W2 notes Flashcards
objectivity
Science relies on objectivity, meaning that conclusions are based on facts, without influence from personal emotions or biases
subjectivity
subjectivity, means that conclusions reflect personal points of view
Scientists strive to be _______, but any observation by a human is, by definition, _________
objective; subjective
confirmation bias
The difference in attention and memory is called confirmation bias
It represents one reason why objective and systematic observation are important in scientific inquiries
critical thinking
Critical thinking or the ability to think clearly, rationally, and independently, is one of the foundation of scientific reasoning
Involves the development of habits, skills and mindsets that can be continually improved with practice
theories
Science seeks to develop theories, which are sets of facts and relationships between facts that can be used to explain and predict phenomena
hypothesis
A hypothesis is a type of inference, or an educated guess, based on prior evidence and logical possibilities
A good hypothesis links concrete variables based on your theory and makes specific predictions
Scientists can never “prove” that a hypothesis is true because some future experiment, possibly using new tech not currently available, might show the hypothesis to be false
replication
results often undergo replication, which means that other scientists independently attempt to reproduce the results of the study in question
If the data are replicated, they will be accepted quickly
descriptive methods
Descriptive methods including surveys, case studies and observations, provide a good starting place for a new research question
Correlational methods
Correlational methods help psychologists see how 2 variables of interest, like the number of hours spent on social media platforms and symptoms of depression, relate to each other
constructs
Constructs are internal attributes that cannot be directly observed but are useful for describing and explaining behaviour
Operationalization
Operationalization is the process of taking an abstract construct and defining it in a way that’s concrete
descriptive methods
Descriptive methods allow a researcher to make careful systematic, real world observations
Illuminates associations between variables and establishes prevalence rates
case study
Case study provides an in-depth analysis of the behaviour of one person or a small number of people
naturalistic observation
Naturalistic observation is the in-depth study of a phenomenon in its natural setting
E.g. studying chimps in their habitat
Can sometimes be problematic as people change their behaviours when they know their behaviour is being observed
surveys
Surveys allow us to ask large numbers of people questions about attitudes and behaviour
sample
One of the requirements for a good survey is the use of an appropriate sample, or subset of a population being studied
population
The population consists of the entire group from which a sample is taken
correlations
Correlations measure the direction and strength of the relationship between 2 variables, or factors that have values that can change
E.g. a person’s height and weight
measure
A measure answers the simple question of “how much” of a variable we have observed
positive correlation
Positive correlation: height and weight usually show this type of relationship
E.g. in most cases, people who are taller weigh more than people who are shorter.
negative correlation
Negative correlation: high values of one variable are associated with low values of another
For example, high levels of alcohol consumption among postsecondary students are usually associated with low GPAs.
zero correlation
Zero correlation, in which the two variables have no systematic relationship with each other
When variables have a zero correlation, knowing the value of one variable does not tell us anything about the value of the other
For example, emergency room and law enforcement personnel are often convinced that they are busier with emergencies and crime on nights with a full moon
independent variable
The variable controlled and manipulated by an experimenter is known as the independent variable
dependent variable
A dependent variable is a measure used to assess the effects of the manipulation of the independent variable, to tell us “what will happen” as a result of the independent variable
control group
The control group will receive all experimental procedures except exposure to the independent variable
experimental groups
The experimental groups experience different values of the independent variable
random assignment
To prevent individual differences from masking or distorting the effects of our independent variable, we randomly assign participants to experimental or control groups
Random assignment means that each participant has an equal chance of being assigned to any group in an experiment
confounding variables
Individual differences among participants are an example of confounding variables, or variables that are irrelevant to the hypothesis being tested and can alter or distort our conclusions
meta-analysis
Conducting a meta-analysis, or a statistical analysis often provides a clearer picture than do single experiments observed in isolation
publication bias
Published studies available to researchers conducting a meta-analysis might be subject to publication bias, or the possibility that they are not representative of all the work done on a particular problem
double-blind procedure
The gold standard for demonstrating the objective effects of any substance, whether a food additive, medication, or recreational drug is the double-blind procedure
-this procedure requires a placebo
placebo
This procedure requires a placebo, an inactive substance that cannot be distinguished from a real, active substance
cross-sectional study
To do a cross-sectional study, we might gather groups of people of varying ages and assess for example, both their exposure to violent video games and their levels of physical aggression
The cross-sectional method introduces what we refer to as cohort effects, or the generational effects of having been born at a particular point in history
longitudinal study
A method that reduces this dilemma is the longitudinal study, in which a group of individuals is observed for a long period
Sometimes participants drop out of the study since it’s too long or lack of incentive
mixed longitudinal design
The mixed longitudinal design, combines the cross-sectional and longitudinal methods
Faster and less expensive than the longitudinal method and avoids some of the cohort effects of the pure cross-sectional method
valid measure
Valid measure actually measures what it’s supposed to measure
reliability
Reliability refers to the consistency of a measure
Good measures show high interrater reliability, or consistency in the interpretation of a measure across different observers
inter-method reliability
Inter-method reliability describes the positive correlation of several approaches to measure a feature in an individual
internal consistency
Internal consistency results from measures within a single test that positively correlate with one another
validity
Validity means that a measure leads to correct conclusions or evaluates the concept that it is designed to do
reliability vs validity
You can obtain a consistent result (reliability) that lacks meaning (validity), but a measure can’t be valid without also being reliable
descriptive statistics
Descriptive statistics helps us organize individual bits of data into meaningful patterns and summaries
standard variation
The traditional way to look at the variance of scores is to use a measure known as the standard deviation, which tells us how tightly clustered around the mean a group of scores is
normal distribution
Normal distribution is symmetrical, has equal numbers of scores above and below the mean
correlation coefficients
Correlation coefficients can range from -1.00 to +1.00.
When the score is either of the 2, the correlation is perfect
inferential statistics
Inferential statistics permit us to draw inferences or conclusions from data
null hypothesis
The default position, stating that there is no real difference between 2 measures, is known as the null hypothesis
Rejecting the null, suggests that alternative hypotheses should be explored and tested
statistical significance
Statistical significance is a standard for deciding whether an observed result is because of chance
informed consent
Researchers must provide prospective participants with an informed consent form, which provides details about the purpose of the study and what types of procedures will occur
3 R’s of animal research
Replacement refers to research methods that avoid or replace the use of animals in an area of research where they would have been used
Reduction refers to any strategy that will result in fewer animals being used
Refinement refers to the modification of animal care or experiment procedures to minimize pain and distress
field experiments
Field experiments involve the manipulation of independent variables and measuring of dependent variables, but the experiments are conducted “in the field” (e.g. residential area)
