HLT362 Applied Statistics for Health care Professionals
Week 3 Quiz
If 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 sample
Cluster sampling
Stratified sampling
Convenience sampling
If 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:
Validity
Reliability
Type I error
Type II error
To 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 sampling
Simple random sampling
Snowball sampling
Convenience sampling
Scenario 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-test
Paired t-test
Pooled variance t-test
F-test
Which of the following can be reduced by proper interviewer training?
Neither sampling error nor measurement error
Sampling error
Both sampling error and measurement error
Measurement error
Which 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:
Validity
Reliability
Type I error
Type II error
Quantitative research strives for quality and the ability to apply the analysis to a broader population. This is referred to as:
Validity
Normality
Generalization
Reliability
A 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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