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70 Cards in this Set
- Front
- Back
Non-Scientific Methods of Acquiring Knowledge |
Method of Tenacity(Superstition) Method of Authority Method of Intuition Empirical Method (direct observation/experience) Rational Method (logical reasoning)
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The Scientific Method |
an approach to acquiring knowledge that involves formulating specific questions, then systematically finding answers |
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Induction/ Inductive Reasoning |
Involves using relatively small set of specific observations to form a general statement about a larger set of observations |
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Deduction/ Deductive reasoning |
Uses general statement to reach a conclusion about specific examples |
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What are the 3 important principles of the scientific method? |
It Is: 1)Empirical 2)public 3)objective |
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What are the 4 elements of a good Hypothesis? |
It is: 1)Logical 2)Refutable 3)Testable 4)Positive (it affirms the existence of something) |
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Applied Research |
Research studies that are intended to answer practical questions or solve practical problems |
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Basic Research |
Research studies that are intended to answer theoretical questions or gather knowledge simply for the sake of new knowledge |
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Primary Source |
A firsthand report of observations or research results written by the individuals who actually conducted the research and made the observations |
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Secondary source |
A description or summary of another person's work, written by someone who did not participate in the research or observations being discussed. |
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Clinical Equipose |
The ethical issue requiring clinicians to provide the best possible treatment for their patients, thus limiting research to studies that compare equally preferred treatments |
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Passive Deception (Omission) |
The withholding or omitting of info; the researcher intentionally does not tell participants some info about the study |
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Active Deception (Comission) |
The presenting of misinformation about the study to participants. |
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Informed Consent |
The ethical principle requiring the investigator to provide all available info about a study so the participant can make an informed, rational decision about whether to participate in the study |
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Debriefing |
A post-experimental explanation of the purpose of the study; Given after a participant has completed the study, especially if deception was used. |
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Confidentiality |
The practice of keeping strictly secret and private the info or measurements obtained from an individual during a research study |
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Anonymity |
The practice of ensuring that an individual's name is not directly associated with the info or measures obtained from that individual |
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Fraud |
The explicit effort of a researcher to falsify or misrepresent data |
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Replication |
The repetition of a research study using the same basic procedures used in the original; it either supports the original by duplicating the results or casts doubt by demonstrating that the original results are not easily repeated |
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Plagiarism |
The representation of someone else'e ideas or words as one's own. |
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Hypothetical Construct |
Hypothetical attributes or mechanisms that help explain and predict behavior in a theory |
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Operational Definition |
A procedure for measuring and defining a construct; Specifies a measurement procedure (set of operations) for measuring an external observable behavior and uses the resulting as a definition and measurement of a hypothetical construct |
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Validity |
The degree to which the study accurately answers the questions it was intended to answer |
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Face Validity |
Concerns the superficial appearance, or face value of a measurement procedure; Does the technique look like it measures the variable it claims to measure? |
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Concurrent Validity |
Validity demonstrated when scores obtained from a new measure are directly related to scores obtained from a more established measure of the same variable |
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Predictive Validity |
Validity demonstrated when scores obtained from a measure accurately predict behavior according to a theory |
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Construct Validity |
Demonstrated when the scores obtained from a measurement behave exactly the same as the variable itself |
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Convergent Validity |
Demonstrated by a strong relationship between the scores obtained from 2 different methods of measuring the same construct |
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Divergent Validity |
Demonstrated using 2 different methods to measure 2 different constructs. Convergent validity must be shown for each construct, then there should be little or no relationship between the scores obtained for the 2 different constructs when measured by the same method |
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Reliability |
The degree of stability or consistency of measurements |
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Test-Retest Reliabilty |
Established by comparing the scores obtained from 2 successive measurements of the same individuals and calculating a correlation between the 2 sets of scores |
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Parallel-Forms Reliability |
Established by comparing scores obtained by using 2 alternate versions of a measuring instrument to measure the same individuals and calculating a correlation between the 2 sets of scores |
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Inter-Rater Reliablity |
The degree of agreement between 2 observers who simultaneously record measurements of the behaviors |
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Split-Half Reliability |
Obtained by splitting the items on a questionnaire or test in half, computing a separate score for each half and then calculating the degree of consistency between the 2 scores for a group of participants |
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What are the 4 Scales of Measurement? |
