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PSYC2002C_Introduction to Statistics in Psychology_Liudmila Jdanova_Winter 2011( Full sets of class notes, good luck on exams)

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Department
Psychology
Course
PSYC 2002
Professor
Liudmila Jdanova
Semester
Winter

Description
Statistics Week 1 Descriptive statisticsUsed to describe the particular sample of data that you haveUsed to organize summarize and present dataEg what single value best represents your data How much variability is in your dataHow tall men and women are average grades of psychology majors vs math majors salaries in geographical regionsInferential statisticsUsed to make inferences about population parameters based on sample statistics generalize from sample to populationPopulationA complete set of individuals objects or measurements of interest ie to which we want our research findings to applySampleA subset of a population that shares the same characteristics as the populationRandom SampleA sample drawn in such a manner that each member of the population has an equal chance of being included in the sampleRandom AssignmentAssign subjects in a way so that each subject has an equal opportunity to be placed in each treatment condition ParametersNumerical values that summarize measurable characteristics of a populationRepresented by Greek lettersegStatisticsNumerical values that summarize measurable characteristics of a sampleTypically statistics are used to generate estimates of population parametersThese estimates are not perfect due to sampzg errorthe discrepancy amount of error that exists between a sample statistic and the corresponding population parameter Scientific Research Methods Research Design A systematic plan for collecting data in order to provide answers to specific questions I Experimental Method Experiment II NonExperimental Methods Studies 1 Descriptive research2 Correlation research 3 Quasiexperimental research Experimental Method True ExperimentVariableany measurable characteristic of a person environment or experimental treatment that variesIndependent Variable IVPresumed cause of DVthe variable that the experimenter manipulates in order to explain differences in the DV or to cause changes in the DVExperimental Experimenter can directly control or changeSubject measurable characteristic of subject that the experimenter does not changeGender height weight etcDependent Variable DVThe outcome of interest that is observed and measured by the researcher in order to assess any effects of the IVExtraneous Nuisance Variables Possible cause of the DV but are not under investigationMust be controlled in an experiment to avoid confoundsConfoundone or more extraneous variables changes with the IV making it hard to tell what the cause isExperimental MethodGoal to determine cause and effect relationshipsGeneral ProcessRandomly select subjects from the populationRandomly assign subjects to different treatmentsExpose subjects to IV manipulated by experimenter Compare dependent variable differences between the groups differences are caused by the manipulated IV Descriptive ResearchGoal Obtaining an accurate description of the population can also assess changes in a population over timeGeneral Process Collect data on variables of interest and use descriptive statistics to summarize the data that you collectCan not make many conclusions Use ONLY for description Correlational ResearchGoal To determine if there is a relationship between two or more variablesGeneral Process Randomly select subjects from the population simple random samplingCollect information on variables of interest Calculate a correlation coefficientCan determine whether things are related still can not determine cause and effectComparing Intact Groups Goal Is there a relationship between a grouping variable and some other variable General Process Randomly select subjects from the populationPlace subje87ucts into a group based on a subject variable smoker vs nonsmokerCompare group differences Can find significant differences between groups still no cause and effect VariablesQualitative Categorical DatadescriptionQuantitative Numerical DatanumbersDiscontinuous Variables akaDiscrete VariablesCounting unitsvalues can only be whole numbers there are no values between numberscant have 2 and a half people Continuous VariablesInfinite number of values between any two numbersLevels of Measurement1Nominal2Ordinal 3Interval 4Ratio 1 Nominal ScaleA numerical scale in which the numbers represent qualitative categorical differences among individualsExamples Marital StatusSingle1 Married2 Divorced3 Widowed4 Separated5 2 Ordinal ScaleA basic form of quantitative measurement that indicates a numerical orderThe numbers represent a position in an ordered series but not how much of a difference exists between successive positions on the scale stndrdExample Place finishes in a race1 2 3 etc 3 Interval ScaleA measurement scale that has equal units of measurement and an arbitrary zero pointHas the characteristics of nominal and ordinal scalesin addition equal differences intervals between numbers represent equal differences in the measured constructExample Temperature measured in degrees Fahrenheit 4 Ratio ScaleA measurement scale that has equal units of measurement and an absolute zero pointPossesses the characteristics of nominal ordinal and interval scalesCannot have negative values ExampleWeight Information content of the four scalesNominalAre two events the same or differentOrdinalIs the second event the same bigger or smaller than the firstIntervalIs the second event the same bigger or smaller than the first and by how muchRatioIs the second event the same bigger or smaller than the first and by proportionally how much twice as big etc Levels of Measurement PracticeIndicate the level of measurement for each of the followingRanking of the top five movies of all time ordinalNumber of children in a room ratioNumbers on football jerseys nominal
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