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Science is a process Scientific inquiry is a search for information and explanation
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Two Types of Scientific Inquiry
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Discovery Science - describes nature
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Two Types of Scientific Inquiry Discovery Science - describes nature Hypothesis-based Science – helps to explain natural phenomena
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Two Types of Scientific Inquiry Discovery Science - describes nature through observation Hypothesis-based Science - explains the observations & how biological systems work Both arrive at conclusions using logic and reasoning
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Types of Reasoning
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Inductive Reasoning flows from the specific to the general
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Types of Reasoning Inductive Reasoning flows from the specific to the general Deductive Reasoning flows from the general to the specific
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Discovery Science - Observations are made and recorded (data), may be qualitative or quantitative
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Discovery Science - Observations are made and recorded (data), may be qualitative or quantitative Examples: Cell description databases of DNA sequences chimpanzee behavior - Uses inductive reasoning
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Hypothesis-based Science
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-Seeks natural causes and explanation for observation
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Hypothesis-based Science -Seeks natural causes and explanation for observation (How & Why) -Uses deductive reasoning
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Applying hypothetico-deductive reasoning to a campground problem
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Hypothesis
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A possible explanation for a well-defined question
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Hypothesis A possible explanation for a well-defined question Proposed based on past experience and data made available through discovery science
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Hypothesis A possible explanation for a well-defined question Proposed based on past experience and data made available through discovery science Leads to a prediction which can be tested- measurable and controllable
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Steps of hypothesis-driven scientific inquiry
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Observation based on established knowledge
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Steps of hypothesis-driven scientific inquiry Observation based on established knowledge Question
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Steps of hypothesis-driven scientific inquiry Observation based on established knowledge Question Hypothesis
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Steps of hypothesis-driven scientific inquiry Observation based on established knowledge Question Hypothesis Prediction (if…….then) testable
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Steps of hypothesis-driven scientific inquiry Observation based on established knowledge Question Hypothesis Prediction (if…….then) testable Designing and conducting experiment (controlled)
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Steps of hypothesis-driven scientific inquiry Observation based on established knowledge Question Hypothesis Prediction (if…….then) testable Designing and conducting experiment (controlled) Obtaining results (data)
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Steps of hypothesis-driven scientific inquiry Observation based on established knowledge Question Hypothesis Prediction (if…….then) testable Designing and conducting experiment (controlled) Obtaining results (data) Analysis & Conclusion (whether data supports or does not support the hypothesis)
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Steps of hypothesis-driven scientific inquiry Observation based on established knowledge Question Hypothesis Prediction (if…….then) testable Design and conducting experiment(controlled) Obtaining results (data) Analysis & Conclusion (whether data supports or does not support the prediction and the hypothesis) Revision of hypothesis (if necessary)
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Theory
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A general statement about a comprehensive concept supported by much evidence.
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Theory A general statement about a comprehensive concept supported by much evidence. Broader than a hypothesis Brings together many conclusions
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Theory A general statement about a comprehensive concept supported by much evidence. Broader than a hypothesis Brings together many conclusions Example: The Cell Theory
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An explanation offered by a hypothesis must be for a question that is Well-defined Testable measurable controllable
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Elements of Experimental Design Identification of the: Independent Variable - the factor that will be manipulated/altered by the scientist from experimental setup to setup Dependent Variable - the factor that is counted, measured or observed Uncontrolled Variables - alternative independent variables that have not been accounted/compensated for that may impact results Controlled Variables - alternative independent variables we have accounted for (kept uniform among different groups) Instituting a control - a setup where the independent variable is held constant or omitted so that the control treatment serves as a benchmark, yielding either an expected positive or negative value/result.
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Presenting Results Data is presented commonly in two standard formats: Figures and/or Tables Figures include graphs, charts, diagrams, sketches, pictures/photos, etc. When in graphical format, figures need appropriately labeled axes Additionally, all figures need an appropriate label & title that have been correctly positioned below the graph For example:
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[Independent Variable (x-axis)] [Dependent Variable (y-axis)] Figure 1. Effect of CO 2 Concentration on Growth of Strawberry Plant Concentration of CO 2 (parts per million) Plant Height (centimeters) labelTitle (very descriptive)
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Choosing an Appropriate Graphing Format Line graph vs. Bar Graph vs. Scatter Plot Line Graph - used in the presentation of continuous data; plot separate data points and then connect the points using lines Bar Graph - used for data from separate distinct groups or non-numerical categories Scatter Plot - use data to determine how much one variable is affected by the other; the closer the data points come when plotted to making a straight line, the higher the correlation between the two variables, or the stronger the relationship - correlations can be positive (showing a proportional relationship) or negative (inversely proportional relationship)
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Tables are constructed with 2 columns and multiple rows - each column receives a heading with the left column representing the independent variable and the right column representing the dependent variable Tables also need an appropriate label & title that have been correctly positioned above the table For example:
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CO 2 Concentration (parts per million) Plant Height (centimeters) 55 107 15 2019 Table 1. Growth of Strawberry Plant When Exposed to Differing Amounts of CO 2 Gas.
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Labeling of Figures and Tables is conducted independently of one another For example, if there is a figure to start with followed by a table followed by two more figures followed by a final table, the labeling would occur as such: Figure 1. Table 1. Figure 2. Figure 3. Table 2.
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Observation: A person with high cardiovascular fitness has relatively lower resting pulse rate and a lower respiratory rate increase after exercise, and his or her pulse rate returns to normal faster than a less fit person Experimental Investigation: Lab 1
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Question: Are females more cardiovascularly fit than males? Hypothesis: Your simple tentative answer/statement to this question (does not require an explanation) Prediction: In the format of “If…., then….” Ex: If the hypothesis is true, and the step test is carried out, then females should demonstrate/have…(whatever specific result you would anticipate in support of the hypothesis).
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Designing an Experiment Cardiovascular fitness Determined by 1. increase in pulse rate (PR) after exercise. Measure PR before (resting rate) & after aerobic exercise (exercise rate) 2. Recovery time to resting pulse rate - how many minutes it takes to return to resting rate after exercise.
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