Understanding Research Methods: Terms & Concepts in Quantitative & Qualitative Research, Quizzes of Statistics

Download Understanding Research Methods: Terms & Concepts in Quantitative & Qualitative Research and more Quizzes Statistics in PDF only on Docsity! TERM 1 research question DEFINITION 1 a measurable inquiry that add or extends on a body of knowledge TERM 2 three types of research questions DEFINITION 2 qualitative, quantitative, and mixed methods TERM 3 qualitative research questions DEFINITION 3 in which you use qualitative research questions to answer the research question TERM 4 quantitative research questions DEFINITION 4 in which you use quantitative research procedures to answer the research question; this type of research is the main focus in Stats of Social Science TERM 5 mixed methods research questions DEFINITION 5 in which you use both quantitative and qualitative research procedures to answer the research question TERM 6 phenomenon of interest DEFINITION 6 a specific measure related to the research question, being recorded where random outcomes occur per observation TERM 7 population DEFINITION 7 subjects (living or nonliving) that the question is trying to inquire information about TERM 8 What issues arise that prevent a researcher from answering the research question directly? DEFINITION 8 Costly, Time consuming, prone to experience bias TERM 9 nonresponse bias DEFINITION 9 bias that occurs when the researcher is not able to capture a response due to a refusal or because the subject is unavailable TERM 10 response bias DEFINITION 10 bias that occurs due to the result of falsification of answers by subjects or question confusion TERM 21 sampling DEFINITION 21 the act of selecting subjects from a population to create a sample. TERM 22 sampling bias DEFINITION 22 error that occurs from having a nonrepresentative sample from the population TERM 23 sampling frame DEFINITION 23 a list of the possible subjects to sample from. (not necessarily all of the originally selected subjects will always fit into a sample frame) TERM 24 sampling design DEFINITION 24 the methodology used for selecting subjects from the sample frame TERM 25 4 basic random sampling designs DEFINITION 25 simple random sampling design, cluster random sampling design, stratified random sampling design, systematic random sampling design. TERM 26 simple random sampling design (SRS) DEFINITION 26 involves selecting a sample of size n subjects (from N = subjects in sampling frame) from a population where each possible sample of that size has the same chance of being selected. Each subject in the sampling frame has an equal chance of being selected. Paper or electronic random number generator is used to select the subjects from the sampling frame. TERM 27 cluster random sampling design DEFINITION 27 in this desgin, the sampling frame is able to be broken into clusters by some natural auxiliary variable. The SRS is then used to selecet the clusters one at a time. Of the clusters randomly selected, use all of the subjects in the sample. TERM 28 stratified random sampling design DEFINITION 28 in this design, the sampling frame is able to be broken into strata by some natural auxiliary variable. This time, the researched will use each stratum by taking a SRS from each one. If the stratum are not the same size, then you must find out what percent of the subjects in this stratum represent that of the sampling frame. Divide the sample number by the sampling frame and multiply this number by the sample size (the selected people) to determine how many subjects to sample from that strata. TERM 29 systematic random sampling design DEFINITION 29 in this design, the researcher numbers each subject in the sampling frame the same as if the SRS was used. Then you randomly select the first subject from the first N/n observations in the sampling frame. The remaining subjects will be selected by going every kth observation from the first subject selected. Count the number of subjects in the sampling frame. Determine the sample size needed. find N/n and use the highest positive integer k where k is less than or equal to N/n. randomly select the first subject i where i is greater than or equal to one and less than or equal to k. Go every k elements in the sampling frame until the same size of n is gathered.