PRP1001/JHX1003 Research Methods 1 Lecture Notes PDF

Dr Simone Calabrich PRP1001/ JHX 1003 Class Notes What is Science? Science is the systematic study of the structure and behaviour of the physical and natural world through observation and experiment. It involves using empir...

Dr Simone Calabrich PRP1001/ JHX 1003 Class Notes What is Science? Science is the systematic study of the structure and behaviour of the physical and natural world through observation and experiment. It involves using empirical methods to gather knowledge, test hypotheses, and understand natural phenomena. 1. Systematic Systematic refers to an organised and methodical approach. In science, this means following a structured process for studying phenomena. It involves clear steps—like making a hypothesis, collecting data, analysing results, and drawing conclusions. Being systematic ensures that scientific research is consistent, replicable, and objective, which helps eliminate bias and errors. 2. Observation Observation is the act of carefully watching or monitoring something in the physical world. It involves gathering data about events or conditions as they naturally occur. Scientists use their tools (like microscopes or telescopes) to observe phenomena. For example, watching how plants grow in different environments is an observation. Observations are crucial for identifying patterns and forming hypotheses. 3. Experiment An experiment is a controlled test designed to explore or verify a hypothesis. In experiments, scientists manipulate variables to observe the effects and outcomes. For example, if a scientist wants to test whether sunlight affects plant growth, they would conduct an experiment by growing plants with and without sunlight, comparing the results. Experiments allow scientists to explore cause-and-effect relationships and test specific predictions. 1  Dr Simone Calabrich Science builds on previous knowledge. This is one of the key characteristics of scientific progress. 1. Each new scientific discovery builds on earlier findings. Scientists don’t start from scratch; they use established theories, data, and methods as a basis for new research. 2. Science often involves refining or expanding existing knowledge. For instance, new technologies or methods can allow scientists to examine old theories in more detail or apply them in new ways. A scientific theory may evolve as new evidence emerges, providing a more accurate understanding of a phenomenon. 3. Scientific knowledge also grows by correcting errors in previous understanding. Sometimes new experiments or observations disprove earlier ideas, leading to revised theories. 4. Scientists collaborate and share their research through publications and conferences. New studies often cite previous research, building on the results of other scientists. This collective effort helps science advance more quickly, as knowledge is shared and built upon globally. Saying that something has scientific status is important because it indicates that the idea, theory, or claim is based on a rigorous, reliable, and systematic approach to understanding the world. Here are several key reasons why this is important: 1. Reliability and Credibility  Scientific status signifies that a claim has been subjected to empirical testing, observation, and experiment, and follows the principles of the scientific method. This gives the claim credibility because it has undergone a rigorous process to verify its accuracy, minimising personal biases, guesswork, or unfounded opinions. 2. Objectivity  Science strives for objectivity, meaning that the findings are based on facts, not influenced by personal beliefs or opinions. When something has scientific 2  Dr Simone Calabrich status, it means that the results are replicable by other researchers under similar conditions, providing consistency and transparency in the findings. 3. Falsifiability and Testability  Scientific claims are testable and falsifiable—meaning that they can be proven wrong through evidence. This is important because science is self- correcting: if new data contradicts an accepted theory, the theory is reevaluated or refined. Non-scientific claims often lack this openness to testing and falsification, which limits their reliability. 4. Evidence-Based  When something is labelled as having scientific status, it means it is based on evidence gathered through observation and experimentation. This distinguishes it from opinions, beliefs, or pseudoscience, which might rely on anecdotal evidence or assumptions that lack empirical support. 5. Predictive Power  Scientific claims often have predictive power, meaning they can help us make accurate predictions about future events or outcomes. 6. Public Trust and Policy Impact  Scientific status can affect public trust and decision-making. Policies related to public health, technology, and environmental protection often rely on scientific findings. For example, climate change policies are guided by scientific evidence on global warming. Labelling these findings as "scientific" reassures the public and policymakers that they are based on solid research and evidence, leading to more informed decision-making. 7. Ethical Responsibility  Scientific status also implies a certain level of ethical responsibility. Science must adhere to ethical guidelines, ensuring that methods are fair, data is 3  Dr Simone Calabrich accurately reported, and studies are conducted with integrity. This is especially important in fields like medicine, where people's lives and well- being depend on the accuracy of scientific research. The results of many scientific studies are not always replicable or reproducible, and this has been a major issue in certain areas of research, particularly in fields like psychology, biomedical science, and social sciences. This phenomenon is often referred to as the replication crisis or reproducibility crisis. 1. What Does Replicability/Reproducibility Mean?  Replicability refers to the ability of other researchers to achieve the same results using the same methods and conditions in an independent study. For example, if a scientist performs an experiment and gets a certain result, others should be able to replicate that result if they follow the same steps.  