1. Inquiry

2. Jag Mark 2/16/11  Sciencespot: Experimental scramble

3. Jag Mark 2/17/11  Sciencespot: Experiment 1

4. Jag Mark 2/18/11  Sciencespot: Experiment 2

5. Classwork 2/17  Read Buckle down pages 4-14.  Complete questions and answers.

6. Jag Mark 2/21/11  Identify each of the following as either an observation or an inference about the object in the picture. It has red spots. It's a toy. It feels rough. It doesn't make a sound unless you move it. It's a soccer ball. It feels light. It smells bad. It's round It's squishy. It's used to play with.

7. Jag Mark 2/22/11  Describe a each type of graph and give an example of when to use each graph.

8. Jag Mark 2/23/11  Andrew and Alex set up an experiment to test how soil temperature and water temperature vary. The set up two beakers, one with 100 grams of water and one with 100 grams of soil, under a lamp and record the temperature of each every 5 minutes. What is the independent variable? What is the dependent variable? What are the materials? Is this a controlled experiment?

9. Jag Mark 2/24/11  Beginning with a question, write an outline of an experimental set up.

10. Jag Mark 2/25/11  Give three examples of qualitative data.  Give three examples of quantitative data.

11. Jag Mark 2/28/11  Choose the best type of graph to illustrate the following types of data. Percentage of elements in Earth’s crust Mass of fetus during gestation Deer population in Madison from 1950-2010 Number of each letter grade for first semester

12. Jag Mark 3/1/11  Test Day!  Clear desk except for sheet of paper and pencil.

13. Scientific inquiry  Scientific: Relating to the practice of science  Inquiry: A close examination of a matter in search for information or truth  Scientific inquiry: The ways in which scientist explore the natural world

14. How does Scientific Inquiry Work?  Scientific Method Ask questions Make observations and inferences Develop hypothesis Design experiments Make measurements Collect data Interpret data Draw conclusions Communicate

15. Ask Questions  Scientific inquiry begins with a question or a problem

16. Make observations and Inferences  Observation: Using one or more of your senses to collect data  Inference: An interpretation of an observation that is based on evidence or prior knowledge  Data: Facts, figures, and other evidence gathered through observation

17. Making Inferences  An inference is only one of many possible interpretations of the observation  Examples: Observation: Oil floats in water Inference: Oil is less dense than water. Observation: Lemon Juice has a pH of 4. Inference: Lemon Juice taste sour.

18. Developing Hypothesis  Hypothesis: A possible explanation for a set of observations or answer to a scientific question  A hypothesis must be something that can be tested and research based  Worded as an “If…, Then…” statement  Hypothesis can either be supported or disproved

19. Designing a experiment to test a hypothesis  After you state your hypothesis, you must design an experiment to test it.  An experiment is a carefully controlled test.

20. Experiment Variables  Variables: Factors that can change in an experiment  Manipulated (Independent) variable: The variable that is changed during the experiment.  Responding (Dependent) variable: The factor that changes because of the manipulated variable

21. 3 Kinds of Variables  Independent Variable – something that is changed by the scientist What is tested What is manipulated

22. 3 Kinds of Variables  Dependent Variable – something that might be affected by the change in the independent variable What is observed What is measured The data collected during the investigation

23. 3 Kinds of Variables  Controlled Variable – a variable that is not changed Also called constants Allow for a “fair test”

24. For Example:

25. Students of different ages were given the same jigsaw puzzle to put together. They were timed to see how long it took to finish the puzzle.

26. Identify the variables in this investigation.

27. What was the independent variable?  Ages of the students Different ages were tested by the scientist

28. What was the dependent variable?  The time it to put the puzzle together The time was observed and measured by the scientist

29. What was a controlled variable?  Same puzzle All of the participants were tested with the same puzzle. It would not have been a fair test if some had an easy 30 piece puzzle and some had a harder 500 piece puzzle.

