DNP 816 Test Questions and 100% Correct Solutions

Stastics - empirical or practical method for collecting, organizing, summarizing and presenting data & for making inferences about the population from which the data is drawn Probability - Likely-hood that something will happen Population - An entire group of individuals that a researcher wants to study Sample - A subset of those individuals selected from a population from which an investigator draws conclusions that are used to understand the population What is an example of a population study? - The U.S. census Parameters - The numerical measurements taken from the population Inferential statistics - Allows a researcher to generalize the results from a sample to a population through hypothesis testing Hypothesis testing - Examining data to determine whether there is sufficient evidence to reject the null hypothesis Random Sampling - Method of selecting subjects base don chance alone and is the strongest approach to sampling Simple random sampling - Taken so that all subjects in a population have an equal probability of being selected Systematic Random Sampling - Beings w/ assigning a number to each subject in the population and then selecting every 'nth' person (where n is the population size divided by the desired sample size) Stratified Random Sampling - Is useful when the researcher wants to ensure that certain groups are represented equally in the sample - divide the population into groups - called strata - ex. the researcher will divide pts by gender groups and then randomly select patients from each gender group A stratified random sample is _______________ if the subject size of each stratum in the sample is in proportion to that in the population - Proportionate A stratified random sample can be _________________ if the subject size of each stratum in the sample is non proportionate to that of the population - Non-proportionate Cluster Sampling - Similar to stratified sampling - is particularly useful when a population is large - works better when subjects in a cluster of heterogenous In general, cluster sampling provides _______ ____________ than simple random sampling or stratified sampling - Less precision - but more cost-effective and feasible approach Nonrandom Sampling - Members of the population do not have an equal chance of selection - prioritize feasibility or access Convenience Sampling - Non-random sampling - Based on the accessibility of subjects in the population - ex. using every student in a since course at a university (less likely to be representative of the population) Volunteer Sampling - Nonrandom sampling method where participants self-select into the sample Quota sampling - Nonrandom sampling - dividing the population into mutually exclusive (not overlapping) groups and selecting subjects from each group (the same as stratified random sampling, but it's not random) - can limit generalizability Snowball Sampling - Nonrandom sampling - Uses word of mouth, nomination, or referral to accrue subjects - useful for finding hidden subjects Sampling distribution - Distribution of a statistic that is computed from samples Sampling error - The difference between population mean, n and the sample mean - can affect our statistical estimate - when large, it means there is a lot of variability in the sampling distribution Confidence level - The level of assurance a researcher has that data from a study/studies represent true values Power analysis - Procedure to calculate the minimum sample size - should be performed before beinning a study Variable - Trait or characteristics that varies or changes Data - Values or variables when they vary Data set - A collection of data values