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1
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Structuralism

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was founded on the notion that the task of psychology is to analyze consciousness and break it down into its basic elements or pieces, while investigating how these elements are related.
Structuralists wanted to identify and examine the fundamental components of conscious experience, such as sensations, feelings and mental images.
To examine these components, the structuralists depended on introspection, the careful, systematic self-observation and recall of one’s own conscious experience.
The creation of this school of thought, as well as the use of introspection, is attributed to Wundt’s student, Edward Titchener.

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2
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Gestalt Psychology

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Emerging from Berlin, Germany in the early 20th century, Gestalt Psychology studies the whole or entirety of consciousness, which includes the component parts of perception, sensation, learning,& problem-solving. Think of Gestalt Psychology like a puzzle that is viewed as its completed work, and not broken down into its separate pieces. Consciousness is the completed puzzle, made up of perception, sensation, learning and problem-solving. With Gestalt, we look at the entire picture, to help understand how we perceive and make sense of the world around us. Integrate the pieces into a meaningful whole! This was a rejection of Wundt and Titchener’s structuralist psychology.

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3
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functionalism

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was based on the belief that psychology should investigate the function or purpose of consciousness, rather than its structure.

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4
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Sigmund Freud & The Psychodynamic Perspective of Psychology

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The Psychodynamic perspective of psychology focuses on our unconscious thoughts (we are not aware of them, nor can we willfully recall anything related to them) and the impact of childhood experiences in shaping our future, emotional responses to the world around us and our adult personalities. Free association, a method of exploring the unconscious, is employed by having the patient relax and freely say whatever comes to mind after being prompted. No matter how trivial or embarrassing in nature one’s thoughts may be, the psychodynamic practitioner looks for patterns of thought to help the patient gain insight into what is troubling them or interfering with their daily lives. Sigmund Freud, a Viennese physician who practiced in the late 19th to mid 20th centuries, is the founder of this perspective of psychological thought.

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5
Q

Psychology

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which can be defined as the scientific study of individual human behavior and mental processes, can trace its origins back to early philosophers (“lovers of wisdom”) such as Plato, Rene Descartes, and John Locke. These philosophers, as well as countless others before and after them, were curious about what made humans behave and think the way they did (and still do!!!). How one learns, processes and recalls information were also points of wonder for these people who predate formal psychology as we know it today.
Early physiologists (study the functions and systems of living creatures) and doctors took interest in these topics as well.

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6
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Introspection Vs. Free Association

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Structuralist Introspection
Participants would carefully observe their own conscious experiences, reporting sensations, feelings, and thoughts in response to stimuli. The goal was to identify the basic elements of consciousness and how they combined to form complex experiences.
It emphasized precision and control, often taking place in highly structured laboratory settings. Researchers aimed for detailed, objective descriptions of immediate conscious experience.

Freudian Free Association
Patients were encouraged to speak freely and say whatever came to mind without censorship or filtering, allowing their unconscious thoughts and feelings to emerge spontaneously. It was an open-ended process, allowing for exploration of the psyche without constraints.
This method focused on uncovering latent, often unconscious material. Freud believed that unconscious conflicts and desires significantly influenced behavior, so free association was used to explore underlying psychological issues.

Key Differences
Structuralist introspection aimed to dissect the conscious mind, while Freudian free association sought to uncover unconscious thoughts.

Introspection was controlled and structured, focusing on immediate conscious experience, whereas free association was unstructured, emphasizing free-flowing, uncensored thought to access deeper, unconscious material.

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7
Q

Additional Psychological Perspectives

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Behavioral
Humanistic
Cognitive
Biological / Neuroscience
Evolutionary
Sociocultural
Biopsychosocial

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8
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Behavioral Perspective

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The behaviorists rejected unobservable traits or characteristics (unconscious mind and consciousness)to determine how we are shaped, mentally and behaviorally. The focus of behaviorists is on our environment and how it teaches and molds us.
Behaviorism looks at objective, observable behaviors in order to determine how we learn and navigate the world around us.
A system of rewards and punishments is used to encourage desirable behaviors, while discouraging undesirable ones (Operant Conditioning).
Key figures include John B. Watson (Considered the founder of Behaviorism), Ivan Pavlov, BF Skinner

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9
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Humanistic Perspective

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The Humanistic perspective arose from the belief that both the psychodynamic and behavioral lenses of viewing psychology were too myopic (limited) in nature. There is more to behavior than the influences of childhood and the altering of behaviors through reward and punishment, as well as conditioning.
The Humanistic perspective views human beings as being free, rational creatures with the potential for personal growth and psychological maximization. Humans are set apart from the remainder of the animal kingdom in that we are consciously aware of our potential for personal growth and our abilities to rise above our personal situations.
Human nature is positive and we possess free will. It is a perspective of optimism.
Abraham Maslow and Carl Rogers are central figures of the Humanistic perspective.
Key terms include free will and self actualization.
Maslow created a “Hierarchy of Needs”, which was his blueprint for achieving “Self Actualization”, or satisfaction / fulfillment with one’s self.

