Solution of Ms-95 Assignment Dec 2011 Essay Example for Free

Solution of Ms-95 Assignment Dec 2011 Essay take to the woods TitleResearch Methodology for Management Decisions Assignment CodeMS-95/SEM II /2011 CoverageAll Blocks melody Answer all the questions and submit this assignment on or before 31st October 2011, to the coordinator of your study center. 1. chthonian the circumstances stratified random sampling design is considered get hold of? How would you engage such sample? formulate by means of an example. 2. Experimental method of research is not suitable in management field. Discuss, what atomic number 18 the problems in the introduction of this research design in business organisation? 3. What is the meaning of measurement in research? What difference does it make whether we measure in terms of a nominal, ordinal, interval or dimension scale? 4. Interpretation is a fundamental component of research Process. Explain. Why so? define the precautions that the researcher should take while interpreting his findings. 5. Write shot notes on a) Criterion of good research. b) babelike and Independent variable. c) Casestudy method. d) Components of a Research Problem. 1. Under the circumstances stratified random sampling design is considered appropriate? How would you select such sample? Explain by means of an example.ranked sampling is comm precisely utilize probability method that is superior to random sampling beca delectation it reduces sampling error. A stratum is a subset of the existence that share at least one common characteristic. Examples of stratums might be males and females, or managers and non-managers. The researcher low identifies the relevant stratums and their actual representation in the macrocosm. Random sampling is then used to select a sufficient number of subjects from each stratum. Sufficient refers to a sample size large enough for us to be reasonably confident that the stratum represents the population. tell apart sampling is often used when one or more(prenominal) of the st ratums in the population have a low incidence sexual congress to the other stratums. Stratified sampling strategies Proportionate allocation uses a sampling fraction in each of the strata that is proportional to that of the marrow population. If the population consists of 60% in the male stratum and 40% in the female stratum, then the relative size of the two samples (three males, two females) should reflect this proportion. Optimum allocation (or Dis per capita allocation) Each stratum is proportionate to the standard deviation of the distribution of the variable.Larger samples are taken in the strata with the greatest variability to mother the least possible sampling variance. A real-world example of using stratified sampling would be for a US political survey. If we wanted the respondents to reflect the diversity of the population of the United States, the researcher would specifically seek to include participants of various minority groups such as race or religion, based o n their dimension to the total population as mentioned above. A stratified survey could thus claim to be more representative of the US population than a survey of simple random sampling or taxonomical sampling.Similarly, if population density varies greatly within a region, stratified sampling will ensure that estimates move be make with equal accuracy in different parts of the region, and that comparisons of sub-regions can be made with equal statistical power. For example, in Ontario a survey taken throughout the province might use a larger sampling fraction in the less populated north, since the disparity in population between north and south is so great that a sampling fraction based on the provincial sample as a whole might result in the collection of only a handful of data from the north.Randomized stratification can also be used to meliorate population representativeness in a study. Advantages over other sampling methods focuses on important subpopulations and ignores i rrelevant ones improves the accuracy of estimation efficient sampling equal numbers from strata varying widely in size may be used to equate the statistical power of tests of differences between strata. Disadvantages can be difficult to select relevant stratification variables not useful when there are no homogeneous subgroups can be expensive subscribes accurate information about the population, or introduces bias. looks randomly within specific sub headings. =========================== thither may often be factors which divide up the population into sub-populations (groups / strata) and we may expect the measurement of evoke to vary among the different sub-populations. This has to be accounted for when we select a sample from the population in order that we entertain a sample that is representative of the population. This is achieved by stratified sampling.A stratified sample is obtained by fetching samples from each stratum or sub-group of a population. When we sample a population with several strata, we generally require that the proportion of each stratum in the sample should be the same as in the population. Stratified sampling techniques are generally used when the population is heterogeneous, or dissimilar, where certain homogeneous, or similar, sub-populations can be isolated (strata). Simple random sampling is most appropriate when the entire population from which the sample is taken is homogeneous.