Stage 1 Biology - Key Ideas and Data Analysis

Stage 1 Biology - Key Ideas

• Design investigations with clear questions and potential solutions, possibly with implementation.
• Critique proposed investigations.
• Use findings from one experiment to develop subsequent experiments.
• Alter an independent variable to modify an experiment.
• Improve existing experimental procedures.
• Select appropriate methods for measuring dependent variables.
• Identify appropriate data collection types and volumes.
• Consider ethical and safety factors.

Representing Results

• Use appropriate SI units and symbols.
• Construct properly labeled tables.
• Create graphs (linear, non-linear, best-fit lines).
• Use significant figures.
• Choose and use appropriate representations (diagrams, equations, ratios, mathematical relationships).
• Explain concepts, solve problems, and make predictions using representations.

Data Analysis

• Identify trends, patterns, and relationships in data.
• Use interpolation/extrapolation when relevant.
• Select relevant evidence and scientific understanding to draw and justify conclusions.

Evaluating Uncertainty

• Identify sources of uncertainty (random and systematic errors).
• Evaluate the impact of uncertainty on experimental results.
• Consider repetition, sample size, accuracy, reliability, precision, and validity.
• Control variables effectively.
• Recognize limitations of conclusions.

Communication

• Communicate findings to specific audiences for specific purposes.
• Use appropriate language, terminology, conventions.

Microorganisms

• Microorganisms (bacteria, fungi, protists) are important living entities.
• Bacteria populations increase exponentially under ideal conditions.
• Factors affecting bacterial growth include temperature, nutrient availability, moisture, pH.
• Microorganisms decompose waste, recycling essential nutrients.
• Bacteria reproduce asexually.
• They play a role in human digestion, oxygen production, recycling, and genetic engineering.
• Humans have used microorganisms for about 10,000 years for preservation.
• Microbes cause food spoilage and controlled growth is crucial for preservation.
• Preserved food preparation techniques involve heat, cold, acids, salts, and sugar.
• Microbes cause infectious diseases.
• Distinguish infectious from non-infectious diseases.
• Pathogens have characteristics and transmission methods (air, dust, direct contact, faeces, food).
• Infectious diseases are interrelated with factors like pathogen persistence, transmission method, immunity levels and population mobility.

Pathogens and the Immune System

• Pathogens have traits enabling them to invade cells/tissues.
• Molecular recognition is key for entry and survival.
• Pathogens trigger an immune response.
• Antigens are substances that stimulate an immune response.
• Foreign vs. self-antigens are distinguished.
• The immune system (physical barriers, innate, adaptive) protects against infections.
• Adaptive immune response reacts to foreign antigens.
• Exposure to antigens leads to immunity—passive or active, through natural exposure to a pathogen or vaccination, or through antibody serum injections.

Biodiversity and Ecosystems

• Biodiversity includes variety in genetics, species, and ecosystems.
• Distinguish between species, populations, communities, and ecosystems.
• High biodiversity promotes ecosystem stability.
• Biological classification is hierarchical and relies on shared structures and molecular information.
• Nomenclature is a standardized system.
• Organisms have adaptations for survival and reproduction.
• Ecosystem components (biotic and abiotic) interact and establish relationships (e.g. energy flow, nutrient cycles).
• Understanding diversity, interactions, and keystone species is essential for healthy ecosystems.
• Human activities significantly impact ecosystems.
• Genetic diversity is essential for species' survival.

This quiz covers essential concepts related to designing scientific investigations in Stage 1 Biology. It focuses on data representation, analysis, and improving experimental procedures. Additionally, it emphasizes understanding trends and relationships in biological data.