Data Analysis Strategies - Essay Example

Running Head: Applications of sampling procedures and alternatives Applications of sampling procedures and alternatives [Institute's Name] Applications of sampling procedures and alternatives Abstract There are some researchers as well as the analysts who believe that there should be newer better and alternative methods other than the ones being used for the analysis as the statistical methods. Although it is fact that there are many data analysis strategies that are available in the market for the researchers and the analysts but still the fact that needs to be kept in mind is that the statistical data analysis is the one technique that has been seen to be much more reliable than the other newer techniques. Introduction Statistics gas been used by the analysts and the researchers for many purposes and some of which include the summarization as well as to describe the data is the best analytical manner. This is usually referred to as the descriptive research and this has been considered as the best methodology to convey the results to the readers. A research project always has the goal to investigate the causes and the reasons and thereby to be able to draw the conclusion in the basis of the changes that take place. Responses that have been counted in this vase are the independent or the dependent variables or the predictors (Park, 2005). In statistics sampling is referred to as the selection of a portion of the population whereas this is the sample that represents the major part of the population. Sampling types in this case include the convenience, accidental, quota sample, random sampling as well as the cluster sampling. In this case it has to be seen as to what the margin of error is in the specific sampling technique. Main problems that are faced in this case is the sample bias where the sample is not the representative of the whole population thereby the sample has to be chosen rather carefully. Importance that has been used in the statistical testing is that in the research projects it can be used to test the data in the experimental basis, so as to draw the conclusion that are based on the facts representing the major part of the population. In this case the main term that has been used is the confirmatory data analysis that uses the hypothesis to be tested in the population. Statistical hypothesis testing has been considered to be one of the main techniques in the frequentist statistical inference, and still it has been seen that this is the technique that has been under criticism. An important role is played by the statistical hypotheses testing in statistical inferences. It has been said by statisticians that the hypothesis testing although has many shortcomings and still there are many changes that are needed but it is the technique that plays central role in theory as well as the practice of statistics (Levin, 1998). When the null hypothesis are being tested than the main point that has to be taken into account is the effect size. As it has been known that here are four main parts of the statistical answers and they are inclusive of the effect size, the sample size, the alpha level that indicates the significance level of the newer or the odds that have been observed by the answer by the significance testing and the last one being the power that indicates the odds that have been observed by the reader of the research results. It has been estimated that tout of these for components there are some components that can be manipulated and this all depends upon the situation and the circumstances in which the research of the project has been carried out. The main point that needs pt be argued here in this case that the null hypothesis is known as the null hypotheses as it has the no difference or no effect case. The main statistical technique that has been facing the discussion hitherto by the professors, the researchers is the significance test. It has changed its face into a controversy from being just the topic of discussion these days. Since many years this is the topic of discussion for many researchers and the professors in case of the conduction of the analysis in the statistical fields. The researchers as well as the ones who use the statistical analysis techniques or the ones who have been using the techniques are the ones who have been seen busy discussing the pros and cons of using the technique for analysis. It has been seen that these are the discussions and the debates that date back to the decades and the principles that outline the debates are generally referred to as the generational correctness (Gall, 2001). The discussions have been seen to be noticed in many scenarios however the main scenario that has been noticed is the ones in which it has been strongly said that the hypothesis testing in the form of significance testing is the way that has been impeding and slowing down the scientific progress since the last many years. Still these are the same professors and the researchers who have deeply analyzed the work that has been done with the help of the statistical significance testing and that, in some cases have said that there ios no greater harm being caused by its use in the academic research. The researchers and the critics have admitted and acknowledged to the fact that the significance testing has been seen to prove much of the unproved facts in the past decade. A number of researches have been carried out on the hypothesis testing and it has been said that the scholars and the academicians are the ones that have abandoned the significance testing. The statement has been given by some of the most eminent researchers of the times. The point that needs to be argued here is that there are not much researchers who have not been using the