1) The Nominal Scale 2)The Ordinal Scale 3) Interval Scale 4)Ratio Scale |
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Nominal Scale |
Categories represent qualitative difference in the variable being measured; categories have different names that are not related in any way (eg. Name, Occupation, Address) |
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Ordinal Scale |
Categories have different names and are organised sequentially (1st, 2nd, 3rd)` |
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Interval Scale |
The categories are organised sequentially and all categories are the same size. The zero point is arbitrary and does not indicate an absence of the variable being measured (eg. temperature,) |
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Ratio Scale |
The categories are sequentially organised, all categories are the same size, the zero point is absolute or non-arbitrary and indicates a complete absence of the variable being measured (eg Pounds, Time etc) |
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Artifact |
A non-natural feature accidentally introduced into something being observed; an external factor that may influence or distort the measurements |
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Experimenter Bias |
Occurs when the measurements obtained in a study are influenced by the experimenter's expectations or personal beliefs regarding the outcome of the study |
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How can experimenter bias be reduced? |
Through: 1)Single-Blind research 2)Double-Blind Research |
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Reactivity |
Occurs when participants modify their natural behavior in response to the fact that they are participating in a research study or the knowledge that they are being measured |
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Demand Characterstics |
Any of the potential cues or features of a study that 1)Suggest to the participants what the purpose and hypothesis is and 2)influence the participants to respond to behave in a certain way |
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What are the 2 general categories of statistical techniques? |
1)Descriptive statistics 2)Inferential statistics |
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Descriptive Statistics |
Methods that help researchers organize, summarize and simplify results obtained from research studies (eg graph, table, average scores) |
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Inferential Statistics |
Methods that use the results obtained from samples to help make generalizations about populations |
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Statistic |
A summary value that describes a sample |
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Parameter |
A summary value that describes a population |
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Central Tendency |
A statistical measure that identifies a single score that defines the center of a distribution. The goal is to identify the value that is most representative or typical of the entire group |
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What are the 3 measures of central tendency? |
1)Mean 2)Median 3)Mode |
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Mean |
Obtained by adding the individual scores, then dividing the sum by the number of scores. |
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Median |
Measures central tendency by identifying the score that divides the distribution in half (Arrange scores in order, median is the one in the middle) |
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Mode |
Measure central tendency by identifying the most frequent occurring score in the distribution |
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Variability |
A measure of the size of the spread of score in a distribution |
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What are 2 methods of measuring variability? |
1)Standard Deviation 2)Variance |
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Standard Deviation |
A measure of variability that describes the average distance from the mean; obtained by taking the square root of the variance |
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Variance |
A measure of variability obtained by computing the average squared distance from the mean. |
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Sampling Error |
The naturally occurring difference between a sample statistic and the corresponding population parameter; i.e the sample does not produce a perfectly accurate picture of its population |
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Hypothesis Test |
An inferential statistical procedure that uses sample data to evaluate the credibility of a hypothesis about a population; determines whether the results are statistically significant |
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What are the 5 basic elements of a Hypothesis Test? |
1)The Null Hypothesis 2) The Sample Statistic 3)Standard Error 4)The Test Statistic 5) The Alpha Level (Level of Significance) |
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Null Hypothesis |
A statement about the population(s) or treatments being studied that says that there is no change, no difference, no effect or no relationship; i.e what would the parameters be if nothing happened
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Standard Error |
A measure of the average or standard distance between a sample statistic and the corresponding population parameter |
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Test Statistic |
A summary value computed in a hypothesis test to measure the degree to which the sample data are in accord with the null hypothesis; ie the actual difference in data & hypothesis divided by the difference expected by chance |
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The Alpha Level/ Level of Significance |
is the criterion for statistical significance that defines the maximum probability that the research result was obtained simply by chance; criterion for evaluating the significance of the test statistic |
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(Statistically) Significant Result |
Means that it id extremely unlikely that the research result was obtained simply by chance. |
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What are the 2 types of errors that can be made in hypothesis testing? |
1) Type I Error 2) Type II Error |
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Type I Error |
Occurs when the researcher finds evidence for a significant result when, in fact, there is no effect or relationship in the population. (Consequence: false report) |
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Type II Error |
Occurs when sample data do not show evidence of a significant effect when, in fact, a real effect does exist in the population |
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Standardized Distribution |
is composed of scores that have been transformed to create predetermined values for the mean and standard deviation; used to make dissimilar distributions comparable |