In any research, researchers have to use scientific measures to ensure that the targeted audience accepts the outcomes. Any dissatisfaction from the audience qualifies the outcomes as invalid, thus prompting the examiners to do another research on the subject under investigation. The development of study objectives, questions, selection of the sample, collection of data, or data analysis and presentation must be appropriate to enable the researcher draw an accurate conclusion. The measures of central tendency and the descriptive statistics used in a research paper are significant in determining the validity and strengths of the conclusions. Readers can use them to assess whether they can accept the findings or use them to effect any necessary changes (Plichta, & Kelvin, 2012). This paper presents an analysis of a research paper based on the descriptive statistics and measures of central tendency used therein. The research selected is Nursing Academicians’ Attitudes towards Work, Life, and their Personality Traits by Yildirim and Çam (2012).
Yildirim and Cam (2012) conducted a study whose aim was to find out the link between the feelings held by nursing intellectuals concerning an organization or occupation and their individual behavior. The researchers had a sample size of 287 nursing academician participants who were working in 14 nursing schools that were spread over the various universities in Turkey (Yildirim & Çam, 2012). The researchers used various methods of data collection, with a number of tools being used in the data gathering process. The tools used included, “descriptive information form, job and organization-related attitude scale, and temperament and character inventory” (Yildirim, & Cam, 2012, p. 709).
In their literature review, the researchers established that the attitudes that nursing scholars held towards their work, life, and daily practices were influenced by their academic title, the social-economic status, working years, persistence, and temperament features among other characters (Yildirim, & Cam, 2012). Therefore, the researchers recommended that the appointment of nurses to academic careers should be based on their displayed features of persistence and cooperativeness among other established characteristics.
Measures of Central Tendency and Descriptive Statistics
In a Gaussian distribution of data, the measures of central tendency are useful in determining the central value (Plichta, & Kelvin, 2012). In the normal distribution curve that can be constructed from a dataset, the measures of central tendency are important in providing a value for the measurement of statistics and testing of various hypotheses. Some of the “measures of central tendency include the mode, mean, and median” (Plichta, & Kelvin, 2012, p. 711). In most of the normally disseminated statistics, these three elements have the same value. The measure of central tendency discussed in this paper is the mean, which is obtained from a dataset by dividing the summation of the data figures by the number of figures used in the set (Plichta, & Kelvin, 2012). It is given by the equation,
Within the context of this study, the research by Yildirim and Cam employed the average as its measure of central tendency. The first mean calculated was the mean age for the participating nursing academicians. This value was stated as 33.64 years with a standard deviation (SD) of 8.27 (Yildirim, & Cam, 2012). The second mean that the researchers calculated in the research was the mean total working years for the nursing academicians. This figure was found to be 12.51 years with a SD of 8.15 (Yildirim, & Cam, 2012).
Yildirim and Cam also calculated the mean of the years that the academicians had worked in the respective organizations. This figure was stated as 7.52 years with a standard deviation of 6.97 years. The researchers also calculated the means for the results from the various scales that they used in their tools, which were presented in a tabulated form. The means presented included the average for the job and organization-related attitude scale subscale (JORSS) scores and the one for the TCI scale subscale. The values were later used as the main statistics in the paper. They were put through a number of tests to assess the given hypotheses.
After the presentation of the results from the research and the appropriate data, the hypotheses were tested using a valid test. The testing of hypotheses should be done using an appropriate test for the obtained data. In addition, the descriptive statistic should be accurate enough since the conclusions depend on the obtained results (Yildirim, & Cam, 2012). In this paper, the researchers used the multiple regression analysis to evaluate the roles played by the descriptive and personality characteristics of nursing academicians in relation to the job and attitudes towards it (Yildirim, & Cam, 2012).
The researchers proceeded to calculate the respective p-values of the data obtained. The researchers weighed and used these results in the testing of the hypotheses they had developed. The tabulation of the respective values was obtained. Yildirim and Cam used the testing of the probability to see the relevance of their findings, which they wanted to use in the process of deriving a conclusion. According to Plichta and Kelvin (2012), the strength of any conclusion that a researcher makes is dependent on the calculation of the measures of central tendency and the accurate use of descriptive statistics to evaluate these measures.
The use of the mean as a measure of central tendency in the research under discussion was appropriate because the researchers wanted to test the attitudes and other factors affecting the job and individual characteristics of nursing academicians. The appropriate calculation of the descriptive statistics, as used in the research, would not have been possible if the researchers did not use the measures of central tendency that they employed in their study. Therefore, the mean enabled them find a central value that they could use in the data analysis part. The conclusions made were credible and valid since the calculations made satisfies the basic research expectations.