statistical significance testing systems. In the case it can be argued here significantly that there has been no evidence or there has been no survey that has been carried out in this regard that shows that the researchers and the scholars have abandoned the use of the statistical techniques in the academic work (Levin, 1998). As it has been mentioned in the previous sections that the committees have been discussing and have been trying to persuade the researchers to abandon the statistical testing techniques, and these committees are inclusive of APA, while from APA there have been many eminent scholars who themselves argue on the positive level about the significance testing being used in the research. In accordance to the many statements that have been given by these erudite learners it has been said that the significance testing must not be abandoned on a complete note however it should be improved in the ways that makes the testing work in the better manner. In the testing systems there are some enhancements that are needed so that the research can be carried out in a better way. As has been known by the researchers that the null hypothesis are the ones that are tested by using the significance testing. In this case it has to be added that a pragmatic approach is needed in this case so as to understand the importance that is associated with the significance testing. As has been seen that the null hypothesis are always tested by the saying that they are being tested by the significance testing and this needs ot be changed in many ways. In this case this needs to be added that there has been a great deal of research done on the significant hypothesis texting and it has been realized by the many researchers that the results that are given by the statistical significance testing are not very pragmatic and significance. The recommendations that have been given by the researchers say that the results that are presented by the null hypotheses testing systems are not very pragmatic as well as the importance of the results are not reflected by the test results. In addition to this the main point that needs to be argued is that the academic policies that are changing need to be welcomed as to has been discussed in the previous section that the hypothesis testing has been deemed unable to be proving any important in the case of the results. Thereby there are many academic committees who believe that the hypothesis testing by the help of the significance testing should be banned from all the academic journals. In case of the many debates have taken place in case of the null hypothesis texting it has been said that the discussions need to include the pragmatics related to the significance testing. It has been added by the critics that when the irrelevance e of the significance testing is being discussed than even the 1% significance of the null hypotheses testing has to be attested as well as appreciated to a significant level. An argument that arises here is that there are many eminent scholars who believe as yet that there are many cases in which the significance testing have proved their importance and these are the test s that in some cases have proved that they cannot be nullified in all manners in the academics. Although the errors that have been seen to be associated with the tests are sampling errors as well as the effect sizes that can show the errors but still the results do hold an importance (Gall, 2001). The design of experiments is an important part and in this case the power analysis takes a lead. Meaningful effect size can be estimated through the power analysis and the proper designing of an experiment helps in making an experiment have better outcomes. In the case of power analysis it has been seen that the resource usage and the study design can be optimized and this can lead to better results (Chen). However with the use of power analysis there are some problems in this case. Power analysis by some statistical analysts has been found problematic as it is being performed in an infrequent manner as well as in an inefficient manner. Power analysis has been found to be technically complicated especially as it has been under determined in the curriculum of statistics. In the case of power analysis the proper meanings of the terms and need to be interpreted as there meanings can be important in making the conclusions for the results that have been obtained (Trochim, 2006). Conclusion It has been seen that the results that are seldom displayed by the research in the significance testing are not to be relied upon. It has been seen by the researchers that although there are some significance in the testing systems but still these are not to be banned in the academics. These are the tests that have their own significance in all cases. References Gall, M. D. (2001). Figuring out the importance of research results: statistical significance versus Practical significance. Paper presented at 2001 annual meeting of American Educational research Association. Retrieved august 2009 from www.uoregon.edu/mgall/statisitcal_significance_v.htm Levin, J. L. (1998). What of there were no bickering about statistical significance tests Research in the schools. 5(2), 43- 53. Retrieved august 2009 from www. perrsonal.psu.edu/users/d/m/dmr/sigtest/6mspdf.pdf Park, H. M. (2005). Hypothesis testing and statistical power of a test. UITS Centre for statistical and mathematical computing. Retrieved August 2009 from www.indiana.edu/statmath/stat/all/power/power.pdf. Chen, C. & Teffeau, L. (n.d.). Self-administered surveys: Mail survey methods. http://www.business.uiuc.edu/shavitt/BA_531/week10.ppt Trochim, W. (2006). Statistical power. Research Methods Knowledge Base. From http://www.socialresearchmethods.net/kb/power.htm Read More