Foundations of Life Sciences: The Scientific Method

Foundations of the Scientific Method

• Definition of the Scientific Method: It is an objective approach utilized for answering specific questions within the field of Science.

• Core Components: The method relies on a structured cycle of three primary activities:

  • Observation: Noticing phenomena of interest within a specific field of study.

  • Analysis: Processing data and experimental results to determine significance.

  • Experimentation: Conducting tests to validate or refute explanations.

• Limitations of the Scientific Method:

  • Data Applicability: It can only be applied to situations where concrete data can be collected.

  • Requirement for Testability: The situations must be testable through physical or observational means.

  • Proof vs. Refutation: The method often does not definitively prove something to be true in an absolute sense; rather, it is used to refute false claims.

Hypotheses and Theories

• Hypothesis:

  • Defined as a proposed explanation for a specific phenomenon.

  • Formatting: Typically structured as an "$If/then$" statement.

• Theory:

  • Defined as a substantiated explanation of some aspect of the natural world.

  • Grounding: Supported by rigorous experimentation performed on several underlying hypotheses.

  • Evolution: Theories are not static; they may change or be refined as more data becomes available.

The Seven Steps of the Scientific Method

• Step 1: Make an Observation:

  • Requirement: Identify what is happening of interest to you and your specific field.

  • Example: Current antibiotics are determined to be no longer very effective against staph infections.

• Step 2: Ask a Question:

  • Requirement: Investigate the potential reason(s) for the initial observation.

  • Example: Can new antibiotics be identified to treat staph infections?

• Step 3: Research Current Literature:

  • Requirement: Gather data on existing knowledge and identify what related experiments have already been conducted.

  • Example: Discovery that several fungal alkaloids have been shown to possess antibacterial properties.

• Step 4: Formulate a Hypothesis:

  • Requirement: Based on research and observations, predict a specific explanation or outcome.

  • Example: $If$ Staphylococcus is exposed to fungal extracts, $then$ their growth will be inhibited.

• Step 5: Test the Hypothesis:

  • Requirement: Set up experiments to physically determine if the predicted outcome occurs.

  • Example: Staphylococcus cultures are exposed to various fungal compounds and placed into incubation.

• Step 6: Measure, Record, and Analyze Results:

  • Requirement: Arrange all collected data into appropriate groups. Graphing is used to provide a visual display of results.

  • Goal: Determine if the raw data supports or refutes the formulated hypothesis.

  • Example: Findings indicate that compounds $F1$, $F6$, and $F8$ display inhibitory action against Staphylococcus.

• Step 7: Retest:

  • Requirement: Determine if the results are repeatable. This is primarily done if the hypothesis is supported.

  • Example: A repeat of the previous experiment provides consistent inhibitory results for the compounds $F1$, $F6$, and $F8$.

Principles of Experimental Design

• Importance of Controls: These are essential to ensure proper design and allow for a comparison of results.

• Variables: Defined as the changing conditions within an experiment.

• Groups: Categories into which test subjects are organized.

• Double-Blind Design: Considered the best design for experimentation. In this setup, both the experimenter and the test subjects do not know who is receiving which treatment, reducing bias.

Control Mechanisms

• Purpose: Controls are known situations used as benchmarks.

• Positive Control:

  • A scenario where the phenomenon is expected to occur.

  • Function: Shows what a positive result should look like.

• Negative Control:

  • A scenario where no phenomenon is expected to occur.

  • Function: Shows what a negative result should look like.

Types of Experimental Variables

• Independent Variable:

  • The condition that is changed by the experimenter.

  • Goal: It is the potential cause of a change in result.

  • Constraint: Only one independent variable should be changed at a time.

• Dependent Variable:

  • The measured outcome or effect of the experiment.

  • Management: Several replicants must be used to allow for averaging of the results.

• Control Conditions (Controlled Variables):

  • Conditions that have the potential to change but are intentionally prevented from changing.

  • Function: They limit the independent variable to a single factor to ensure the result is caused by that factor alone.

Categorization of Test Groups

• Control Group:

  • Definition: The group of test subjects that receives no treatment or is given the standard treatment.

  • Interaction: The independent variable is not applied to this group.

• Experimental Group:

  • Definition: The group of test subjects that have one specific variable applied.

  • Interaction: The independent variable is applied to this group.

• Replicants: Each group (control and experimental) must contain several replicants to ensure statistical validity.

Case Study Application: Staphylococcus Growth Experiment

• Negative Control Group: Staphylococcus cultures treated with distilled water ($5$ tubes).

• Positive Control Group: Staphylococcus cultures treated with a known effective antibiotic ($5$ tubes).

• Experimental Groups (Fungal Compound Testing):

  • Group 1: Staphylococcus treated with $5\,\mu l/ml$ of compound $F1$ ($5$ tubes).

  • Group 2: Staphylococcus treated with $5\,\mu l/ml$ of compound $F2$ ($5$ tubes).

  • Group 3: Staphylococcus treated with $5\,\mu l/ml$ of compound $F3$ ($5$ tubes).

  • Group 4: Staphylococcus treated with $5\,\mu l/ml$ of compound $F4$ ($5$ tubes).

• Practical Observation Example: A common observation used to start the scientific process is noticing that tomato plants do not grow as well as desired.