Reproducibility can sometimes refer to reanalysing the original data and getting the same results, or more broadly, achieving consistent outcomes when applying the same procedures in different settings or conditions. Example Scenario: Imagine a team of scientists conducts a study to test how plant growth is affected by different amounts of sunlight. They use a specific type of plant, specific soil, and follow a detailed protocol. At the end of the study, they conclude that plants exposed to 8 hours of sunlight per day grow faster than those exposed to 4 hours of sunlight per day. Now, let's see how this study could be evaluated for replicability and reproducibility: Replicability Example: Replicability refers to whether another group of scientists can follow the exact same methods as the original study and get the same results. 4  Dr Simone Calabrich 1. New scientists follow the exact protocol from the original study: they use the same type of plant, the same soil, the same watering schedule, the same temperature conditions, and the same amounts of sunlight (4 hours vs. 8 hours per day). 2. If the new scientists perform this experiment in identical conditions and observe that the plants exposed to 8 hours of sunlight also grow faster (just like in the original study), then the study is said to be replicable. 3. If they get different results, such as no difference in growth rates, it means the original study lacks replicability, raising concerns about the reliability of the findings. Reproducibility Example: Reproducibility refers to whether the same results can be obtained by analysing the original data or performing a similar study in a different setting. 1. Reproducibility by Reanalysing Data: o Suppose another researcher does not run the experiment again but instead re-analyses the original data from the first experiment (the same data the original researchers collected). o If the new analysis using the same data leads to the same conclusion (8 hours of sunlight leads to faster growth), the study is said to be reproducible by reanalysis. o If the reanalysis shows discrepancies, such as mistakes in how the data was processed or interpreted, it suggests the original study lacks reproducibility. 2. Reproducibility by Conducting a Similar Study: o Now, imagine another research team in a different country tries a similar experiment but with some differences. For example, they use a different plant species or change some environmental factors (such as temperature or soil type), while still comparing plants exposed to 4 hours vs. 8 hours of sunlight. 5  Dr Simone Calabrich o If this modified study still finds that plants with 8 hours of sunlight grow faster, it shows reproducibility across different conditions, suggesting that the general finding (more sunlight leads to faster growth) is robust and reliable. o If the modified study finds no such effect, it means the original study lacks reproducibility under different conditions. 2. Why Are Some Studies Not Replicable? Several factors contribute to the failure to replicate results in science: a. Poor Methodology  Some studies suffer from weak experimental design, small sample sizes, or improper statistical analysis, leading to unreliable or biased results. These issues make it hard for others to reproduce the findings. b. Publication Bias  Scientific journals tend to prefer publishing positive or novel results rather than negative or null results. This means that studies with exciting, unexpected outcomes are more likely to be published, even if those results are due to chance or methodological flaws. As a result, such findings may not hold up under further testing. c. P-Hacking and Data Manipulation  Some researchers, either intentionally or unintentionally, engage in p-hacking —the practice of manipulating data or testing many hypotheses until a statistically significant result is found. While these results may be statistically significant, they are often not replicable because they were produced through selective reporting. d. Complex Variables and Uncontrolled Conditions  In some areas of research, particularly in social sciences and biomedicine, there are many complex and interacting variables that are hard to control. Different labs may have slight variations in procedures, equipment, or even environmental conditions that can lead to different results. 6  Dr Simone Calabrich e. Lack of Transparency  Sometimes, researchers don’t fully disclose all the methods or raw data used in their studies, which makes it difficult or impossible for others to replicate their work accurately. 3. Why Does Replicability Matter?  Trust in Scientific Knowledge: The ability to replicate studies is crucial for building trust in scientific findings. If results can’t be replicated, it casts doubt on the validity of the original research and calls into question its contribution to the body of knowledge.  Policy and Practice: Many scientific findings influence policies, treatments, and practices, particularly in healthcare. If the research isn’t replicable, it can lead to ineffective or harmful decisions, such as adopting treatments that don’t work.  Scientific Progress: Science builds on previous knowledge. If that foundational knowledge is flawed due to irreproducible studies, it slows down or misdirects progress in understanding and applying science. 4. Efforts to Improve Replicability  Pre-Registration of Studies: Researchers are now encouraged to pre- register their study designs and hypotheses before conducting experiments to reduce p-hacking and selective reporting.  Open Data and Open Science: There is a growing movement toward open science, where researchers share their data, materials, and methods publicly so that others can better evaluate and replicate their work.  Replication Studies: More journals and researchers are promoting the importance of conducting and publishing replication studies, which test the reproducibility of previous findings. 7  Dr Simone Calabrich  Improved Research Practices: Encouraging better experimental design, larger sample sizes, and rigorous peer review can help ensure that scientific results are more reliable and replicable. The Scientific Approach A testable hypothesis is a specific, clear, and measurable statement that predicts the relationship between two or more variables and can be tested through empirical observation and experimentation. It must be framed in a way that it can be either supported or refuted through evidence. 1. Initial Observations:  The process starts with initial observations of a phenomenon. This could be anything noticed in the natural world or based on previous research, sparking curiosity. 2. Theory:  Based on these observations, scientists develop a theory—a broad explanation of how they think the phenomenon works, based on existing knowledge and evidence. Theories are general frameworks that guide understanding. 