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# Population

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### Population

1. 1. Population: all possible members of the group you’re studyingSample: subset of the populationDescriptive statistics measures of central tendency (mean, median, mode). Measures of variability(range, standard deviation).Inferential statistics- drawing conclusions (using ANOVA-for 3 samples or more; T-TEST-for 2 samples)ANOVA- the analysis of variance statistic tests whether the means of more than two groups are equalALPHA= statistical significance =probability of a type 1 error (rejecting a null hypothesis when it is true)Alternative (research) hypothesis- the hypothesis that we are testing, contrary to null hypothesisNull hypothesis – the hypothesis that is of no scientific interest; sometimes the hypothesis of no differenceType 2 error: power; accepting a null hypothesis when it is false; say no difference but actually is present(missed)-will be using 0.05% (5%) NULL HYPOTHESIS NULL HYPOTHESIS (TRUE) (FALSE)REJECT TYPE 1 ERROR CORRECTFAIL TO REJECT CORRECT TYPE 2 ERRORDescriptive statistics: Data summarised in numerical form, such as mean, median, mode.:Central tendency - Numbers that give some indication of the distribution ofdata(mean,median,mode)Measures of variability are numbers that indicate how spread out a set of scores is along adistribution. Scores can be bunched up around the mean or spread out significantly along thedistribution. The three measures of variability are range, standard deviation, and variance.Mode-the number that appears the mostMedian- the middle number in a sorted list of numbersRange- The area of variation between upper and lower limits on a particular scaleStandard deviation: the square root of a variance.
2. 2. Variance- how far values lay from the mean; the square of standard deviationDirectional Hypothesis – one tailed test; results in one sample will be higher than the other. A nalternative hypothesis that predicts that the results of one condition will be greater (or less) than another, rather thana prediction that they will simply differ.Non-directional hypothesis – two tailed test; results will differ in some way (could be negative orpositive)Correlated samples- testing same individuals at different times; within subject ( all participants areexposed to every treatment or condition.)Independent samples- testing across individuals (groups) ; between subjectNon EmpiricalAuthority:-Source of expert info/advice (God, government, parents)-Can be wrong despite their convictions-Plays diminished role in scienceLogic:-System/mode of reasoning-Logical argument (deductive) if A+B are true= C follows-Useful as statements/ arguments they’re based upon-important to science, does not substitute for empirical evidenceIntuition:-Spontaneous perception/ judgments (first impression)-Common sense (shared attitudes, standard change over time, location)Characteristics of science:-Empirical (based on experiences)-Objective (knowledge through observations; allows replication)-Self-correcting (new evidence corrects previous beliefs)Assumptions of Sciece:
3. 3. -Realism: physical objects exist independently-Rationality-Regularity: world conforms to same universal laws nothing about human behavior falls outside of lawsnature-Discoverability: belief that it’s possible to answer any questions through use of scientific methods-Causality: belief all events are caused (determinism VS. free will)-Discovery of regularities: describing phenomena; discovering laws1) Law- statement that certain events are regularly associated w each other in an orderly way2) Does not necessarily imply cause-effect; searching for causesDevelopment of theories: 1) Theory- statement explaining 1 or more laws: -typically use at least 1 concept -concept: thought/notion; not observed directly. 2) Theories must be falsifiableRole of Theories: 1) Organize knowledge/ explain laws - Good theories explain a large # of events + laws 2) Predict new laws -discovery in one area opens up doors to others3) guide research4) Prediction + controlHypothesis- statement assumed to be true for purpose of testing its validityOperationalism- belief that scientific concepts must be defined in terms of observable observations. - Concept must be tied to something that can be observed/ experienced directly - Operational definition: precise description of a procedure used to empirically test a theoretical concept
4. 4. • Collect a few different measures when performing an experiment to be more accurate. • Be able to manipulate the variable – better for accuracy • Self report measures + observe the participants • When measuring don’t generalize be specific • Be very detailed in writing- to counteract questionable situations + repetition of experiment/researchChapter 5Variables- an aspect of testing condition that changes w different conditions - Operationalize theoretical concepts: a) Concepts = intangible (abstract) [anger, happiness, hunger] b) Variables = tangible [exam answers, level presses, # of customers servedVariable types: 1. Independent variables (IV) – condition manipulated (or selected) by experimenter to determine its’ effects on behavior. Researcher must be able to control variable -must have minimum 2 different levels (values) -all other variables held constant -subject variable -typically used in correlational studies2. Dependent variable (DV)- measure of subjects’ behavior that reflects the IVs’ effects. Can bemeasured across several dimensions.- Frequency: the # of times behavior is performed- Rate: frequency relative to time (MPH, WPH)-Duration: the # of time behavior lasts-Latency: time btw instruction and initiation of behavior-Topography: shape/style of behavior
5. 5. -Force: intensity/ strength of behavior-Locus: where the behavior occurs in the environmentConfounded Variable – one whose effects cannot be separated from the supposed IVCovarying factors- can’t easily separate effects outOther Variable Types: • Quantitative: varies in amount ( age, # of lever presses) • Categorical: varies in kind (college major, gender) • Continuous: falls along continuum (not limited to a certain number of values; weight, height) • Discrete: falls into separate “bins” (no intermediate values possible; murders committed, guests served)Measurement:Process of assigning numbers to events or objects according to a set of rules. Types of measurementscales: 1. Nominal: divides into categories 2. Ordinal: ranks in order of magnitude (one category, different options) 3. Interval: differences btw numbers are meaningful 4. Ratio: has a meaningful zero • Reliability- getting the same result across repeated measures of the same behavior -Test-retest reliability: degree to which the same test score would be obtained on separate occasions (SAT, GRE) -Internal consistency: degree to which various items on a test measure the same thing (GRE, sports trivia) • Validity- the extent to which the experiment measures what it is supposed to -measure should be reliable before it is valid -Construct validity:
6. 6. Does the test measure the theoretical constructs it’s supposed to and no others? -Face validity: Does the test appear to measure what it’s supposed to? -Types of validity: 1) Content Validity: Does the test sample the range of behavior represented by the concept being tested? 2) Criterion Validity: Does the test correlate w other measures of the same construct? How well does our test correlate with others?3) Measurement error: -Random error (aka error variance): Variability associated with a consistent bias. Ensure that all groups/conditions are equally affected by it, if it cannot be eliminated. Total Variance (DV) = tx Variance (IV) + Relevant/Confound Variable (RV) +Random Error (always alpha 0.05%) Ex: Strength of connection = cable/router modem + # of devisec; distance; interferer + .05%