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111 Cards in this Set
- Front
- Back
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Problems with the scientific method.
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No Place for irrational or random behavior nor supernatural, spiritual, or intutional truths.
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Accuracy
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Predictive power. As close to the actual truth and value as possible.
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Parsimony
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Less is Better. The least complex explanation of a theory,not at the cost of accuracy, is the best
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The Assumptions of the Social Science Inquiry Process.
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There are patterns to find, and there are not random. Everything has a cuase that is observable. Knowledge is empirical.
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Goal of Social Science Research.
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To explain the past to understand the future.
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Independent Variable
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The cause or explanation of a phenomenon.
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Dependenat Variable
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The phenomenon to be explained. The dependent changes in response to the independent.
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LF
False Analogy |
An analogy that explains one common trait between two things is used universally to prove a point.
Eg. Watchmaker analogy |
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LF
Non-Sequitor |
"It does not follow"
A conclusion that does not follow it's premises. Eg. If I am in tokyo, I'm in Japan I'm not in Tokyo So I'm not in Japan. |
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Spurious Relationship
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Two occurences have no causual relationship, but appear to on account of a third unseen, confounding variable.
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Sufficient Casual Condition
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I X occurs, Y must occur. But Y can occur without X.
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Necessary Casual Condition
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X is nessecary for Y to occur. Never see Y unless X is present.
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Logic of Inference
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Inferring causation because complete formal proof of absolute causation is almost impossible.
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Validity
Vs. Reliability |
Validity-Do measurements correspond to the concepts in the theories
Reliability- If the same procedure is replicated the results are identical. |
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Operational Definition
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So narrow a definition there is no room for obsurity or procededral ambiguity.
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When can you use the Logic of Inference?
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Well Defined and valid concepts.
Makes common sense. Accuracy In good Chronological order. |
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LF
Idividualistic Fallacy |
You apply results from a local scale to the broader population.
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Cliche
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An overused or too familiar phrase or device, and when used it loses it's intended effect because it stirs up negative emotion publically.
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Passive Voice
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Object is being acted upon, and the subject is missing, vaquie, or de-emphasized.
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Colloqial
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Informal or Slang language.
Eg. Contactions |
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Jargon
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Pretentious or puffed up language. Also specialized language from a certain disipline.
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Dangling Modifier
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The thing being modified is missing or unclear.
Eg. "I saw the trailor peeking through the window." |
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Misplaced Modifier
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The thing being modified is in the wrong spot.
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Conceptual Definition
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Narrowing a concept down to a more specific idea.
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Mid-Range Theories
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Generalized sub-set of theories to explain specific behavior.
Eg. 20 year olds are selfish |
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Meta-Theories
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Theory of theories. Claim to explain all possible behavior on a large scale.
Eg. Non person acts out of Altruism |
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Falsifiable
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The ability of something that is detailed and specific to stand up to comphrensive critism. Aka Testibility
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Model
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A set of steps to test a theory's predictive ability based on a theory or hypothesis.
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Law
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Theory that has validity on a universal scale.
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Theory
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A possible and logical explanation of a phenomenon that involves a testable model.
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Paradigm
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An experimental setup with fine tuned standars and a theoritical background. A set of assumptions on which theory is based.
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Hypothesis
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An yet untested theory.
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Paradigm
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An experimental setup with fine tuned standars and a theoritical background. A set of assumptions on which theory is based.
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A Good Theory
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Specific Variables
Casual Story Accuracy Falsifiablity Concrete an Specific Generalizable |
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Why eternal truths don't matter
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"If you are trying to catch the bus, knowing God lives doesn't help you!"
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Paradigm
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An experimental setup with fine tuned standars and a theoritical background. A set of assumptions on which theory is based.
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Hypothesis
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An yet untested theory.
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Empirical
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Evidence is dependent on observable proof and produced by experiment or observation
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A Good Theory
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Specific Variables
Casual Story Accuracy Falsifiablity Concrete an Specific Generalizable |
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Hypothesis
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An yet untested theory.
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Why eternal truths don't matter
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"If you are trying to catch the bus, knowing God lives doesn't help you!"
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A Good Theory
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Specific Variables
Casual Story Accuracy Falsifiablity Concrete an Specific Generalizable |
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Parallel Structure
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A repitition of two or more similiar words, phrases, or clauses. Aka. parallelism
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Normative
Vs. Positive |
Normative: Adovacy, persuassive, call to action, bias.
Positive: Facts, Objectivety, Neutral. |
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Empirical
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Evidence is dependent on observable proof and produced by experiment or observation
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Why eternal truths don't matter
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"If you are trying to catch the bus, knowing God lives doesn't help you!"
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Inductive
Vs. Deductive |
In.-Empirical Evidence.
Eg.Watch a b-ball game to play it. De-theory. Eg. Read the b-bal rule book. |
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Parallel Structure
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A repitition of two or more similiar words, phrases, or clauses. Aka. parallelism
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Empirical
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Evidence is dependent on observable proof and produced by experiment or observation
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Normative
Vs. Positive |
Normative: Adovacy, persuassive, call to action, bias.
Positive: Facts, Objectivety, Neutral. |
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Deduction
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Fromal Logic where conclusions follow premises.
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Parallel Structure
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A repitition of two or more similiar words, phrases, or clauses. Aka. parallelism
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Induction
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Reasoning where premises lead to a conclusion but do not entail it.
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Inductive
Vs. Deductive |
In.-Empirical Evidence.
Eg.Watch a b-ball game to play it. De-theory. Eg. Read the b-bal rule book. |
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Nominal Data
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No set order, no gaps.
