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Science Inquiry: Data Collection and Analysis

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Sci method, part 3

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Science Inquiry: Data Collection and Analysis

  1. 1. Life Science Scientific Inquiry Data Collection & Analysis
  2. 2. Bonus: What do IV and DV stand for and what are they? - IV = independent variable (the thing you change to test its effect) - DV = dependent variable (the result or thing that responds to the IV) 1. What is a scientific procedure? • A detailed, step-by-step set of instructions for performing an experiment and gathering data. 1. What type of units should you use for measuring the responding variable? • Metric units (SI units such as millimeters, liters, seconds, grams, m/s, or Celsius) 1. True or False? You should try your best to collect subjective data in order to eliminate bias in your experiment. • False (objective data is less prone to experimenter bias) 1. What part of your hypothesis should describe the IV? • The “IF…” phrase 1. Where/how should experiment results be recorded? • In a data table (in your lab notebook, then transferred neatly to SI worksheet table) • IV in left-hand column, DV across to the right, averaged values at far right column In your lab notebook, please answer as best you can: Week 29 Review Quiz
  3. 3. Data Collection • As you perform the experiment, observations and data must be recorded. – measurements listed in a chart – written observations – drawings – photos Soil Type (Independent Variable) Number of worms (per m2 , 3 cm deep) (Dependent Variable) Day 1 Day 2 Day 3 Day 4 Day 5 Average Compost Bark dust Dirt with compost Backyard dirt
  4. 4. Data Analysis • Next, graph the data to show cause/effect – Numbers, observations, and measurements are broken down, organized, and studied – Graphing the data allows patterns to emerge, showing cause-and-effect relationships • Independent Variable on the X-axis • Dependent Variable on the Y-axis – Label each axis – Include units and a title
  5. 5. Qualitative vs Quantitative Data • Does the IV describe a quality or quantity of something? – If it can be measured with numbers, then it is quantitative. If not, then it’s qualitative. • Incubator warmth • Hours of sleep • Surface texture • Brand of soda • Type of fruit • Distance travelled • Saltiness of water Quantitative Quantitative Qualitative Qualitative Qualitative Quantitative Quantitative
  6. 6. Which Type of Graph? • A quantitative IV should use a line or scatter plot graph. • A qualitative IV must use a bar graph or pie chart. The three sample in each group of the bar graph should be combined into average values.
  7. 7. Sample Line Graph
  8. 8. Scatter Plot • Assign number values at even intervals. – Divide largest value by the number of lines/boxes. • Graph each data point. • Draw a “best fit” line through the points. • What type of data does this graph show? - We can’t tell what the numbers mean because there are no LABELS or UNITS!
  9. 9. Bar Graph • What is the IV? – Type of bread. • What is the DV? – Mold growth. Pie Chart • Shows parts of a whole (not cause-and-effect). – IV = Skittle color – DV = How many per bag
  10. 10. Graphing Exercise Hummingbird Preferences Study Jams Video What was the IV (manipulated variable)? (birdfeeder color) How was the IV changed? (4 different colors of birdfeeders were tested) What was the DV (responding variable)? (amount of food eaten) How was the DV measured? (by taking pictures of the feeders each day) How many trials did Mia perform? (seven days = 7 trials) What type of data was collected? (subjective) What type of graph should Mia use to show her results? (there is no numerical data, it cannot be graphed)
  11. 11. Graphing Objective/Qualitative Data Hummingbird Syrup Missing from Feeder at end of day (ml) Sept 8 Sept 9 Sept 10 Sept 11 Sept 12 Sept 13 Sept 14 Average Red 350 227 412 448 325 276 365 343 ml Blue 22 7 15 19 8 15 10 14 ml Green 11 9 7 5 12 5 10 8 ml Yellow 30 45 67 69 69 72 33 55 ml What type of graph should be used to display these results? (a bar graph)
  12. 12. AverageSyrupEatenEachDay(ml)
  13. 13. Experiment 29 Can Eggs Float?
  14. 14. EXPERIMENT 29 - Observation In your lab notebook, write our question (what we are curious about or the problem/objective): Can an egg float in water? What do we already know? (write this down, too!) • Normally, eggs don't float in water. – Have you ever boiled eggs on the stove? • People float easier in the Great Salt Lake than in swimming pools. • Boiled eggs might be denser than raw eggs. What did we learn after researching the topic? • Salt doesn't disappear, it disassociates (separates and fits between H2O molecules) in water. This is the "look around" or "make observations" step.
  15. 15. EXPERIMENT 29 - Hypothesis Write down your hypothesis: • What do you think will happen? – This should answer your "question" formed in the OBSERVATION step of the scientific method. If we dissolve enough salt in water, then an egg will ____________________ because ____________________.
  16. 16. EXPERIMENT 29 - Experiment Materials: • A tall glass • Graduated cylinder or beaker • An egg • A measuring spoon • A spoon for stirring • Water • Salt • Paper towels Procedure: (from ECGS pg. 60) • Fill a cup with 300 ml of water. • Drop an egg (carefully) into the cup of water. Record whether it sinks or floats in your laboratory notebook. • Use the spoon you have for stirring to pull the egg back out of the glass. **Let it drip in the glass so that you do not lose too much water. • Add 5 ml of salt to the water and stir with your stirring spoon until the salt is dissolved. • Set the egg (carefully) into the cup of water. Write down any difference between how the egg behaved before and how it behaves this time. • Repeat steps (C) - (E) a total of 6 times. Each time, note the difference (in your laboratory notebook) how the egg behaves. If the egg's behavior does not change even after you have repeated steps (C) - (E) 6 times, continue to repeat the steps until you see a difference. • Clean everything up and put it all away.
  17. 17. EXPERIMENT 29 - Data Collection In your lab books, make a chart like this: Water Salt (ml) Float or Sink Observations Trial #1 Trial #2 Trial #3 Trial #4 Trial #5 Trial #6 Trial #7 Trial #8
  18. 18. EXPERIMENT 29 – Raw Data Let's analyze the data: This is a great way to organize your data. Water Salt (ml) Float or Sink Observations 300 ml 0 Sink (2cm) Egg sank down quickly - had to use spoon to keep from cracking 300 ml 5 Sink (2cm) No difference in egg, water looks a little cloudy 300 ml 10 Sink (2cm) Sank down slower 300 ml 15 Sink (2cm) 300 ml 20 Sink (6cm) Sort of bobbed around a little before sinking halfway down 295 ml 25 Float (12 cm) Sank down halfway, then came to top 290 ml 30 Float (12 cm) Stayed at top, water so murky we can barely see the egg 280 ml 35 Float (12 cm) Part of the egg floated above the surface of the water Look for patterns, trends, or correlations. Compare multiple trials and consider throwing out crazy data.
  19. 19. EXPERIMENT 29 – Data Analysis Let's analyze the data: Visual record of the data Patterns, trends, correlations, and erroneous data are easy to spot on a graph. 0 2 4 6 8 10 12 14 0 5 10 15 20 25 30 35 EggFlotation Salt (ml) in 300 ml water
  20. 20. EXPERIMENT 29 - Conclusion Does the data support your hypothesis? Based on the data we collected, our eggs floated when at least ____ ml of salt were added to 300ml tap water. Write your conclusion: This supports our hypothesis that if we add enough salt to water, an egg can float because... Then SHARE your findings: Report to the class what you discovered through oral presentation and/or written report. Include modifications & sources of error: Egg “floatiness” could be measured by distance from bottom.

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