In an experimental research, the use of a research question answers the thesis statement that enables one to research about a problem (Yin, 2013). From the experiment, the research question can be clearly stated as “which vaccine is more effective for preventing getting the flu”. In this case, the problem being researched about is the flu the possible solutions to this problem which the use of vaccines is being analyzed. The null hypothesis of this experiment states that there is no effective vaccine for preventing getting the flu while the alternative hypothesis states that there is an effective vaccine for preventing getting the flu. The results obtained from such an experiment should be significant in that they should not be those that purely occur by chance but they have other causes for their occurrence. From the experiment, the results obtained are statistically significant because only a large proportion of the entire population of 1000 attempts to agree with the alternate hypothesis and therefore the null hypothesis would be rejected by the researchers.
However, the results from this experiment provides a clear view that 420 out of 500 participants were prevented from the flu by use of the shot and 380 out 500 participants were prevented from the flu by use of nasal spray. This shows that the most effective vaccine for preventing flu is the shot. It therefore gives sufficient evidence to support the alternate hypothesis that there is an effective vaccine for preventing getting flu. A sample of 500 participants in both researches is appropriate for this study since provides a wide area of study to the researcher hence enabling him to obtain almost accurate results in his research.
However, the study might have had certain limitations like lack of enough research materials to reach the large population, insufficient funds to contact the study and inaccurate results in the population. In conducting a follow up study, the use of questionnaires and interviewing will be the best techniques to use. This is because they are primary sources of information that give credibility to the already collected information. In research, there exist statistical and practical significance. Statistical significance is the effect whether the observed results are larger than expected by chance while practical significance is about if the observed results can be used in real application context.
Correlation is a mathematical measure that shows the extent to which variables can change in relation to each other. A negative correlation indicates that two variables are inversely related to each other while positive correlation shows a direct relationship between two variables (Sharma, 2005). From the study, a correlation value of 0.75 indicates a positive correlation between two variables whereby one variable directly changes 0.75 times the relevant change in another variable. When using a correlation of 0.75 to compare an individual’s intelligent quotient (IQ) and his own Grade Point Averages (GPA), it implies that an increase in intelligent quotient leads to relative 0.75 times increase in one’s Grade Point average. Therefore, intelligent quotient and Grade Point averages are slightly directly proportional to each other due to their positive correlation. This implies that individuals with high intelligent quotient have relatively high Grade Point Averages.
At a correlation of 0.75, high intelligent quotient leads to high Grade Point averages though at a relatively small proportional change since the correlation value is at 1.0 that indicates a perfectly positive relationship between the variables. A correlation value of 0.75 does not indicate a perfectly positive correlation. This is because there may be other factors affecting their relationship. Among these factors include different academic performance and records, various environments in which one is raised up, physical nature, gender and perception differences among various groups. However, a correlation between two variables does not necessarily imply causation but for a causal relationship to exist between two variables there must be a correlation between the variables (Solomon W. Golomb, 2005).
When predicting the Grade Point Averages, correlation might not be a good test for its prediction. This is because there is no GPA is not only influenced by intelligent quotient but it is also influenced by other external factors like Education background, family background, social and political environment among other factors. Other statistical tests may include the use of rating scales to rate qualities that cannot be directly rated through correlation by use of variables like good, fair, and excellent among others. Coefficient of correlation might also be used as a technique of predicting the Grade Point Averages. This refers to the main result of a correlation whereby it predicts significant and smaller changes among variables by use of scale r that ranges from +1.0 to -1.0.
Descriptive statistics are digits that are used to summarize and describe a given range of data (Klenke, 2008). Basic descriptive data includes, mean, median, mode, variance and standard deviation. The data can be rearranged in an ascending order as follows:
From the research study carried on 1000 participants to determine the most effective vaccine for preventing getting flu, its research question stated that “which vaccine is the most effective in preventing getting flu.” This was done in order to attain the purpose of the study which was to solve the flu problem and attaining the most effective measures of preventing the flu. During the research study, various methods were used for data collection, sample selection and use of statistical techniques.
Among the data collection methods was direct testing in the field by health personnel and the use of questionnaires where every participant was given a questionnaire to fill in data concerning the effective vaccine for preventing getting the flu and the feedback was given directly to the person administering the questionnaire (Dunbar, 2005). The population sample was randomly selected at various places and randomly subdivided into two groups to enable easy comparison of results and avoid biasness in data collection. Among the statistical techniques used was the use of distribution table to find an appropriate spread among the population and other computations including the mean, variance and standard deviation of the data in the sample.
However, the results obtained from the research study were accurate but they did not clearly reflect the alternative hypothesis that states that there is an effective vaccine for preventing getting the flu. By preventing 420 out of 500 participants and 380 out of 500 participants from getting the flu, both the spot and the nasal spray vaccines proved they are all effective in preventing one from getting the flu because they had a small difference in their effectiveness. Therefore the results did not clearly show that a particular vaccine is more effective than another even though a slight difference in the effectiveness was noted. Among the strengths of the study was the use of a large and appropriate population that facilitated almost accurate results obtained from the study (Klenke, 2008).
Use of accurate statistical and evaluation techniques enabled a clear interpretation of the results. The weakness noted in this study was lack of using appropriate variables in the study where all the variables displayed almost equal results. Lack of effective data collection methods and techniques might also be a weakness and a limitation of the study due to the large population sample involved. Use of few variables in the study became the major limitations of the study since its scope was only limited to the two variables stated.
In conclusion there should be appropriate future research directions include the use of an appropriate topic of research whose variables can be clearly distinguished to reduce the limitation of the study. The population sample used should also be effective and appropriate based on the scope of the study, where the variables under study are more there should be a large population sample to be studied to capture all the characteristics under the study. Finally, the use of appropriate descriptive statistics should be used in a research study to facilitate its analysis. Among these statistics basics include computation of the mean, median, mode, variance, standard deviation, skew and the spread of the data. These techniques enhances a clear analysis and interpretation of the research results to the concerned parties hence confirming if the key purpose of the research study was fully achieved.
Dunbar, G. (2005). Evaluating Research Methods in Psychology. New Jersey: John Wiley & Sons Inc. Klenke, K. (2008). Qualitative Research in the Study of Leadership. Bingley: Emarald group publishing. Sharma, A. (2005). Text Book Of Correlations And Regression. New Delhi: Discovery Publishing house. Solomon W. Golomb, G. G. (2005). Signal Design for Good Correlation. New York: Cambridge University Press. Yin, R. K. (2013). Case Research: Design and Methods. New York: SAGE Publications.