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10
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The Cognitive Perspective

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The Cognitive perspective seeks to understand human behavior by examining how we encode, process (make sense out of), store and retrieve information.
Focus is on conscious thought.
Cognition refers to the mental processes involved in acquiring knowledge.
Proponents of the Cognitive perspective point out that the ways people think about events has an influence on behavior.
How do our thoughts affect the ways we interpret different situations?
Jean Piaget, Noam Chomsky, and Herbert Simon are key figures.

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11
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Biological / Neuroscience Approach

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This perspective places its emphasis on the brain and genetics, as well as how the body is affected by mental and emotional states.
How does our biological state affect our social state? (Epigenetics is the study of how the environment and other factors can change the way that genes are expressed.)
How does stress affect our immune system?
Important words and terms include genes, brain, nervous system, hormones, neurons and neurotransmitters.
Heavy emphasis on using medication for treating symptoms.

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12
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Evolutionary Perspective

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The evolutionary perspective is driven by the belief that natural selection and adaptation has given humans specific behavioral traits that will improve the likelihood of survival.
If certain behaviors had a highly negative impact on our ancestors’ chances of survival, they disappeared or were viewed as maladaptive
Those behaviors that significantly increased the likelihood of survival flourished and continue on with us today.
Charles Darwin and his theory of evolution and natural selection is the foundation of this theoretical belief.

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13
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Social-Cultural Perspective

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the Sociocultural Perspective looks at how social interactions and culture influence behavior and thoughts. How, possibly, does behavior and thinking vary across situations and people / populations?
(Culture can be defined as the customs, arts, social institutions, and achievements of a particular nation, people, or other social group.)
Key terms and words include norms, gender, race, ethnicity and socioeconomic class.
How does poverty influence health and mental illness?

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14
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Biopsychosocial Approach

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This is an integrated viewpoint which considers the Biological, Psychological, and Social-Cultural factors that make up the behavioral and mental processes of individuals.
As humans are made-up of complex systems, this integrated, multi-level approach intends to offer a more comprehensive understanding of any particular behavioral or mental process.

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15
Q

Critical thinking
scientific approach

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is the type of thinking that does not automatically accept arguments and conclusions at face value, but rather examines assumptions and appraises (evaluates and analyzes) )the sources of information. Critical thinking, and critical thinkers, also look for hidden biases while evaluating the evidence and conclusions presented in a research study or experiment.

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16
Q

Peer Review
scientific approach

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is also a major component of the scientific approach and critical thinking. Peer review takes place when an expert or group of experts evaluate a research article’s theoretical conclusions, originality, and accuracy.
If the peer review process determines that something is suspect or incorrect, the experts will see if the theory or conclusions presented in a paper can be disproven by observation or experimentation. Are the original findings falsifiable, or capable of being disproved?

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17
Q

Cognitive biases

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are illogical thoughts or errors in thinking, which are often the result of heuristics.

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18
Q

Heuristics

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are mental shortcuts that the brain uses to quickly process information.

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19
Q

Hindsight bias

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(also known as the I knew it all along phenomenon) is the tendency for one to believe after learning an outcome that they would have been able to predict it from the outset. I knew that was going to happen!

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20
Q

overconfidence

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is simply the human tendency to think we know more than we actually do and/or to overestimate our abilities to complete a task or challenge.

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21
Q

illusory correlation

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is the phenomenon of perceiving a relationship between two variables (typically people, events, or behaviors) even when no such relationship exists.
“Every time the New York Rangers play the Edmonton Oilers, they blow a lead and lose the game.”
“Someone always gets trampled to death in a stampede at Walmart on Black Friday.”

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22
Q

Authority bias

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is defined as the tendency to attribute greater accuracy, credibility, or value to the opinions, suggestions, or decisions of an authority figure, simply because of their position or status.
The tendency for people to fall victim to authority bias is why we often see people that are well known or in positions of power an authority advertising products or serving as spokespeople for groups and organizations.
One historical example of this bias was the Tuskegee Syphilis Study. From 1932-1972 the U.S. Public Health Service conducted a study on black men in Tuskegee, Alabama, to observe the effects of untreated syphilis. Although penicillin was already established as a cure and readily available to treat these men, the researchers withheld treatment. Authority bias played a role in allowing this unethical study to continue for decades, because many people believed–falsely–that the medical community would not allow such harm to take place.

