Psychology 104 Cont. 1 PDF

Topic 1: History Revised notes: Slides 1-20 Psychology in a nutshell Originates from the words “Psykhe” and “logia” which directly translates to “Study of the soul/spirit”. - Invokes, “how do we scientifically study an intangible thing as the soul if we cannot p...

Topic 1: History Revised notes: Slides 1-20 Psychology in a nutshell Originates from the words “Psykhe” and “logia” which directly translates to “Study of the soul/spirit”. - Invokes, “how do we scientifically study an intangible thing as the soul if we cannot prove its existence?” → “Psychology” couldn’t exist without the soul Modernly described as the study of the mind and behavior - Invokes, “what is a mind?” and most importantly, “is a mind a spirit//soul?” What is a “mind?” The thoughts and feelings one experiences that outsiders cannot observe - Internal states and processings (as listed above) that can only be inferred through observable, measurable responses - “Goals of Psychology” contradict this definition given that they only target behavior Hippocrates (460 BCE) Starting point for “Scientific medicine” Theory of Humorism → concentration of four fluids that flow throughout the body determine a person’s health - Greek worldview was composed of the four elements → their love for consistency they developed four “humors” to correspond - (BBE, BW, YBF, PWA) → if these were imbalanced, ailment occurred Galen (129 CE) Roman physician that “perfected” theory of Hippocrates Each person has a unique composition of the four humors to form “temperaments” - Each person falls into another category of four (Melancholic, Sanguine *Cheerful, Choleric, Phlegmatic) → Almost like MBTI and zodiac theory! Recall: Greek love for consistency due to the logical order it established. Humor theory allowed them to understand human biology and psychology. - Humors became everything → each corresponded to organs, seasons, planets, etc. Consistency and connection!!! For the body to be in prime condition, humors must be in correct proportions; an imbalance was to blame for moods, illnesses, etc. Everything about a person (including personality and behavior) could be linked back to this theory. Bloodletting was thought to restore humor balance. (removal of blood to manage diseases) Rene Descartes (1586) Philosopher and mathematician who argued substance dualism Minds and bodies (brains) are distinct and radically different. They do not require each other but can cooperate. - Mind lacks physical substance (is immaterial); has property that it thinks - The body is spatially extendable; can exist in and take up space. - Creates a contrast between physical and mentallistic reality. - Things that are objective, observable by all vs. things that cannot be measured or observed by someone other than who experiences them. - ie.) A toothache can be inferred from physical, observable clues, yet the subjective reality (ie. pain) only exists to person experiencing situation Substance dualism created the “Mind Body Problem” → how does something immaterial affect something material and vice versa. Rene’s views were heavily influenced by religion - Attempted to prove them by using the existence of God (Argument for God that could not be doubted) - For thoughts to exist, there must be “something doing the thinking.”; you cannot doubt your own existence, doing so proves you exist. - “I think, therefore I am.” He gained popularity due to his views corresponding to Christian worldviews Emergence of The Study of Psychology Late 1800s psychology became distinct as its own study, partly due to events like the Renaissance As scientific advances arose, more scientifically minded people tried to explore and apply own methods towards the “mind” Steven Blankaart → Dutch physician, chemist, etc. in 1694 → “Physical Dictionary” - Anatomy describes body, psychology describes soul Wilhem Wundt → German professor; established the first psychology lab in 1879. He was the first to “separate psychology from philosophy and physiology”. - Psychology should be modeled after other scientific disciplines (ie. chemistry and physics) in order to study the conscious experience - Used introspection → Person reflects and reports their personal experiences - Wanted to collect as much reliable data as he could by using harsh strange methods; ie.) measured length and concealment of sensations by sticking tube with hot water down throat - Lab assistants had to comply with extensive training Psychology’s Expansion and Different Approaches Wundt’s establishment invoked an increase in the study of psychology around North America; lack of agreed upon frameworks and theories created Structuralists and Functionalists  S : Study mind as a physicist, using introspection and the breaking down of consciousness into its elements (five senses) the relationship between them would then be studied. F : What is the function of consciousness? - Introduced by William James → Inspired by Darwin’s natural selection - A person’s traits must serve a purpose for survival → if we have evolved with consciousness, what is its purpose? - Consciousness is continuous → a “stream” - Emphasis on the purpose of this “stream” gave them a more practical approach and allowed for new avenues of study Sigmund Freud (1856) Physician studying eel reproduction → Medical doctor without pHD → psychiatrist not psychologist Psychoanalytics and psychoanalysis → present is shaped by past Mental disorders are psychological in nature → due to unconscious factors of behavior Unconscious: thoughts, feelings and desires that are not