30. Another example:

31. An investigation was done with an electromagnetic system made from a battery and wire wrapped around a nail. Different sizes of nails were used. The number of paper clips the electromagnet could pick up was measured.

32. What are the variables in this investigation?

33. Independent variable:  Sizes of nails These were changed by the scientist

34. Dependent variable:  Number of paper clips picked up The number of paper clips observed and counted (measured)

35. Controlled variables:  Battery, wire, type of nail None of these items were changed

36. One more:

37. The higher the temperature of water, the faster an egg will boil.

38.  Independent variable – temperature of water  Dependent variable – time to cook an egg  Controlled variable – type of egg

39. Last one:

40. The temperature of water was measured at different depths of a pond.

41.  Independent variable – depth of the water  Dependent variable – temperature  Controlled variable – thermometer

42. Designing Investigations

43. The greater the amount of soap in a soap and water mixture, the bigger a soap bubble can be blown.  Design an investigation to test this hypothesis. Identify the variables What exactly will be changed? How will it be changed? What exactly will be measured? How will it be measured?

44. The farther a ball drops, the higher it will bounce.  Design an investigation to test this hypothesis. Identify the variables What exactly will be changed? How will it be changed? What exactly will be measured? How will it be measured?

45. Controlled Experiments  Controlled Experiment: An experiment in which all of the variables except for one remain the same  Scientific experiments MUST be controlled!

46. Materials  List of all of the equipment and supplies needed to conduct the experiment. Example: water, ruler, beaker, salt, hot plate, stirring rod  Know what equipment is used to measure what. Balance: mass Graduated cylinder: Volume of liquid

47. Safety  Add any specific safety instructions for the lab. Wear goggles. May stain clothes. Flammable. Caution with glass.

48. Procedure  Step by step instructions outlining the process of testing the hypothesis.

49. Observations and Data  Qualitative data: description of results of experiment. The solution boiled.  Quantitative data: numerical data collected during the experiment. (May be expressed in a table and graph) The temperature of the solution was 112° degree.

50. Data  Discrete data is where there are only a finite number of values possible.  Ex. A 5 question quiz is given. The number of correct answers on a student's quiz is an example of discrete data. The number of correct answers would have to be one of the following : 0, 1, 2, 3, 4, or 5. There are not an infinite number of values.

51. Data  Continuous data is a type of data that is usually associated with some sort of physical measurement.  Ex. The height of trees at a nursery. Is it possible for a tree to be 76.2" tall? How about 76.29"? How about 76.2914563782"? The possibilities depends upon the accuracy of our measuring device.  One way to tell if data is continuous is to ask yourself if it is possible for the data to take on values that are fractions or decimals. If yes, it is usually continuous data.

52. Analyze Results  Calculate the measures of central tendency. Mean: average Median: middle Mode: most popular Range: distance from smallest  Modify the procedure if needed.

53. Graphs  A graph is a visual representation of data.

54. Bar Graphs  A bar graph displays discrete data in separate columns.  Advantages Visually strong Can easily compare two or three data sets  Disadvantages Graph categories can be reordered to emphasize certain effects Use only with discrete data

55. Line Graph  A line graph plots continuous data as points and then joins them with a line. Multiple data sets can be graphed together, but a key must be used. Independent variable on the x-axis Dependent variable on the y-axis  Advantages Can compare multiple continuous data sets easily Interim data can be inferred from graph line  Disadvantages Use only with continuous data

56. Pie chart  A pie chart displays data as a percentage of the whole. Each pie section should have a label and percentage.  Advantages Visually appealing Shows percent of total for each category  Disadvantages No exact numerical data Hard to compare 2 data sets "Other" category can be a problem Best for 3 to 7 categories Use only with discrete data

57. Conclusion  Include a statement that accepts or rejects the hypothesis.  Make recommendations for further study and possible improvements to the procedure

58. Communication  It is essential to communicate the results of an experiment in a lab report.  This report must be repeatable to be considered valid.