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23
Q

Hypothesis

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an assumption that is created or stated before research has been conducted. A testable prediction.

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24
Q

Theory

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supported by data from research that has been completed and explains a question, thought, or phenomena, and helps predict future behaviors or events.

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Operational Definition
a statement or description of the exact procedures (operations) used to identify research variables in a study and detail how they will be measured. An operational definition is necessary for replication of the study and for testing the results of a study. Variables must be identified / defined in the operational definition. This is done to check for accuracy / validity and replication
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Experiment
a research method in which an investigator manipulates one or more factors (independent variable) to see what effect, if any, it has on behaviors or mental processes (dependent variable). The participants of an experiment are randomly assigned to either the experimental group or the control group. This is the only research method intended to show cause and effect.
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Random Assignment
is the process of placing participants in an experimental study to different groups (experimental group or the control group) using a method that ensures every participant has an equal chance of being placed in any of the groups.
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Independent Variable
The IV is the variable that is manipulated or intentionally altered in an experiment. It is often referred to as The Cause.
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Dependent Variable
the DV is the variable that potentially changes as a result of the IV. It is often referred to as The Effect. Using one’s smartphone (IV) within 45 minutes of going to bed will increase the time it takes (DV) for a person to fall asleep.
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Confounding Variable
A CV is an unintended / unintentional variable that can have an affect on the experiment and skew the results. A participant in the smartphone-sleep study took in caffeine just prior to the study.
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Double-blind Procedure
A type of clinical trial in which neither the participants nor the researcher knows which treatment or intervention participants are receiving until the clinical trial is over. This makes results of the study less likely to be biased.
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Control Group
these are the participants in an experiment who are not exposed to the treatment.
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Experimental Group
these are the participants in an experiment who receive the treatment, or a version of the independent variable.
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Placebo
an inactive substance given to participants in an experiment. Commonly used in experiments with pharmaceuticals. Participants are led to believe that the placebo is in fact the actual substance or treatment.
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Placebo effect
experimental results or effects that are due to expectations, alone, and not an active ingredient or treatment. The power of believing something will work causes it to work.
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Population
all of the participants in a study. (All of the students who responded to the ChatGPT survey)
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Sample
a group of participants selected from the population, which will be used to represent the entire population. This is often done as a time-saving measure, or when the total number of participants is so large that entire population would not be manageable.Often used with surveys and questionnaires, like public opinion polls. {For populations under 1,000 ppl., 30 % of the population is considered representative (1,000 people in population; 300 randomly sampled). For larger populations, such as 10,000 ppl., 10% is considered representative of the larger population (10,000 people in the population; 1,000 randomly sampled)}
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Random Sample
each individual in a population has an equal chance of being chosen for the study. (The even numbered respondents from each grade-level were selected)
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Stratified Sampling
the population is divided into different subcategories and a random sample is taken from each subcategory. (Grade-level in the ChatGPT survey)
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Sampling Bias
the participants chosen in a sample do not accurately reflect the population being studied. (Only female students’ responses were sampled; too few samples were chosen)
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Experiments Pros vs Cons
Pros Controlled experiments can show cause (Independent Variable) and effect (Dependent Variable). Cons Bias in the experiment's methodology or researchers' theories could skew results. There is also the confounding variable problem. Experiments can also be very costly.
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Correlational Studies
Correlational Studies help researchers predict the relationship between two variables. Scatterplots are used to show patterns of correlation. Pros Shows strength and direction of a relationship Cons Does not show cause and effect; third (confounding) variable problem.
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Correlation
is a measure of the extent to which two factors (variables) vary together (are or are not related), and thus how well one factor predicts the other.
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Correlation coefficient
is a statistical measurement of the relationship between two variables. The scale for cc is -1.00 to +1.00 and is represented by the letter r when the coefficient is calculated. Perfect positive correlation: r = + 1.00; perfect negative correlation: r = - 1.00; no relationship: r = 0.
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Variable
is anything that can realistically and ethically be measured.
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Scatterplot
is a visual representation of a correlation coefficient. It’s a graphed cluster of dots, which represent the values of two different variables. The amount of scatter suggest the strength or weakness of the relationship between the two variables.
