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Range of Motion

Range of Motion. IB SEHS Internal Assessment. Internal Assessment. Lesson 1: -pre-lab -carrying out a standardised practical using handouts I will give you -thinking about how you could adapt the experiment for an Internal Assessment Lesson 2 and 3:

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Range of Motion

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  1. Range of Motion IB SEHS Internal Assessment

  2. Internal Assessment • Lesson 1: -pre-lab -carrying out a standardised practical using handouts I will give you -thinking about how you could adapt the experiment for an Internal Assessment • Lesson 2 and 3: -Using your Design Lab Training Sheet you will work in teams to design a practical investigating an aspect of osmosis. • Lesson 4 and 5: -You will carry out the practical and collect data as a team. • Lesson 6 and 7: -I will show you how to process your data with statistics! -specifically using Excel to calculate means, standard deviations and draw graphs • Lesson 8 and 9: -I will guide you on how to write a conclusion and evaluation • Lesson 10: -Your practical will be handed in -written up individually and in the correct format -self assessment should be complete as well

  3. Writing A Statement of the Problem for the Experiment What should it state? It should state: “The Effect of the IndependentVariable on the DependentVariable”. A good statement of the problem for pur experiment would be….. The effect of a limited range of motion of the knee on sprinting performance

  4. More about our variables: The independent variable is the variable that is purposely changed. It is the manipulated variable. The dependent variable changes in response to the independent variable. It is the responding variable. What is the “RoM” independent variable? Knee brace What is the dependent variable? Sprinting time

  5. Title for the photosynthesis experiment The effect of a limited range of motion of the knee on sprinting performance

  6. Another Look at Our Hypothesis INDEPENDENT VARIABLE If the RoM decreases, DEPENDENT VARIABLE then the sprinting time will increase. To make this IB worthy you MUST: a)Include a sketch graph of your predicted results b) Give SCIENTIFIC reasoning as to why you predict this

  7. Controls in an Experiment Factors that are kept the same and not allowed to change You MUST explain -what affect each CV could have on the reliability of the results if not controlled -how you are going to control them What should be kept constant in the experiment? • Age • Gender • Level of fitness • Health/dietary issues • Distance run and surface • Intensity of run • Construction of knee brace • Outside air temperature • Time of day

  8. Values of the Independent Variable How many different values of the independent variable should we test? Enough to clearly illustrate a trend in the data Always have 2 populuations for dicontinuous data (with one being the control) e.g. smokers and non-smokers Always use the 5x5 rule for continuous data e.g. 10cm, 20cm, 30cm, 40cm, 50cm

  9. Repeated Trials How many repeated trials are needed in the experiment Always have a minimum of 20 in each experimental group for discontinuous data Always have at at least 5 repeats for each range of the independent variable

  10. Drawing/photo of experiment Place a cardboard strip either side of the knee to stabilize it Wrap the bandage around the knee to hold the cardboard strips in place thereby stabilizing the joint

  11. Writing a method • EVERY step needs to be written with quantities, equipment and uncertainties ALL specified • You must take into account the ethical considerations of carrying out a practical • If you plan to use people in your experiment then you MUST ask them to sign consent forms

  12. Now complete your Design Lab sheet!

  13. Carrying out your practical… Qualitative Observations (must have these or zero for DCP1!!) • Pupils wearing looser clothing generally found it easier to run faster • Allpupilsstartedon a differentfoot

  14. Quantitative: Sample Data Table Title:The effect of changing glucose concentration on the rate of respiration Vol of C02 produced in 5 min (±0.01ml) TRIALS Concentration of glucose (%) Mean Vol of C02produced in 5 min (±0.01ml) 1 2 3 3.00 5.00 4.00 4.00 4.00 5.00 6. 00 5.00 6. 00 7.00 5.00 6.00 7.00 8.00 6. 00 7.00 9.00 7. 00 8. 00 8.00 10 20 30 40 50

  15. Data Processing for Internal Assessment AND Topic 1

  16. Data Processing • You need to: • Calculate the mean sprinting time for each group • Calculate the errorfor EACH mean • Plot a graphcomparing the times

  17. Two classes took a recent quiz. There were 10 students in each classEach class had an mean score of 81.5

  18. Since the means are the same, can we assume that the students in both classes all did pretty much the same on the exam?

  19. The answer is… No.The mean (mean) does not tell us anything about the distribution or variation in the grades.

  20. Here are scatter diagrams of the grades in each class:

  21. Mean

  22. So, we need to come up with some way of measuring not just the mean, but also the spread of the distribution of our data.

  23. Why not just give an mean and the range of data (the highest and lowest values) to describe the distribution of the data?

  24. Well, for example, lets say from a set of data, the mean is 17.95 and the range is 23. But what if the data looked like this:

  25. Here is the mean But really, most of the numbers are in this area, and are not evenly distributed throughout the range. And here is the range

  26. The Standard Deviation is a number that measures how far away each number in a set of data is from their mean.

  27. If the Standard Deviation is large, it means the numbers are spread out from their mean.If the Standard Deviation is small, it means the numbers are close to their mean. large, small,

  28. Here are the scores on the biology quiz for Team A: mean: 81.5

  29. The Standard Deviation measures how far away each number in a set of data is from their mean. For example, start with the lowest score, 72. How far away is 72 from the mean of 81.5? 72 - 81.5 = - 9.5 - 9.5

  30. Or, start with the lowest score, 89. How far away is 89 from the mean of 81.5? 89 - 81.5 = 7.5 - 9.5 7.5

  31. Now, lets compare the two classes again 81.5 81.5 4.88 15.91

  32. 6.1.3 State that the statistic standard deviation isused to summarize the spread of valuesaround the mean, and that within a normaldistribution approximately 68% and 95% ofthe values fall within plus or minus one ortwo standard deviations respectively.

  33. 6.1.4 Explain how the standard deviation is usefulfor comparing the means and the spread ofdata between two or more samples. • A small standard deviation indicates that the data is clustered closely around the mean value. • Conversely, a large standard deviation indicates a wider spread around the mean.

  34. Now...how do you do it the easy way?

  35. Concluding and Evaluating

  36. Conclusion This is the section where you draw conclusions about the experiment as it relates to your aim and hypothesis. Calculated results should be compared to values from the literature (i.e. accepted values from professional laboratories) where possible. This section should include: • Conclusion based on your Aim or Hypothesis. (using appropriate language) • States the quantitative or qualitative relationship • Correctly interprets the graph of the data • Includes relevant calculated values to support conclusion • Includes some elaboration based on the science being learned

  37. Discussion of errors and limitations to the experiment • Must comment on the “quality” of the results, do they make sense? • Identifies anomalous results where appropriate (use your SDs to help you do this!) • Prioritizes errors and suggests where they came from. • Utilizes the ideas of “systematic” and “random” errors in the discussion • Indicate what effect the error(s) would have on the results • Human errors should not be the main source of errors! • Suggestions for improvements • Identifies weaknesses in the experiment and suggests realistic suggestions for improvement • Improvements should help to improve the errors previously identified

  38. How to write an effective conclusion Also known as putting it all together

  39. What is a conclusion? • A conclusion is a summary of the experiment. • It is putting the hypothesis together with the data and coming up with a conclusion or ending thought. • It is a written answer to the original question.

  40. So where to start… • Every conclusion begins with a topic sentence. • In a conclusion, the topic sentence is the restatement of the problem/question.

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