Research, Statistics and Psychology

Research is an organized study, methodical investigation in to a subject in order to discover facts, to establish or revise a theory, or to develop a plan of action based on the facts discovered. Research can also be defined as scientific investigation of alleged phenomena and events that appear to be unaccounted for by conventional physical, biological or psychological theories. The scientific research method is the means by which researchers put together conclusive and valid statements concerning a study they have done with a minimum of bias. Unfortunately data interpretation can be laden with bias.

The researcher often has personal stakes in the results of his conclusive statements and his work at large. For the purpose of minimizing the influence of personal stakes and biased opinions, a standard method of testing a hypothesis is to be used by all the members of the scientific community. The first step to using the scientific method is to have some basis for conducting your research which is based on observed phenomenon that is either directly or indirectly related to the specific subject matter of your proposed research. The second step is to form a hypothesis which will be used to explain some major aspects of your observations. You are now ready to test the hypothesis which you have formed. Your formed hypothesis will be used to predict other phenomena that have not yet been observed. The final step is to test your prediction. It should be noted that you cannot prove your hypothesis you can only fail to disprove it. While this is the way the scientific method is used in day to day research and hypothesis testing, it is also the basis of creating theories and laws. Most scientific methods in the present day require a hypothesis to be done away with if experiments repeatedly contradict the predictions made. A hypothesis may sound so great but it should be noted that any hypothesis is only as good as its ability to consistently predict experimental results. It should also be noted that a theory or hypothesis is not in any way meaningful if it is not quantitative and testable. Lakatos (1970) suggested that Kuhn (1970) was right to state that science does not progress by falsification. Lakatos proposed that theory tests are not two-cornered contests among competing theories and investigations. Some investigations result in confirmation rather than falsification. Lakatos proposed a scientific theory, T1, is falsified if, and only if, another theory, T2, has the following characteristics T2 predicts novel facts that are improbable for, even forbidden by, T1. Secondly, T2 explains the previous success of T1 that is, all the parts of T1 that have not been refuted are contained within T2 and finally some of the information in T2 exceeding that in T1 has been corroborated. The ultimate success of this approach of investigation is a sequence of problem-shifts of a series of theories T1, T2, T3 each having as much content as the un-refuted content of the previous one and differs from it by some additional proposition(s).

In comparison to Secondary data or second hand published data, Primary or first-hand data are very costly one reason is because primary data has never been gathered before. An advantage of primary data is you find the data you need to suit your purpose. Unfortunately because of the added expense associated with collection of primary data, there is no certainty that what is gained by way of improvement over secondary data sources is worth the added cost. A prior assumption of primary data supremacy are unwarranted poorly drawn samples, sampling errors, inadequate or poorly trained field workers, and poorly conceived schedules are among possible sources of error to balance against the possibilities of secondary data being inapplicable to a region. Using the primary research methods we note that focus groups bring together respondents with common characteristics and observations are actually made from viewing the respondents. Primary data makes it possible for the researcher to control variables and respondent groups as well as having one-on-one survey with respondents this increases the accuracy of the results in line with the current situations at the ground. On the other hand secondary data analysis saves time that would otherwise be spent collecting data and particularly in the case of quantitative data, secondary data also provides larger and higher quality databases than would be difficult for any individual researcher to collect on their own. A number of analysts consider secondary data essential, since it is impossible to conduct a new survey that can adequately capture past change andor development. The main purpose of both primary and secondary data is that they are collected and analyzed for the purpose of making valid inferences on the findings and eventually making sound decisions which solve the problem in question from the collected data.

Statistics is a branch of applied mathematics which consists of univariate and multivariate procedures. Psychologists use univariate procedures in research when they measure one variable and multivariate procedure are used when multiple variables are used to determine the relationship between two or more variables, to derive the test statistic and to extract factors.

Statistics is used to describe data in terms of the shape, central tendency and dispersion of their frequency distributions and to make decisions about the properties of the statistical populations on the basis of sample statistics in research. Statistical decisions are made with reference to a body of theoretical distributions the distributions of a number of test statistics that are in turn derived from the appropriate sample statistic. A parameter is basically a property of the population, where as a statistic is just characteristic of the sample. A test statistic is an index derived from the sample statistic. The test statistic is used to make a statistical decision about the population in a given research. Statistics is divided in to two descriptive and inferential statistics.  Psychologists use descriptive statistics to describe research data concisely. Psychologists apply inferential statistics to decide whether or not there is statistical significance with reference to a criterion value set in terms of the distribution of the test statistic.


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