subjectively perceivable; yet they affect one’s behavior - Could not even be observed with introspection - Freudian slip → misspeaking can reveal suppressed desires - Repression → pushing unwanted thoughts out of conscious awareness Theories are unfalsifiable (not good science) and heavily criticized due to his lack of experimentation and scientific study; Freud’s theories were based on his own experiences and conversations with patients - He still gained popularity due to his strength in literature and english (compelling, seemingly consistent and charismatic writing) Occam’s Razor William of Occam (1285) Also referred to as Law of Economy, Principle of Parsimony - Not developed by him but heavily advocated for by him If you can’t choose which theory to believe and they are explained equally well → choose the most parsimonious one → which one makes the least new assumptions? (Each new assumption is another chance to be wrong) Parsimonious and simple are not the same thing “Razor” refers to shaving off unnecessary assumptions Revised notes: Slides 20- end Humans vs. Animals During the early 20th century, people did not like ascribing mental characteristics to (nonhuman) animals → comparing animals to humans on a mental scale While physical and structural similarities are widely accepted, humans resist the idea that there could be a mental/psychological connection - This is due to the belief that humans are “special” or “superior” due to our capacity to think, as well as our mental/conscious processes Raises the question… “Is the human capacity to reason and/or its mental processes really that special?” These mental processes may just be a byproduct of being a behaving organism that has evolved. (Therefore can’t be the cause of our behaviors) John B Watson Psychologist during the 20th century → like Freud, began studies centered around nonhuman animals Did not believe in introspection, thought the works of those like Wundt were “guesswork” → why he used animals (cannot rely on them for subjective assessment) - Mental inference is not good science (needs to be verifiable) - Even if a subject gives true info during introspection, there is no way to verify it other than faith→ can’t assume this is what causes our behavior - For psych to be a real science, researchers must switch to studying behavior rather than the “mind” or “spirit” → behavior is observable and measurable Tongue and cheek → Watson’s argument that environment partly determines behavior - Since eugenics was still thought to be valid, many did not believe him Behaviorism (behaviorists) Theoretical orientation (belief) that scientific psychology must study behavior - Behaviorists argue against eugenics → rather place emphasis on an organism’s environment - Also philosophy of science → the reason why a science of behavior is valuable  Many types of behaviorism separated by philosophical and theoretical differences; united by the fact that a science of behavior is possible for its own sake - Usually blanketed by “Methodological” → advocated by Watson; popular due to Pavlov → “conditioned reflexes” (dealing with stimulus and response) *Response/reflex must be a measurable change in behavior* Successful due to animal research - Experiments become more successful the more control you have over all aspects (easier done with animals due to it being frowned upon with humans) Codominant with psychoanalysis in the 1950s - Due to psychoanalysis’ focus on strange unconscious repression and behaviorisim’s focus on evolved genetic learning history controlled by our environment…people began to dislike these frameworks. - Both felt deterministic and dehumanizing → implies humans don’t have free will B.F Skinner Found inspiration and issues in ideas from Watson, Pavlov, etc. - Learned behavior cannot be the product of pavlovian responses alone Experimental analysis of behavior rather than psychological research Had massive impact on study of behavior - Operant conditioning → rewards and punishment modify behavior Pragmatist → Didn’t deny existence of minds, didn’t see point of studying them Competing perspectives (in reference to Behavioristic) Humanistic - Anti-behaviorism and psychoanalysis - Pioneered by Carl Rogers and Abraham Maslow - Theoretical orientation that humans are more than the sum of their parts → able to self actualize (capacity to experience personal growth, and the desire to find meaning in existence) - Conscious motives, choice, freedom, individuality, improvement, potential - Even if behaviorism is true, people can only live through a subjective experience Cognitive - 1970s anti-behaviorism due to its rejection of the mind (contrasted completely with substance duality) - Renewed interest in the mind and consciousness (is it linked to behavior?) - Behaviorism wielded results → people used it to make comments about consciousness aka infer the unobservable using the observable  - Cognitivists were afraid of appearing pejorative, so used technical terms like cognition - Theoretical orientation that humans are information processors (mind is a computers software, brain is computers heart) Biological (neuro) - How our brain and bodily functions regulate our behavior - Part of psych since its conception (why it was first produced in medical dictionary) - Physiological processes that occur in body and brain influence your behavior recall: humorism - Viewed more as a branch of biology ie.) do brain regions have different functions Modern Psychology Move away from more nuanced philosophical perspectives on how psych should be conducted, emphasis on areas of