11 Apr If a study is comparing number of falls by age, ag
If a study is comparing number of falls by age, age is considered what type of variable?IntervalOrdinalRatioNominalValidity is:A data item, such as characteristics, numbers, properties, or quantities, that can be measured or counted.The extent to which an idea or measurement is well-founded and an accurate representation of the real world.A measurement level with equal distances between the points and a zero-starting point.Raw unorganized information from which conclusions can be made.Data is defined as:A data item, such as characteristics, numbers, properties, or quantities, that can be measured or counted.The extent to which an idea or measurement is well-founded and an accurate representation of the real world.A measurement level with equal distances between the points and a zero-starting point.Raw unorganized information from which conclusions can be made.External and internal influences within a study that can affect the validity and reliability of outcomes is called:Continuous variablesDemographicsBiasStandard deviationLevel of measurement that defines the relationship between things and assigns an order or ranking to each thing is known as:IntervalOrdinalRatioNominalThe average of the collected data is known as:MeanMediaVarianceRangeThe subset of the population to be studied is called:SampleVariablePopulationDemographicWhen a researcher uses a random sample of 400 to make conclusions about a larger population, this is an example of:Descriptive statisticsDemographicsInferential statisticsDependent variablesA variable is considered:A data item, such as characteristics, numbers, properties, or quantities, that can be measured or counted.A component of mathematics that looks at gathered data.Statistics designed to allow the researcher to infer characteristics regarding a population from sample population.External and internal influences within a study that can affect the validity and reliability of the outcomes.The experimental or predictor variable is an example of:Extraneous variableDependent variableIndependent variableNominal dataHLT 362 Applied Statistics for Health care ProfessionalsWeek 3 QuizIf you are conducting a study on the impacts of diet and exercise on high blood pressure and you take a proportional sample based upon race/ethnicity, this would be an example of:Simple random sampleCluster samplingStratified samplingConvenience samplingIf a researcher does not select the appropriate level of significance (alpha) based upon prior research or industry standard and concludes that the study found a statistical difference when in fact there was no difference, this is referred to as:ValidityReliabilityType I errorType II errorTo obtain a sample of 20 patients in ICU, clinician goes to the ICU and selects the current patients. This is an example of a:Judgement samplingSimple random samplingSnowball samplingConvenience samplingScenario Based Question: If you were conducting a study of blood pressure readings in a hospital unit, compared AM and PM readings, and assumed the data were normally distributed and variances were equal, what type of statistical test would be conducted?Separate variance t-testPaired t-testPooled variance t-testF-testWhich of the following can be reduced by proper interviewer training?Neither sampling error nor measurement errorSampling errorBoth sampling error and measurement errorMeasurement errorWhich of the following would be an appropriate null hypothesis?The mean of a sample is equal to 65.The mean of a population is greater than 65.The mean of a population is equal to 65.The mean of the sample is greater than 65.In a research study, if the sample size is too low and the results do not find a statistical difference when in fact there is a difference, this is referred to as:ValidityReliabilityType I errorType II errorQuantitative research strives for quality and the ability to apply the analysis to a broader population. This is referred to as:ValidityNormalityGeneralizationReliabilityA Type I error is committed when:We reject a null hypothesis that is true.We do not reject a null hypothesis that is true.We reject a null hypothesis that is false.We do not reject a null hypothesis that is false.A Type II error is committed when:We reject a null hypothesis that is true.We do not reject a null hypothesis that is false.We do not reject a null hypothesis that is true.We reject a null hypothesis that is false.
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