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# BIO270H1 Lecture Notes - Null Hypothesis, Confounding, Dependent And Independent Variables

Department
Biology
Course Code
BIO270H1
Professor
Chris Garside

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Bio 270 pre lab
1. Formulate a Question from an Observation
A scientist observes, perceives
It is important to formulate a question based on what they observe
Ex. “Does consumption of caffeine of caffeine found in coffee increase heart rate?
2. Develop a Hypothesis
Proposed explanation: hypothesis
Hypothesis can be confirmed but is never true
Biological hypotheses independent and dependent variables
B (dependent (measured variable))
A (demonstrating a relationship between them)
Hypothesis is testable
Researchers must have a null hypothesis
Predicts that there will be no effect on the independent variable will not affect the dependent
variable
3. Designing and conducting Experiments to test the hypothesis
It is important to design and organize the experiment properly
Confounding variable: an extraneous variable that can affect the results, you collect do not
reflect the actual relationship between the variables
Confounding variable: might be that some of the students and an exam in class whereas the
others did not
They can be controlled
Random variation: quantifies the extent to the individuals in a sample
There could be random variation between the Daphnia’s heart
Replication: taking a number of measurement
Do a number of replications
Replication can allow for less experimental error
Randomisation: The process is choosing a wider population to sample
This is used to avoid bias
Intra-observer variability: imprecision introduced by human error: systemic error
Inter-observer variability: several observers
Observer effects: observing a biological system will change the way it behaves
To reduce errors there are control groups
The two group must be exactly the same and one condition changed
Two groups experimental and control group
Independent (manipulated) variable: variable or interest which is intentionally changed by the
experiment
Dependent (responding) variable: A variable that can be counted or observed
Underlying assumption in experimental design is that the independent variable is the one
affecting the dependent variable