interest Sociocultural → how cultural and social aspects of environment influence behavior - First noted focus on cultural variables - Bias within samples (usually researching a common demographic so cannot be applied to general public) - Consequences and causes Applied → (clinical) diagnosis and treatment for illnesses and disorders - Emerged from WWII for assessment and screenings, as well as PTSD Psychometrics → tests that assess a person’s psych (iq, personality, disorders) Developmental → focuses on human development across lifespan (specifically children) Topic 2: Science and Measurement Revised notes: Slides 1-8 The Problem With “Common Sense” We believe our “common sense” can have no flaws → this is not the case ie.) you can believe two contradictory things at once (opposites attract and birds of a feather flock together) - This behavior does not support the idea that humans are logical creatures Naive realism → the believe that each of us sees the world for what it really is  - We all believe that our perception of the world is the “right one” - This means that our intuition can be useful (ie. cross street to avoid traffic) but is not always accurate (ie. Earth appears flat) - Common sense is a starting point for answering questions about reality, but it must be verified The Scientific Method The way humans validate and test theories/opinions Comes from Latin word “scientia” → to gain knowledge 1. Identify a question 2. Gather relevant information and form testable hypothesis Some hypotheses are untestable (unfalsifiable) if they cannot be disproved, that means there is no way to know if the hypothesis is accurate 3. Design a test for the hypothesis 4. Analyze data and draw conclusions 5. Report findings and ask further questions Ignaz Semmelweis (Hospital Experiment) Hungary physician worked at a hospital in Vienna He noticed a disparity in the mortality rate of the women in his maternity ward and the second ward worked by midwives - Many women succumbed to childbed fever (feverish symptoms that lead to death) - Fever was thought to be caused by miasma (air particles) - Women who gave birth in the streets also had a lower mortality rate 1. Constructed a question - What is the cause for the discrepancy in the mortality rate? 2. Formed testable hypotheses - Semmelweis formed many hypotheses at first - Is it due to the path of the priest while making sacraments? Is it due to women laying on their backs during delivery? - When his friend Jacob Kolecha was accidentally cut by a scalpel used for childbirth he died, showing similar pathology to the deceased women. This reminded Semmelweis that his ward performed autopsies in the morning and delivered babies at night without washing their hands or tools. - Does handwashing have an effect on the mortality rate? 3. Designed a test for hypothesis - Had doctors wash hands and tools in a Cl solution before deliveries 4. Analyze data and come to conclusions - The mortality rate went down significantly, lack of hand washing is the cause for discrepancy between the two wards. 5. Report findings and ask further questions  - Unfortunately medical establishments did not like his findings and fired him Revised notes: Slides 8-42 Deduction and Induction Deductive statement→ statement in which the conclusion must follow its premises - Used in logic and math to create theorems - If the premises of an argument are true, so is the conclusion - ie.) If Socrates is a man and all men are mortal, Socrates must be mortal *This is known as being deductively valid* Inductive argument → a statement in which the conclusion is improbable (unlikely) to be false if its premises are true - Depends on probabilistic reasoning, is what science relies on - Since this follows rules of probability, it is impossible to be 100% sure of a conclusion since the universe is always changing we must collect evidence and make assumptions based off of it - ie.) All swans ever observed have been white, so all swans are white *While this conclusion is likely, it is deductively invalid* Falsifiability and Truth In science, there is no such thing as proving a positive claim, unlike in math. - Evidence can support (corroborate) a claim but it cannot prove it - Rather on focusing on proving something “true” we must look to prove something as “false” ie.) finding one black swan will prove the statement “all swans are white” is false Falsifiable → (a hypothesis) that is possible to be proved false through an experimental circumstance. This means your hypothesis can never be subjective. - Many theoretical perspectives are criticized for being unfalsifiable because they cannot be measured or explained - If a theory accounts for everything, it can never be proven false ie.) psychoanalytic statements such as childhood trauma being a link for everything - ie.) “aliens don’t exist” is falsifiable → all we need to do is find an alien - ie.) “Steven Walter is an alpha” is not falsifiable → there is no way to prove or disprove this because it is subjective - Tested by induction and deduction Hypotheses, Theories, Laws, and Facts Facts → objective observations ie.) it is sunny outside - These lead to developing possible explanations… AKA Hypotheses → something to be tested for falsifiability ie.) if it is sunny, the sun must be out so let’s go outside to check - Usually multiple of these are made; we find the “correct” one by eliminating the wrong ones - Finding the right hypothesis leads to a… Theory → the way we know something works based on our tested hypothesis and the evidence we have already gathered *The Gold