Diese Präsentation wurde erfolgreich gemeldet.
Wir verwenden Ihre LinkedIn Profilangaben und Informationen zu Ihren Aktivitäten, um Anzeigen zu personalisieren und Ihnen relevantere Inhalte anzuzeigen. Sie können Ihre Anzeigeneinstellungen jederzeit ändern.

Science Inquiry: Conclusion and Presentation

591 Aufrufe

Veröffentlicht am

Conclusion & Beyond

Veröffentlicht in: Bildung
  • Als Erste(r) kommentieren

  • Gehören Sie zu den Ersten, denen das gefällt!

Science Inquiry: Conclusion and Presentation

  1. 1. Life Science Scientific Inquiry Conclusion & Presentation
  2. 2. Bonus: Your DV data ranges from 0 to 37 worms (per square meter). On a grid with 30 boxes along each axis, what value should you assign to each box? - 1.5 or 2 worms per box (always round UP to fit your range of numbers) 1. What is the average of this data set: 23 mm, 4 mm, 98 mm, and 37 mm ? • 40.5 mm (23 + 4 + 98 + 37 = 162 ÷ 4 = 40.5 mm ) 1. On which axis should the manipulated variable (IV) be placed? • X-axis (and the DV should be on the Y-axis) 1. What is the difference between quantitative and qualitative data? • Qualitative describes what type (with categories or verbal descriptions) • Quantitative describes how much or how many (with numbers) 1. True or False? Qualitative data should be displayed on a scatter plot line graph. • False (a bar graph or pie chart should be used) 1. What should always be included in the label of each axis on a graph? • UNITS!!!!! usually in parentheses: (mm) or (in grams) or (%) In your lab notebook, please answer as best you can: Week 30 Review Quiz
  3. 3. Data Presentation Checklist  Does your graph have a descriptive TITLE at the top?  Does each axis have a LABLE with UNITS?  Did you start the numbering on each axis at zero (0)?  Did you spread numbers out evenly along each axis?  Do the numbers in your data table and numbers on your graph match?
  4. 4. Interpreting Data • Graphs are often used to show the relationship between the independent variable and the outcome. 1. exercise/hair loss 2. income/SAT 3. driving practice/ accidents 4. sugar/sleep 1. 2. 3. 4.
  5. 5. Experiment Conclusion • After explaining what your data shows, state your CONCLUSION – Summarize your results (share average values) in a way that relates the numbers to your original scientific question. – Restate/rephrase your hypothesis as past-tense, filling in what actually happened. – Tell whether your data supports or contradicts your hypothesis – Example: • The measurements, when compared, showed an average 1.6 mm difference in length and .8 mm difference in width. The cast was almost identical in shape, but did not fit into the mold of the hypothesized animal because it was 7 mm smaller in width and 4 mm shorter length-wise. This does not support the hypothesis that the animal tracks were made by a skunk.
  6. 6. • If hypothesis is rejected – modify your hypothesis and perform another experiment • If hypothesis is supported – the experiment should be repeated to verify results • Either way, something was learned! – NEVER make up results simply because you think it was “supposed” to go differently – NEVER change your hypothesis before forming a conclusion What if My Hypothesis was Wrong?
  7. 7. Evaluating Error • EVERY experiment has errors – Uncontrolled variables • Weather, animal behavior, unexpected interruptions – Data collection errors • Inconsistent methods, accidents, contamination • Sloppy recording (can’t read writing, mixed numbers) • Be sure to record and note in your conclusion all errors and ways they could be corrected in future experiments.
  8. 8. What’s Next? • Include plans for further experimentation – Revisions: what would you do different next time? – New questions: revised hypothesis or different (but related) questions to investigate. • Include WHY you want to change things for your next experiment!
  9. 9. • Display most of the SI Packet info on a poster or tri-fold board. • Make LARGE FONT titles for these sections: – QUESTION – HYPOTHESIS – MATERIALS (list) – PROCEDURE – RESULTS (your data table & graph) – CONCLUSION • Colorful borders and graphics help info stand out. • Include photos, models, equipment, video, etc. Sharing Your Findings
  10. 10. 1. State problem and gather information 2. Formulate hypothesis Fact - Theory - Law
  11. 11. F = ma Fact - Theory - Law • Fact: – an objective, verifiable observation of something that occurs in our natural world – i.e. heat exchange, movement, gravity's effect, natural selection, etc. • Theory: – an explanation of how natural occurrences work • it can be observed, repeated, and tested with predictable results • A tested hypothesis often explains part of a theory (theories often incorporate many different hypotheses which are supported by much data). – i.e. Theory of Gravity, Theory of Evolution, Kinetic Theory of Matter • Law: – a verbal or mathematical description of observable phenomenon – i.e. Newton's Second Law of Motion: • or Newton's Third Law of Motion: "For every action, there is an equal and opposite reaction."
  12. 12. Scientific Law • Definition: A law in science is a generalized rule to summarize a body of observations in the form of a verbal or mathematical statement. – Scientific laws imply a cause and effect relationship between the observed elements and must always apply under the same conditions. – Scientific laws do not try to explain 'why' the observed event happens, but only that the event actually occurs the same way over and over. – Examples: • Kepler’s Laws of Planetary Motion • The Law of Conservation of Mass • Newton’s Universal Law of Gravitation
  13. 13. (Facts)

×