W2 notes Flashcards

(52 cards)

1
Q

objectivity

A

Science relies on objectivity, meaning that conclusions are based on facts, without influence from personal emotions or biases

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2
Q

subjectivity

A

subjectivity, means that conclusions reflect personal points of view

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3
Q

Scientists strive to be _______, but any observation by a human is, by definition, _________

A

objective; subjective

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4
Q

confirmation bias

A

The difference in attention and memory is called confirmation bias
It represents one reason why objective and systematic observation are important in scientific inquiries

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5
Q

critical thinking

A

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

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6
Q

theories

A

Science seeks to develop theories, which are sets of facts and relationships between facts that can be used to explain and predict phenomena

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7
Q

hypothesis

A

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

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8
Q

replication

A

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

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9
Q

descriptive methods

A

Descriptive methods including surveys, case studies and observations, provide a good starting place for a new research question

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10
Q

Correlational methods

A

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

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11
Q

constructs

A

Constructs are internal attributes that cannot be directly observed but are useful for describing and explaining behaviour

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12
Q

Operationalization

A

Operationalization is the process of taking an abstract construct and defining it in a way that’s concrete

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13
Q

descriptive methods

A

Descriptive methods allow a researcher to make careful systematic, real world observations
Illuminates associations between variables and establishes prevalence rates

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14
Q

case study

A

Case study provides an in-depth analysis of the behaviour of one person or a small number of people

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15
Q

naturalistic observation

A

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

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16
Q

surveys

A

Surveys allow us to ask large numbers of people questions about attitudes and behaviour

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17
Q

sample

A

One of the requirements for a good survey is the use of an appropriate sample, or subset of a population being studied

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18
Q

population

A

The population consists of the entire group from which a sample is taken

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19
Q

correlations

A

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

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20
Q

measure

A

A measure answers the simple question of “how much” of a variable we have observed

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21
Q

positive correlation

A

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.

22
Q

negative correlation

A

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.

23
Q

zero correlation

A

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

24
Q

independent variable

A

The variable controlled and manipulated by an experimenter is known as the independent variable

25
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
26
control group
The control group will receive all experimental procedures except exposure to the independent variable
27
experimental groups
The experimental groups experience different values of the independent variable
28
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
29
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
30
meta-analysis
Conducting a meta-analysis, or a statistical analysis often provides a clearer picture than do single experiments observed in isolation
31
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
32
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
33
placebo
This procedure requires a placebo, an inactive substance that cannot be distinguished from a real, active substance
34
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
35
longitudinal study
-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
36
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
37
valid measure
Valid measure actually measures what it’s supposed to measure
38
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
39
inter-method reliability
Inter-method reliability describes the positive correlation of several approaches to measure a feature in an individual
40
internal consistency
Internal consistency results from measures within a single test that positively correlate with one another
41
validity
Validity means that a measure leads to correct conclusions or evaluates the concept that it is designed to do
42
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
43
descriptive statistics
Descriptive statistics helps us organize individual bits of data into meaningful patterns and summaries
44
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
45
normal distribution
Normal distribution is symmetrical, has equal numbers of scores above and below the mean
46
correlation coefficients
Correlation coefficients can range from -1.00 to +1.00. When the score is either of the 2, the correlation is perfect
47
inferential statistics
Inferential statistics permit us to draw inferences or conclusions from data
48
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
49
statistical significance
Statistical significance is a standard for deciding whether an observed result is because of chance
50
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
51
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
52
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)