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Lab 1. Overview  Instructor Introduction & Syllabus Distribution Attendance – Don’t miss labs. Assignments – Things are due EVERY week. See calendar/table.

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Presentation on theme: "Lab 1. Overview  Instructor Introduction & Syllabus Distribution Attendance – Don’t miss labs. Assignments – Things are due EVERY week. See calendar/table."— Presentation transcript:

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2 Lab 1. Overview  Instructor Introduction & Syllabus Distribution Attendance – Don’t miss labs. Assignments – Things are due EVERY week. See calendar/table in syllabus.  Lab Safety (Students sign contracts).  Science, Hypothesis Testing, and Syllabus  Complete and turn in in-class exercise.  Termite Study Introduction.  Design and conduct your termite study.  Exercise due in Lab 2 discussion & questions

3 Science  Science = Knowing the world based on the belief that phenomena have natural, predictable causes that can be revealed by sensory (empirical) evidence.  Assertions must be testable (able to be rejected).  Scientific doubt - Can only say PROBABLY or NO ≈ SUPPORT or REJECT  Replication = repeating observations. More replication = More likely = better study  Quantification = making data numerical; increases precision and ability to repeat.

4 Scientific Studies  Comparative Studies = hypotheses predict patterns in nature  Experimental Studies = hypotheses predict patterns based on manipulation Experimental Group = given treatment Negative Control (Group) = treated like the exper. group, BUT does no treatment –The basis for comparison. Positive Control (Group) = treatment is applied to a situation with a known outcome – Identifies errors in the procedure.

5 Variables  Independent variable = manipulated or varying condition – On x-axis if graphed.  Dependent variable = measured response (usually quantitative; often called “the” data) – The y- axis if results are graphed. Descriptive Statistics = Summarize a set of data. Mean = Average  Probabilistic Statistics = Determine if groups of data show “chance” similarity. e.g., Can answer, “Is the difference between the means of my data taken for the experimental group and the negative control group significant?”

6 Using Data and P-Values P-value = “probability of error;” (0.05 =5%). P-value  0.05 = significantly different. Unpaired t-test = compares means; gives a P-value. Testing a Hypothesis of Difference Between Means 1.Compare Means to Hypothesis ↓ * If inconsistent with hypoth., reject the hypoth. * If consistent with hypoth., then do 2 ↓. 2.Use a t-test to Calculate a p-value * If p > 0.05, then reject the hypothesis (= not significantly different). (Treat means as “same.”) * If p ≤ 0.05, then the hypothesis is supported, the consistent means = significantly different.

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8 Scientific Investigations  Termites follow blue Papermate ® pen. Develop a hypothesis as to what they are following (sight, scent, touch, etc.) Develop and conduct a REPLICATED experiment involving QUANTITATIVE data to test your hypothesis. KEEP IT SIMPLE (2-3 conditions) MAKE PATH CIRCULAR WRITE DOWN YOUR QUANT. DATA READ the instructions (  ) in the manual

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