Designing Your Own Experiment

  • Hypothesis: an explanation of an observation, written as a statement and testable.  Can be based on previous knowledge

  • Variables
  • a characteristic or property capable of taking on a range of values and with the potential to affect things
  • Independent variables: variable set before starting the investigation
  • Dependent variables: variable that is measured during the investigation
  • Control variables: factor kept the same in the investigation

  • Parts of Experimental Method
  • Aim- purpose of the experiment
  • Hypothesis
  • Prediction
  • Method: physical steps required to test hypothesis and predictions
  • Things to consider
  • Materials needed
  • Variable
  • Sample size and replication of experiment

  • Experimental Design
  •  Preliminary
  • Aim and hypothesis
  • Hypothesis and predictions are testable with resources available
  • Assumptions and variables
  • Awareness of assumptions that you are making in experiment
  • All variables are identified
  • Independent variable range has been set
  • Layout of experiment considered

  • Data Collection
  • Units for all variables have been identified
  • Amount of data to be collected has been identified
  • Consideration of how data will be analyzed
  • Method for systematically recording results

  • Repeat or Trials: investigation that is carried out again at a different time
  • Ensures experiment is reproducible and data is consistent

  • Treatments: well defined conditions applied to the sample
  • Specific and predetermined

  • Sample
  •  subset of a whole used to estimate the values that might have been obtained if every individual was measured
  • Data
  •  What is it going to look like? -> data table or graph
  • Things to consider: How are you going to arrange your data?
  • Data presentation: Table: allows one to organize data in a way that shows relationships
  • Graph: Visual image is easier to see

Statistical Analysis

  • Why use it?
  •  Science requires observations and collections of measurable data
  • Ex. Investigation question is what is the height of bean plants growing in the shade?
  • How many bean plants to study?
  • Can’t study thousands of bean plants b/c time, money and land, labor
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  • Need to take a sample of bean plants to represent the population of all bean plants
  • Need to get a representative sample

  • Statistics:
  •  helps sample small portions of habitats, communities, biological populations to draw conclusions about the larger population
  • Measures differences of the relationships between the sets of data
  • Compare small populations of bean plants in sunlight vs. shade
  • Depends on sample size, mathematically form conclusion with a level of confidence

  • In science, level of confidence is usually around 95%, can never be 100
  • Statistics- can be describe conditions in countries around the word
  • Data ...

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