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Illusory Correlation
is the phenomenon of perceiving a relationship between two variables (typically people, events, or behaviors) even when no such relationship exists.
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Regression Towards The Mean
the tendency for extreme or unusual scores (or events) to fall back (regress) toward the average. This is true of scores way above or way below the mean.
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Case Studies
Case Studies are an in-depth investigation of an individual, family, group, event, or other entity. Multiple types of data (psychological, physiological, biographical, environmental) are assembled to understand an individual's background, relationships, and behavior. (APA) Case studies can also be an example of a longitudinal study. Longitudinal studies follow a particular person, group or topic / trend over a long period of time. Pros Can observe rare behaviors; captures the context and lived reality of participants. Cons Collected data can’t be used to generalize to / for a population; participants may drop out; expensive & time-consuming; Hawthorne effect Case Studies, like Naturalistic Observation, only describe behavior, they do not explain it. What happened,not why it happened!
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Naturalistic Observations
Research that observes behaviors as they happen in a “real-world” setting. There is no lab. Pros The environment is an authentic one in which the participants are familiar. Cons Can be limiting in context; participants may alter their behavior as a result of knowing they are being observed (Hawthorne Effect). Depending upon the time frame, what is observed may be an anomaly.
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Surveys
Surveys are self-reported data from questions that often ask for an individual's opinions, thoughts, or information on things they have experienced or believe. Pros Inexpensive, provides large amount of data and data that is hard to observe (feelings and opinions), relatively easy to administer. Cons Participants might desire to look good in answers (Social Desirability Bias), wording of questions can create leading questions and skew data (Wording Effect)
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Meta-Analysis
A meta-analysis is when researchers take the results from a group of different studies about the same topic and combine them to get a bigger picture. By looking at many studies together, they can figure out what the overall findings are, rather than relying on just one study. Example: Does Exercise Help Reduce Anxiety? Instead of doing just one new study, a team of researchers looks at 20 different studies that have already been completed on the relationship between exercise and anxiety-reduction. Each study might have a slightly different result, but by combining all of the results in a meta-analysis, the researchers can see that, overall, exercise does seem to reduce anxiety for most people.
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Data Analysis
When analyzing data, it is broken down into two general categories, quantitative and qualitative. Quantitative data is data that is statistical in nature, or numerical. It is objective and not open to interpretation. Qualitative data is data that is subjective in nature and reveals the thoughts, opinions and feelings of those who are surveyed or take part in research. An Example of quantitative data would be the total number of students enrolled in AP psychology at Syosset high school for the 20 24–2025 school year. Examples of qualitative data would include the students’ favorite AP Psychology teacher at Syosset high school (you know who I’m talkin bout), least favorite subject matter, and favorite food served in the cafeteria.
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Descriptive Statistics
When analyzing data, we must understand the differences between descriptive statistics, and inferential statistics. Descriptive statistics summarize and describe data that researchers have already collected. Common descriptive statistics include Mean (statistical average), Median (the middle number or data point when you arrange the data in order), and Mode (the number or data set that appears most often). The Range, which is the difference between the highest and lowest numbers, is also an example of descriptive statistics. Descriptive statistics help you organize and summarize the information in a way that's easy to understand, but it doesn't help you make predictions.
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Inferential (Analytical) Statistics
Inferential Statistics (AKA Analytical Statistics) help researchers make predictions or conclusions about a larger group based on a smaller sample. These statistics help you go beyond the data you have to make educated guesses (predictions) about what might be true for a bigger population. Inferential (analytical) statistics help you make predictions or decisions based on your data. For example, let's say we want to know the average test scores for all 9th graders in your school, but you can't ask every single student. Instead, you take a sample of 30 students and calculate their average score. You then use inferential statistics to predict the likely average score for all 9th graders in the school based on that sample.
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Descriptive and Inferential Statistics: A Simple Illustration
Imagine we run an experiment to see how students feel about AP Psychology. We ask 60 students (from the periods 2 & 8 classes) whether they like the class or not. Descriptive Statistics: We find and report that 36 students said yes and 24 said no. This means that 60% of our sample population likes AP Psychology. Inferential (Analytical) Statistics: we use that 60% result to predict that around 60% of students in Syosset Senior High School like AP Psychology, even though we didn’t ask everyone.
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Measures of Central Tendency
Measures of central tendency are a single score that represents a whole set of scores. The single scores are used to make the data more manageable and easy to understand and work with. The simplest measure is the mode, which is the most frequently occurring score or scores. A bimodal distribution occurs when there are two frequently occurring scores. The most familiar measure of central tendency is the mean, or arithmetic average. The median is the midpoint or center of a distribution; AKA the 50th percentile.
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Percentile Rank
