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Term Define
DataObservations (such as measurements, genders, survey responses) that have been collected
StatisticsA collection of methods for planning experiments, obtaining data and then organizing, summarizing, presenting, analyzing, interpreting, and drawing conclusions based on the data
PopulationThe complete collection of all elements (scores, people, measurements, and so on) to be studied
Populationit includes all subjects to be studied
CensusThe collection of data from every member of the population
SampleA subcollection of members selected from a population
Sample datamust be collected in an appropriate way, such as through a process of random selection
If sample data are not collected in a appropriate way,the data may be so completely useless that no amount of statistical torturing can salvage them
TYPES OF DATA???Parameter,Statistic ,
ParameterA numerical measurement describing some characteristic of a population.
Parameterall of those votes to be the population considered, When Lincoln was first elected, he received 39.82% of the 1,865,908 votes cast which is 29.825.
StatisticA numerical measurement describing some characteristic of a sample
Based on a sampleof 877 surveyed executives, it was found that 45% of them would not hire someone with a typographical error on their job application
Quantitative dataData consists of numbers representing counts or measurement
Quantitative dataweights of supermodels
Interval level of measurementTemperature, Years
Interval level of measurementData that can be arranged in order and for which differences between data values are meaningful
Interval levelshoe sizes [US vs Europe] and temperature
Interval datacan be either discreet or continuous
Ratio level of measurementData that can be arranged in order, for which differences between data values are meaningful, and there is an inherent zero starting point.
Ratio level of measurementdifferences and ratios are meaningful
Ratio level of measurementprices of textbooks; $50 is half of $100
Ratio level of measurementHeight of students
Ratio datais continuous.
Ratio level of measurementHIGHEST LEVEL OF DATA
Ratio level of measurementcan be either discreet or continuous.
Quantitative (interval and ratio) datacan be further distinguished between discrete and continuous.
Discrete DataData that results when the number of possible values is either a finite number or a “countable” numbers.
Discrete DataCounting-type things
Discrete Datanumber of eggs that hens lay
Continuous (numerical) Datathickness of paper; measurement of weight
Continuous (numerical) DataResults from infinitely many possible values that correspond to some continuous scale that covers a range of values without gaps, interruptions, or jumps.
Continuous (numerical) Dataamounts of milk from cows
Qualitative (or categorical or attribute) dataCan be separated into different categories that are distinguished by some nonnumerical characteristics.
Continuous (numerical) DataThe genders (male/female) of professional athletes
Nominal Level of MeasurementCharacterized by data that consists of names, labels, or categories only
Nominal Level of MeasurementLowest form of data. Has groups, but no ordering to the groups
Nominal Level of Measurementcannot be arranged in an ordering scheme (such as low to high)
Nominal Level of MeasurementSurvey responses of yes, no, and undecided
Nominal Level of MeasurementColors of cars driven by college students (red, black, blue, etc.
Ordinal Level of Measurement(Categories & groups, but with some natural order to the groups.)
Ordinal Level of MeasurementCourse grades – Grades of A, B, C, D, or F
Ordinal Level of MeasurementRanking cities; those ranked 1st, 2nd, 3rd, etcBut, the differences between ranks are meaningless
Money and Counting areDiscrete
Temperature isInterval
Ages areusually Discrete
Man on the street samples arealways convenience sampling
Misuses of Statisticsself-selected surveyBad samplesSmall samplesMisleading graphsPictographsLoaded Questions
Misuses of StatisticsOrder of Questions
Misuses of StatisticsPrecise NumbersPartial picturesDeliberate Distortions
Randomnesstypically plays a critical role in determining which data to collect.
Observational StudyObserving and measuring specific characteristics without attempting to modify the subjects being studied. (Control group)
Cross Sectional StudyData are observed, measured, and collected at one point in time.
Retrospective (or Case Control) StudyData are collected from the past by going back in time.
Prospective (or Longitudinal or Cohort) StudyData are collected in the future from groups (called cohorts) sharing common factors.
ExperimentalApply some treatment and then observe its effects on the subjects. (Experimental group.) Doing something to affect what happens.
Experimental Key ElementsControl, Replication, Randomization
controlEffects of variables through: blinding, blocks, completely randomized, experimental design, rigorously controlled experimental design
ConfoundingOccurs in an experiment when the experimenter is not able to distinguish between the effects of different factors.
BlindingSubject doesn't know if he or she is receiving a treatment or placebo
Double-blindNeither the subject nor the experimenter knows whether treatment or placebo is being administered
BlocksGroups of subjects with similar characteristics
Completely Randomized Experimental DesignSubjects are put into blocks through a process of random selection
Rigorously Controlled DesignSubjects are very carefully chosen so that those in each block are similar in the ways that are important to the experiment.
Random SampleSelection so that each has an equal chance of being selected
Simple Random Sampleof size n
Systematic SamplingSelect some starting point and then select every Kth element in the population
systematic sampling7th person of a group of 10; i.e., 7, 17, 27, 37, etc., OR every 7th person i.e., 7, 14, 21, 28, etc
Convenience SamplingUse results that are easy to get, choosing the first 10 people who get off work
Stratified SamplingSubdivide the population into at least two different subgroups that share the same characteristics, then draw a sample from each subgroup (or stratum
Cluster SamplingDivide the population into sections (or clusters); randomly select some of those clusters; choose all members from selected clusters
Sampling ErrorThe difference between a sample result and the true population result; such an error results from chance sample fluctuations
Nonsampling ErrorSample data that are incorrectly collected, recorded, or analyzed (such as by selecting a biased sample, using a defective instrument, or copying the data incorrectly