Star Idea* - Used to give explanations, and predict how things are. Once we know… Law → A detailed description to explain how something works - This description explains how things are and predicts how they will be in the future Remember: Farnood Had To Leave :( Variables In Experimentation Variable → anything that can take on a different value - Placeholders in math (can occupy multiple values ie.) x-intercepts) - Can also occupy multiple values in experiments ie.) amount of saliva produced, hands washed or unwashed - Experiments must have fixed independent and dependent variables to ensure what exactly we are testing - Dependent → variable we are investigating the outcome of - Independent → (manipulated) this variable causes results Karl Pearson and Alice Lee - Collected variety of measurements to see if there was a statistical relationship between parents and children (children 18+) - Measured height, arm span, and left forearm to check inheritance of physical characteristics - Collected over 700 different responses… tedious to measure so how do we do it? Measuring Variables (The Operational Definition) Variables should be described in quantitative terms Operational Definition → description of a variable in terms of the operations used to measure it - Cannot be ambiguous - Should create criteria that will classify when an event of interest occurs by being 1. Precise 2. Practical 3. Quantitative  4. Interobserver reliability (degree of agreement between different observers) ✅ ie.) number of milligrams of saliva absorbed by cotton ball (size x) placed in cheek for specific ❌ area of time good definition ie.) how many times a rat turns a corner bad definition (what counts as “turning a corner”?) Measuring Variable Distribution (STAT) To describe variables in quantitative terms, we use stat methods Probability distribution → math equation that describes the probability of obtaining given variable values Central tendency → a value that best represents an entire distribution - Mode Provides exact values Works well with nominal frequencies Lowest sampling stability - Median Withstands outliers Not good with common stat methods Medium sampling stability - Mean Affected by outliers Good with common stat methods Should not be used for likert scales (opinions, attitudes) Value might not exist in real life ie.) what is the “average” person? Does not provide exact values - *Sampling stability starts lowest in the mode We visualize data using a number of tools - Histograms - Density plots ( essentially the filled curve of a histogram) Data Spread (Variability) Must be considered to make good predictions - ie.) the mean is not a good representation of people on its own When looking at a set of data, we are less concerned with the numbers themselves, more so the relationships between the values and the processes occuring Deviation to mean → distance between data points and the mean - Calculated by subtracting the mean from all variable values - Since the mean is the theoretical data center, you will get a value of zero due to positive and negative halves canceling out Revised notes: Slides 42-end Standard Deviation and Variance Standard deviation → average measure of how far data observations are from the mean - Used during normal distribution - - The formula above can only be used for populations (greek letters), rather than samples (latin letters) *Population SD can usually not be calculated - To change this → Replace “N” with “N-1” → subtracting a degree of freedom - Note that all greek symbols become replaced by latin ones Recall: extreme values are found at the ends → on a normal distribution (bell curve) which is why they have a low probability of being selected at random - 95% of all data falls within 2SDs above or below the mean *Note: The probability of selecting a value exactly equal to the mean (or any other exact value) is always zero. - This is due to continuous distribution → there are an infinite number of possible values (the probability is there, but so small it becomes negligible) - Variance → value describing how much data observations vary from the mean (square difference) Normal Distribution and Probability Also known as the bell curve Demonstrates the probability of different data values Infinite in both positive and negative directions (continuous) - Must discuss data in intervals and range rather than at a specific point Different graphs and their appropriate measures Bell curve (normal) → only the mean and stand deviation are required to find central tendency and spread, respectively - This is due to the unimodality and symmetricity Skewed and multimodal → the median and IQR are best for calculating central tendency and spread, due to presence of extreme values - *Note: in order to determine if data is skewed, we must plot it with a histogram or density plot → do not make assumptions Topic 3: Research Methods Revised notes: Slides 1-10 The Importance of Choosing the Right Method Objective evaluation began to grow important in the 40s-50s when leukotomies (lobotomies) were popular - Lobotomy: the severing of frontal lobe connective tissues - Created by Egaz Moniz, who claimed it could treat disorders such as mental illness or epilepsy - Success of this was based on anecdotes of doctors → no proper research or experiment, success was solely based on personal observations of it “working” - Procedure later proved to be ineffective in curing disorders, rather rendering patients in a vegetative state Anecdotes Personal experiences disguised as “evidence” Can include contradictions, bias, inaccuracies - Does not allow for cause and effect inferences Make causal claims without consideration for lurking variables  ie.) an intense diet program portrayed on social media Can portray survival bias (not able to apply results to whole general public) Research Methods Observational 1. Descriptive - Describes aspects of a phenomenon through surveys, case studies, etc. - The goal is to witness these phenomenon as accurately as they occur in reality, so we do not interfere Naturalistic - A fly on the wall approach ie.) Jane Goodall studying warfare of chimpanzees - Observing individuals in a real world setting to predict possible causes - High external validity → extent to which findings can be applied to the real world - Can produce reactivity/hawthorne/watcher effect *should subside eventually Case Studies - Examining one (or a few) individuals closely over time - WEAKEST for external validity and generalization (internal) - Pioneered by Phineas Gage - Examines what cannot be ethically or easily examined in a lab - Reliance on indirect assessments (interviews and recollections). Subjectivity can create bias and inaccuracy *researchers may unintentionally focus on what fits their own expectations - Good for existence “proofs” (demonstrating that a phenomenon can occur) *is not actually proof due to no manipulation of variables Surveys - Questionnaires and interviews centered around participant background, experience, demographic, etc. PROS: - Easy to obtain large amounts of data for relatively little effort (many factors can be measured at once) - Not limited in how they can be created - Can produce hypotheses about a phenomenon CONS: - Assumes participants understand all questions (no misrepresentation or miscommunication) - Assumes no response bias (through memory gaps, positive impression management and malingering) 1. Correlational  - Assesses the extent to which two variables are related through descriptive research methods - Stat methods are utilized for making generalizations about observations about the relationship being studied *ie.) Karl Pearson’s investigation of relationship between parent and child height Scatter plots → a graph involving many dots which represents a set of paired x and y variables - X = provides a prediction for a phenomenon - Y = the phenomenon being predicted - Plots vary from a shapeless blob (0 correlation) to a straight line (perfect correlation) - Outliers will always be present with the exception of perfect correlation *Space and inconsistency between data points is statistical noise Correlation Coefficient (Created by Pearson) - A value falling between the interval of -1 and 1 - The closer you get to either exact value, the stronger the relationship - Positive: As X increases, so does Y (identical) - Negative: As X decreases, Y increases (opposite) *In a scenario where there is 0 correlation, use the mean to predict data Issues with Correlation - Illusory → Perceiving a relationship to exist when it does not - Confirmation Bias → Looking at results with a tendency to look for evidence that supports your hypothesis, or ignore evidence that denies it - Availability Heuristic → easiest accessible information from memory is the information most likely to be believed, even if you are dubious about a phenomenon *Humans are not good at remembering things that don’t happen ie.) remembering all the times a crime occurs, failing to recognize all the times it does not Correlation is NOT Causation! - Only examining relationship correlation (X and Y) will provide predictions - Must consider Third Variable Problem which suggests that the relationship between X and Y may be due to lurking variables - Experimental - Opposed to observational research, we manipulate variables of a phenomenon - We are able to use our observations to isolate causes of events or trends (however one prediction is not automatically the answer) - “Gold standard” of research methods To make causal inference, we must have clear manipulated variables, ensuring all other variables are kept consistent - ie.) An experimental group will receive variable X while the control group will not. If all other aspects of these situations are kept the same, we can attribute the differences in results to the presence of variable X. Hazards - No random assignment - Demand characteristics *Subjects pick up cues that generate specific results → experiment often disguised to avoid this ie.) Clever Hans: A horse believed to be capable of solving mathematical problems by owner Von Austin. Oscar Funks revealed that rather than solving the problem, Hans was responding to subtle physical cues by Von Austin to generate results. When Hans could not see Von Austin, he could not solve math. - Experimenter expectancy *researcher hypothesis can lead to biased interpretation of study → double binding is used to avoid this - Lack of binding *Subjects must be unaware of what group they are assigned - Confounding variables *A variable not properly controlled can lead to different results Revised notes: Slides 10-end Evaluating & Assessing Data Reliability → consistency within measurement - Test-retest *Administering a test should produce similar results each time, in other words you should be able to replicate the results *ie.) a ruler that measures a different length for the same object each time is not useful and essentially says nothing about the object’s length - Interobserver *Interpretations of results should not differ based on clinic  *Two or more people conducting the same experiment should arrive at the same conclusion *Interrater reliability *Note: Rorschach tests have poor reliability for both Validity → experiment should assess what it claims to ie.) If a questionnaire for depression actually measures anxiety, it has low validity - Polygraph machines (lie detectors) *measure physiological body responses rather than actual lies → not 100% valid *Bad for criminal investigations due to high false negatives and false positives Why Does Data Fluctuate? It is impossible to control 100% of all aspects within an experiment. - ie.) Humans in an experiment are never guaranteed to have the same genetic, nutritional, learning history - All uncontrolled variables can influence results and produce errors (unsystematic variation) - It is difficult (and unethical) to maintain high control over human subjects → the reason why animals are primarily used in experimentation Evaluating Results Recall that means are useless without understanding surrounding variation When viewing overlap within histograms, ask: could these results be chance, is there test-retest reliability? - If the results are accurate → is the difference large enough to be meaningful? - ie.) The Canadian quarter is not exactly the same size and weight on both sides, yet we still consider landing on heads a 50% chance → difference is negligible Error bars → provide a sense of variability around mean - Confidence interval: where the true population mean is likely to be within a 95% chance (population inference) - Lack of overlap (large distance) between intervals supports the idea that difference observed is true - Also displays IQR, SD, Range, etc. → read figure caption to be sure of what is being demonstrated Statistical significance - Occurs when p < 0.05 *P = the probability of obtaining a result, assuming hypothesis is true and stat assumptions are satisfied - Just because this occurs, the study does not automatically become significant in a meaningful way; a large enough sample size will always result in p < 0.05 *Consider effect sizes *Should not be used to measure merits (worth) of a study Topic 4: Research Ethics Revised notes Why are research ethics important? The wellbeing of subjects becomes more impactful when dealing with animals rather than rocks or plants - ie.) Studying brain damage in the most effective way would be administering controlled levels of brain damage to randomly selected subjects → seen as unethical in terms of humans, more acceptable when using rats Forms the question… What lives take precedence? What makes a rat less important than a human? What determines the value of a life? Why do we care about any of this? Some experiments in the past have been insanely unethical - Little Albert - Monster (Stutter) Study - Milgram Experiment - Bystander effect - Stanford Prison - Aubery Levin Homosexuality - Harry Harlow’s Monkeys Research Ethics Board (REB) A committee of officials of different backgrounds responsible for protecting the welfare of human subjects Determines if an experiment is in accordance with the tri-council policy statement - Ethical conduct for human research - Joint council of three federal research agencies Required screening by REB anytime we experiment on humans → REB will make provisional edits to anything unethical Weighs the risks and benefits to participants in an experiment and ensure subjects are not exposed to (or are offered ways to deal with) significant distress ie.) Physical or psychological harm, personal info leaks How do we ensure participant welfare? Informed Consent - Participants must be aware of all tasks, risks, purposes, etc. of what they are consenting to in the experiment - No coercion *Some experiments involve methodologically hiding the true nature of the study from participants (binding). This is known as deception*  Deception - Hiding the nature of a study to maintain its integrity ie.) Placebo Tests - Must only be used short term - Requires a debrief after the study has concluded - Participants can choose to withdraw their data Anonymity Confidentiality Animals vs. Humans Lots of animal research has led to great discoveries for human treatments - Autism - Mental disorders/illnesses - Dyslexia - Brain damage Animal research has also led to great developments for animals! - Veterinary care - Wildlife habitats - Quality of life in zoos Animal research helps define the differences and similarities between humans and other species, which can help with evolutionary theories But why? Conducting research without the use of living organisms can only get us so far. Using other species that share similar organs, behaviors, etc. serve as good models. Animals provide greater experimental control ie.) We can use breeding, controlled learning, etc. to decrease genetic variation Animals are practical and reliable ie.) Animals will not show up late or flake on your experiment! They are friendly, hard workers. While humans require monetary payment, you can easily source a piece of cheese for a rat! Apply procedures that may be deemed unethical for humans The Nuremberg Code Ethical principles established for human research Animal research should form foundation for any invasive or potentially harmful research Results should justify the performance of an experiment Protecting The Animals Canadian Council on Animal Care (CCAC) functions as the animal version of REB Provides a checklist of requirements that must be met for research to be done!  Replacement → can we avoid/replace the use of animals? Reduction → can we limit the number of animals being tested on? Refinement → modifications must be made to experiments to minimize significant distress!