Eg. Major |
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Normative
Vs. Positive |
Normative: Adovacy, persuassive, call to action, bias.
Positive: Facts, Objectivety, Neutral. |
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Interval Data
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Gap betwen variables is exactly the same
Eg. Age |
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Deduction
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Fromal Logic where conclusions follow premises.
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Inductive
Vs. Deductive |
In.-Empirical Evidence.
Eg.Watch a b-ball game to play it. De-theory. Eg. Read the b-bal rule book. |
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Induction
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Reasoning where premises lead to a conclusion but do not entail it.
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Deduction
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Fromal Logic where conclusions follow premises.
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Ordinal Data
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Intervals without equal gaps.
Eg. Very, Somewhat, Strongly agree. |
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Induction
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Reasoning where premises lead to a conclusion but do not entail it.
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Nominal Data
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No set order, no gaps.
Eg. Major |
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Interval Data
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Gap betwen variables is exactly the same
Eg. Age |
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Ordinal Data
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Intervals without equal gaps.
Eg. Very, Somewhat, Strongly agree. |
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Nominal Data
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No set order, no gaps.
Eg. Major |
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Interval Data
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Gap betwen variables is exactly the same
Eg. Age |
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Ordinal Data
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Intervals without equal gaps.
Eg. Very, Somewhat, Strongly agree. |
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Ethical Arguments on LF
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It's Risky to use them.
Everyone does it. Sometimes they are Accurate Still Misleading |
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LF
Bandwagon |
Appeal to the majority. "Everyone else it doing it!" If everyone believes it, it must be.
Eg. "Watch the office, the #1 show on T.V. |
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Appeal to Authority |
Using an expert to prove a claim. Opposite of ad hominem.
Eg. Al Gore is an expert, so global warming must be real. |
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Circular Reasoning |
An attempt to support a statement simply by repeating it in different or stronger terms.
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False Cause |
A cause is incorrectly assigned to a phenomenom.
Correlation does not mean causation. |
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"Either or" |
When two options are held to be the only possible choices or outcomes, when in reality there are several.
Eg, "Either you are with us or the terrorists." |
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Red Herring |
A delibrate attempt to change or divert the subject with intentional distraction or diverson. Aka Misdirection.
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Ad Hominem
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Replying to an argument by attacking a characteristic or belief of your opposition that is irrelevant to the issue being discussed in order to subvert the issue being discussed
Eg. Hilary is a bitch, so here war policy must be wrong. |
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Qualitative Design
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Less than 20 cases or observations
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Quanitiative Non-Experimental
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More than 20 cases with no random assignment of the X.
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Quanitative Quasi-Experimental
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More than 20 cases where X cannot be assigned.
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Hawthorne Effect
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Productivity goes up when people are being observed.
Eg. Better Lighting |
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Quanitative Case-Selection
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Random or all cases and a control without the indep. variable.
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Qualitative Case-Selection
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Cross-case selection by either
1. Most Similiar 2. Most Different Single case selection by manipulating the dep. variable |
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Internal Validity
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Used in Qualitative-Eliminating confounding varibales to maintain good caustion.
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External Validity
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Used in Quanitative-
Finding of a study can be generalized to the population. |
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Dark Figure Stats
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Undiscovered or unreported stats that would effect the reliabity of your stats, stat analysis, or regression.
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Mutant Stats
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Stretched, Twisted, Distorted, or magled versions of the orginal #s. What you report is technically correct, but misleading, unrepresentative, or bias.
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Descriptive Stats
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The reporting of one outcome that appeals to public.
Eg. You study all last names but report the stat "80% of america has the last name smith." |
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Inferential Stats
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Used to draw assumptions about the sample as a whole. Comprehensive.
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Mean
Mode Median |
Average
Common Value Middle number of the values |
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Frequency
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The number of cases or obervations values for a variable.
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Distribution
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Plot of all the frequencies for a single variable.
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Dummy/Dichotomous Variable
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Two possible values can occur in a variable
Eg. Married, Gender, Virgin |
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Variance
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The average amount of deviation from the mean.
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Standard Deviation
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Deviation from the norm. Found in the Square root of the variance.
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Mu
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Standard Deviation for the entire population.
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X-Bar
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Mean
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Sigma
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S or greek E
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Normal Distribution
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-1 to 1 works on it.
Normal Bell Curve. |
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Z Score
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A way to universilize findings from different studies to compare them.
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Sample
Vs. Population |
The groups that participate in yor study.
Group of people which you get you're experimental group from |
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Substantive Significance
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If a value is above a certain significant value on the Z score chart, then there is a 95% it is significant.
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Statistical Significance
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If a value is lower than the significant value on the Z score schart, then it has no actual logicical significance, only numeral, mathematical, and statistical significance.
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PRE
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Orginal Error Rate-New Error Rate
----------------------------- Orginal Error Rate |
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Original Error Rate
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Accurate prediction of values of a varible when you have no other infomation.
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New Error Rate
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Accurate Prediction of the variable value when you know the value of another.
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Chi Squared
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Z Score for nouns instead of numbers.
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Null Hypothesis
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A way to try and prove your results wrong in order to prove them falisible, accurate, and correct. Use the Z score.
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Law of Large #'s
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The bigger the random sample, the more accurate the results are.
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Central Limit Theory
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The larger tha sample, the more normal the distribution will beomce, despite existing computed non-normal data and average in the population.
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Breakdown of SD
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68% chance it's within -1 and 1
95% Chance it's within -2 and 2 99.7 Chance it's within -3 and 3 |