is also used as a measure of central tendency. Percentile rank is the percentage of scores that are less than a given score, so if you were in the 79th percentile in a math competition, your score is higher than 79% of your peers.
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Mean
The Mean is the average of all the values in a dataset. You find it by adding up all the values and dividing by the total number of values. For example, if you have test scores of 85, 90, 88, 92, and 89, the mean score would be (85 + 90 + 88 + 92 + 89 = 444 / 5) 88.8. During the past month, Henri and Sylvia each ate 10 candy bars, while Jerry ate 8, Tricia ate 6, and Tahli ate only 1. What is the mean number of candy bars eaten by these individuals?
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Median
The median is the middle value when all values are arranged in order. For instance, if you have test scores of 85, 90, 88, 92, and 89, when arranged in order, the median would be 89 because it's the middle value. If there is an even number of values, it's the average of the two middle values. If you have values of 79, 88, 62, 90, 96 and 84, the median would be 86. (62, 79, 84, 88, 90, 96; 84 + 88 = 172; 172/2 = 86)
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Mode
The mode is the value that appears most frequently in a dataset. For example, 88 is the mode for the following dataset: 88, 11, 66, 72, 88, 99, 81
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The Range
The Range is the difference between the highest value point of a data set and the lowest value point of a data set. In the following data set reflecting hours slept a night for grade 12 HS students, we have the following values: 5, 7, 4 ,8, 7, 6, 10, 9, 6, 7, 9, 11 What is the range in this data set representing hours slept per night?
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Measures of Variation
In addition to Measures of Central Tendency, we have Measures of Variation. Measures of Variation give researchers insight into how much variety or difference there is with the data that they collect. Results that come from scores with low variability are more reliable than results based on scores with high variability, especially when researchers are looking at the strength of a relationship between two variables, and if there is actually a cause and effect relationship between them. One way of determining variation is to look at the range of scores. As we learned earlier, the range is the difference between the highest and lowest score. For example, if we had student scores of 100, 96, 90, 88, 82, 80, 74, and 60 on a math test, we could determine that the range of scores is 40. This is calculated by subtracting the lowest score (60) from the highest one (100). Another measure of variation that is used in research is something known as the standard deviation. Standard deviation
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The Z-Score
The Z-Score (or standard score) represents the number of standard deviations a data point or score is from the MEAN data point or score.
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Null Hypothesis
Think of it as the “no relationship” hypothesis. It indicates that there is no significant effect or relationship between the things we're studying. For example, if we're looking at whether studying with classical music playing in the background helps you earn better grades, the null hypothesis would say, "Listening to classical music while studying has no impact on your grades."
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Alternative Hypothesis
The alternative hypothesis is what we really want to find evidence for and support with our research. In our music example, it would be something like, "Listening to classical music while studying improves your grades." Testing: To figure out which hypothesis is right, we collect data and run statistical tests. If the data shows that listening to classical music doesn't really improve grades significantly, we'd say, "Well, our null hypothesis is supported." But if the data shows a clear improvement in grades when listening to classical music, we'd say, "Our alternative hypothesis is supported."
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P-Value
A P-Value is a number that helps researchers determine whether the results of a study are likely due to chance or if there's a real effect / statistical significance. - If the p-value is small, usually less than 0.05, it means the results are unlikely to have happened by chance, so the findings are considered statistically significant and this supports the alternative hypothesis. - If the p-value is large, greater than 0.05, it suggests that the results could have happened by chance or coincidence, and the findings may not be significant. This supports the null hypothesis. In short, a p-value helps researchers figure out if their results are meaningful, or statistically significant.
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Effect Size
tells us the strength of the relationship between the independent and dependent variables in an experiment and how meaningful the effect is in real world terms. Effect size is a way to measure how big or important the difference is between two groups in an experiment, and if it’s worthwhile to move forward with the findings. Example 1: a new allergy medicine has been shown to offer some relief to users, but the relief is so minimal and short-lived it’s not worth bringing the medicine to market. Example 2: Imagine you’re conducting an experiment to see if a new studying technique improves test scores. You have two groups of students who have been randomly assigned to their respective groups, Group 1 (experimental) who uses the new studying technique, and Group 2 (control) who uses the traditional method. After the test, you find that Group 1 (new technique/experimental) scored, on average, 10 points higher than Group 2 (traditional method/control). When you calculate the effect size, it is statistically significant and meaningful.
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Institutional Review Board
When research is conducted using human participants, a group of people Known as an Institutional Review Board is assembled to judge if the proposed study is ethical, safe and worthy of being conducted. Key components of safeguarding human participants include: Obtaining informed consent (participants understand and agree to the methods and purpose of the study) Protecting participants from “greater than usual harm and discomfort” Keeping personal information about participants confidential Debriefing participants at the conclusion of the study (explain the research afterwards and to let them know if there was any intentional deception involved in the process).