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Lecture

Bio 270 pre lab.docx

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Department
Biology
Course
BIO270H1
Professor
Chris Garside
Semester
Fall

Description
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  Control variable: is constant or impact that is removed b. conducting the experiment  Conduct the experimental groups and control groups  Negative control: group with no manipulation  Positive control: research question will call for a control that is manipulated in some way  Solvent control group/placebo: another treatment may examine the solvent used in the experiment c. Organization and Analysis of Data  i. Calculate the mean and standard error of the mean  ii. Decide whether you will use tables, graphs or drawings  iii. Determine if you see any trends or patterns  iv. Data is controlled and there are statistical tests (the test and the one-way ANOVA)  t-test compares sample populations  p-value the probability that t falls in a certain change  p-value < 0.05 suggests a significant different: reject null hypothesis  p-value > 0.05 suggest we do not reject the null hypothesis  Unpaired t-test used when you have independent samples. Samples are not directly to one another  Paired t-test: when samples are related  ANOVA is a stats analysis  1. Number of treatments increases is better  2. We reject the null with the null hypothesis with 95% 4. Reflectin
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