheses were correct.

7. Statistical Significance O If P value > 0.05, O You say the results were “not statically significant” O If the null hypothesis is true, the probability of randomly getting the observed sample is likely. O This does not provides evidence against the null hypothesis and we would FAIL TO REJECT the null hypothesis, allowing us to reject the alternative hypotheses.

8. Statistical Tests/Hypothesis Testing/Inferential Test: O All statistical tests provide a P value that is the probability that your results would have occurred if the null hypothesis were true.

9. Statistical Tests/Hypothesis Testing/Inferential Test: O All statistical tests provide a P value that is the probability that your results would have occurred if the null hypothesis were true. O They use information from your data (mean, standard deviation, etc.) to figure out a probability based upon a population that meets the null hypothesis (much like coin simulation).

10. Statistical Tests/Hypothesis Testing/Inferential Test: O All statistical tests provide a P value that is the probability that your results would have occurred if the null hypothesis were true. O They use information from your data (mean, standard deviation, etc.) to figure out a probability based upon a population that meets the null hypothesis (much like our card simulation). O You use the p-value to make a data-driven decision

11. So what do you do with this information? O If the p-value says “fail to reject” the null hypothesis, but you see a significant trend in your raw data, more trials is the way to go, especially if the trend is what you would expect based on your background research.

12. What if the trend is not what you expected? O If the trend in your data is not what you would expect based on your background research, then you need to examine the science further (more background research).

13. Examining the science O Here are some ideas to consider: O pH: all living tissue has BUFFERS which resist changes in pH up to a certain point; enzymes begin to denature at certain pH values O Temp: enzymes begin to denature at certain temperatures. O Enzyme/substrate concentration: perhaps you do need to consider the “freshness” of your sample as well as the starting concentration before you doubled or diluted it.

14. Flaws in your technique O Yes, of course you are not a perfect person and you are also quite inexperienced in working in a lab, so there is lots of room for improvement here, BUT… O If the methodology is “tried and true” (which for all of you it was), then the better way to improve your results is to dig deeper into the science, in addition to practicing those skills and being more consistent in your techniques.

15. Nuts and Bolts O Proof read your work!!! Please! Out loud! O Do not Capitalize Words that Are Not Proper Nouns unless they begin a sentence! O Format your data tables and graphs to fit on the page completely. There’s no magic button, just a lot of trial and error to make it look right! O Do not waste paper. Double space, and remove extra space between sections.

16. Next Steps… O Use this information to revise your paper. O Ask questions in Titan Time or before/after school. O Resubmit your paper by next Friday (yes, it’s an A DAY, so put it in your block’s box even if I’m not in the room!)