BSAD 3500 EXAM 3 with correct answers 100%

BSAD 3500 EXAM 3 with correct answers 100% Differentiate a sample from a census. - Correct Answer Sample is a selected part of the population. Census is information gathered by all population. How can a researcher overcome (random) sampling errors? - Correct Answer 1. Parameter: a characteristic or measure of population. 2. statistic: a characteristic or measure of sample. Differentiate probability and nonprobability samples. - Correct Answer 1. probability: a sample in which each target population elements has a known NONZERO chance of being included in the sample. (Random sampling) Ex. simple random, systematic, stratified, cluster 2. Nonprobability sample: a sample that relies on personal judegemtn in the element selection process. (Neither sampling error nor the margin of sampling error can be estimated or calucated. (non-random sampling) ex. convience/judgment/snowball/quota Differentiate cluster, stratified, convenience, judgment, quota, snowball, and systematic samples. Examples?Differentiate cluster, stratified, convenience, judgment, quota, snowball, and systematic samples. Examples? - Correct Answer 1. Cluster: like stratified sample (1) population is divided into mutually exclusive & exhaustive subsets. (2) unlike stratified sample; a simple random sample of subsets (ex. cluster) is chosen. ex: subsets are heterogeneous within but homogeneous between with respects to key variables. 2. Stratified: (probability technique) sample in which (1) population is dived into mutually exclusive & exhaustive subsets and (2) a simple random sample of elements is chosen independently from each group/subset. ex. Homogeneous vs. heterogeneous. 3. convenience: population elements are sampled simply because they are in the right place at the right time. (also called accidental sample). ex. Question of the day polls - students on campus etc. 4. judgment: population elements are handpicked because they are expected to serve the research purpose. ex. hire panelists who are knowledgeable about the issue being researched rather than selecting them at random. 5. quota: sample chosen so that the proportion of a sample elements with certain characteristics is about the same as the proportion of the elements with the characteristics in the target population. ex. 100 undergraduate students attitudes towards etc. 6. snowball: initial sample chosen by a probability technique. (ex. systematic sampling). then the population elements are asked for referrals of other they know who might be interested in participation. ex. a demand study for a new product where initial respondents know people with high interest level within the product category. 7. systematic samples: a probability sampling plan in which every kth element in the population is selected for the sample pool for a random start. What is a sampling frame? Identify examples. - Correct Answer The list of population elements from which a sample (n) will be drawn. ex. customer databases, telephone directories, lists developed by data compliers. Differentiate random sampling error and nonsampling error (often referred to as systematic error). What are some sources of nonsampling error? - Correct Answer 1. Random sampling error: the difference between results obtained from a sample & results that would have been obtained had information been gathered from or about every member of the population. 2. nonsampling error: (systematic error) error that arises in research that is not due to sampling. non sampling error can occur because of errors in conception, logic, interpretation of questions and replies, statistics, arithmetic, analyzing, coding or reporting. (cannot be accounted for statistically). Differentiate sampling error, noncoverage error, nonresponse error, response error and office error. What factors contribute to each? - Correct Answer 1. sampling error: 2. noncoverage error: nonsampling error that arises because of failure to include some unites or entire sections of the defined target population in the sample frame. (SAMPLING FRAME PROBELM). 3. nonresponse error: nonsampling error that represents a failure to obtain information from some elements of the population that were selected & designed for the sample. (potential problem that only occurs when those who do not respond are systematically different in some important way from those who don't respond. ex. university wants to assess the success of it's graduated based on their annual salaries, five yrs after graduation.