3. Hypothesis:  From the theory, a specific, testable hypothesis is generated. This is a prediction or a statement that can be tested through experiments or observations. The hypothesis is a focused way to test part of the theory. 4. Observations and Measurements:  Scientists then conduct experiments or make observations and measurements to test the hypothesis. This step gathers data to evaluate whether the hypothesis is supported or refuted. 8  Dr Simone Calabrich After testing, the results either support the theory or challenge it:  If the results support the hypothesis, it strengthens the theory and suggests it is likely to be correct, but further testing is still encouraged.  If the results challenge the hypothesis, it may lead scientists to revise or reject the theory, leading to new hypotheses and experiments. When scientists are described as critical and sceptical, it means they approach scientific inquiry with a mindset of careful evaluation and questioning. Here's what that entails: 1. Critical Thinking  Scientists use critical thinking to thoroughly evaluate data, evidence, and methodologies. They assess whether research is sound, whether conclusions are logically derived from the evidence, and if there are any flaws or biases in the process. This involves analysing assumptions, testing hypotheses, and considering alternative explanations. 2. Scepticism  Scepticism in science means that scientists question claims and results until they are supported by strong, replicable evidence. Scientists don’t accept conclusions at face value; they demand rigorous testing, replication, and peer review. Scepticism helps prevent the acceptance of weak claims. What makes a good theory? 1. Testability  A good theory must be testable. This means that it can be empirically evaluated through experiments or observations. A testable theory allows scientists to make predictions that can either be supported or refuted based on evidence. If a theory isn’t testable, it can’t be subjected to scientific scrutiny, making it impossible to confirm or disprove. 9  Dr Simone Calabrich 2. Predictive Power  A good theory should have predictive power, meaning it can predict novel events or outcomes that haven’t been directly observed yet. If the theory accurately predicts future events or experimental results, it strengthens the theory’s credibility. Predictive power is one of the strongest indicators that a theory correctly models reality. 3. Parsimony (Simplicity)  A good theory should be parsimonious, meaning it is as simple as possible while still explaining the phenomena. This is often referred to as Occam's Razor—the idea that, among competing hypotheses, the one with the fewest assumptions should be selected. A parsimonious theory avoids unnecessary complexity and convoluted explanations, making it more understandable and efficient without sacrificing accuracy. 4. Consistency  A good theory is internally consistent and doesn’t contradict itself. It should also be consistent with existing, well-established knowledge. If a theory contradicts verified scientific facts, it will likely need revision or may be invalidated. 5. Falsifiability  A theory must be falsifiable, meaning there must be a way to prove it wrong. If a theory can’t be disproven or isn’t open to being challenged by evidence, it’s not scientifically useful. Falsifiability allows for the theory to be tested against reality. Scientific knowledge is considered provisional because it is always subject to revision or refinement as new evidence, observations, or discoveries are made. 10  Dr Simone Calabrich This means that while scientific knowledge is based on the best available evidence at any given time, it is not considered final or absolute. Here’s why: 1. New Evidence Can Emerge  Science is a process of continuous discovery. As new technology, methods, or tools are developed, scientists can gather new data that may challenge or expand current understanding. 2. Theories Are Open to Testing and Falsification  Scientific theories and hypotheses are falsifiable, meaning they must be open to the possibility of being proven wrong. If new experiments or observations contradict an existing theory, scientists will revise or discard the old theory in favour of a more accurate one. This is part of the self-correcting nature of science. 3. Imperfect and Incomplete Knowledge  Science operates with the understanding that current knowledge is often incomplete. Scientists build on what is known, but as new discoveries are made, previous ideas may need to be updated. The use of the word “Prove” in science Using the word "prove" when writing about scientific findings is problematic because scientific knowledge is always provisional and open to revision. Here are the key reasons why "prove" is not typically used in scientific writing: 1. Science is Tentative and Evolving  Scientific knowledge is constantly updated as new evidence becomes available. Even well-established theories may be revised or refined over time. Using the word "prove" suggests that a conclusion is final and unchangeable, which is inconsistent with the evolving nature of scientific understanding. Instead, scientists prefer terms like "support" or "provide 11  Dr Simone Calabrich evidence for", which acknowledge that findings are based on the best available data but may be challenged in the future. 2. Falsifiability, Not Proof  In science, theories and hypotheses are considered falsifiable—they can be tested and potentially disproven, but they are never definitively proven. Even when evidence strongly supports a theory, there’s always the possibility that future discoveries could show exceptions or contradictions. 3. Probability and Uncertainty  Scientific findings are often based on statistical analysis and deal with probabilities rather than certainties. For instance, a study might find that a treatment is effective with a high probability, but it doesn't "prove" that the treatment will work for every individual in every scenario. Using "prove" oversimplifies the inherent uncertainty and nuance in scientific research. 4. Multiple Interpretations  Scientific experiments may yield results that support a particular hypothesis, but those results can sometimes be interpreted in different ways. Claiming that a study "proves" something ignores the possibility of alternative explanations or future evidence that could modify the interpretation. 5. Bias Toward Finality  Saying that something is "proven" can unintentionally create a bias toward viewing scientific conclusions as absolute truths. Science thrives on openness to challenge, and using less definitive language encourages further inquiry and critical thinking. 12