In any research, researchers make a number of assumptions that are crucial to research, with the examiners investigating the postulations. A good research should focus on meeting and investigating these assumptions (Plichta, & Kelvin, 2012). The hypothesis made should be clearly stated, with the researchers using the descriptive statistics and other values such as measures of central tendency to evaluate the validity of the assumptions and hypothesis. This section discusses some of the assumptions made in the research in the effort to find out if they were met or not.
Therefore, in the perspective of the paper, the assumptions made in the research in relation to the measures of central tendency used were met. The postulations included the claim that a relationship existed between personality characteristics and the attitude of nursing academicians in Turkey. The examiners also hypothesized that the association between the individual character and the mind-set of these intellectuals was positive, with the two variables affecting each other in a positive way. Yildirim and Cam (2012, p. 711) managed to establish a relationship between personal characteristics and job attitudes for the research population. They also managed to show a positive relationship between the attitudes of the academicians and their jobs (Yildirim, & Cam, 2012). Therefore, the researchers met the assumptions of their work, especially in relation to the measure of central tendency discussed.
The assumptions in the calculation of the mean as a measure of central tendency made in the research also included the claim that the data obtained was from a sample and not the entire population, and hence the use of (n-1) in the calculation. The researchers also assumed that the data was obtained from a normal distribution. These assumptions were met since the data obtained from a sample was described prior to the calculation (Yildirim, & Cam, 2012). Yildirim and Cam also explained that the data was from a normal distribution and hence the ease of calculating the mean, which they were able to obtain, as a measure of central tendency in their research (2012, p. 711).
Levels of Measurement
The levels of measurement in the statistical analysis developed by Stanley Smith Stevens arise from his theory of scale types (Plichta, & Kelvin, 2012). These include the nominal, ordinal, interval, and ratio types (Plichta, & Kelvin, 2012). The use of median in the nominal scale was not appropriate as a measure of central tendency. However, the use of the mode and mean were appropriate (Plichta, & Kelvin, 2012). The use of the average in the ordinal degree was not appropriate. Researchers can combine these methods in their research work to provide the best method for them to assess their hypotheses.
In the research by Yildirim and Cam, both of the above scale types were applied. The mean was calculated from the nominal data (Yildirim & Cam, 2012). The nominal data obtained in the research was the ages of the participants whose mean ages were calculated. The scales used in the research also provided nominal data, which allowed room for the calculation of the means (Yildirim, & Cam, 2012). These levels of measurement were appropriate for the research. Besides, they were crucial in the conclusions made. An evaluation also showed that they were accurate.
Data Presentation Methods
The methods used to present data in any research are important since they can be used to assess the research findings. The type of data obtained determines the methods of presentation that are appropriate for use (Plichta, & Kelvin, 2012). The presentation methods have their weaknesses and strengths. Therefore, researchers have the choice of using these methods to display their data. In the research discussed above, the researchers did not use graphs, charts, or figures to present their research data findings. However, they used three tables to present the results. The three tables used displayed the data on the job and organization-related attitude scale–subscale mean scores, the temperament and character inventory (TCI) scale–subscale mean scores, and job and organization-related attitude scale evaluation results for the nursing academicians (Yildirim, & Cam, 2012).
The strengths of data presentation, which is the use of tables that are used in the research, include the ease in making conclusions for the readers. Tables provide and efficient way of data presentation in the research since the types of data obtained can be displayed through this method. The other strength of using tables to present data obtained from the research is that they provide a visual representation of the means besides allowing readers to access it easily. The results are easily interpreted using the data available in the tables. This claim is the other strength of data presentation using tabulation.
However, there are a number of weaknesses in the use of data presentation as done in the research. The researchers used only one form of data presentation method. This strategy did not give the reader a good mental picture in the interpretation of the results. Although the tables are visually appealing, the use of graphs, figures, and charts would have made the research more visually appealing and interesting to read. The tables are also not adequate to show the differences in the various values.
Based on the detailed analysis made in the paper, it is evident that the research discussed above applied the mean as a basic measure of central tendency. The researchers were able to calculate the mean from the data that they obtained. This value helped them in the calculation of the descriptive statistic, which contributed in the making of a valid conclusion. The assumptions made in the measure of central tendency were met. The researchers used tables as the sole method of data presentation. This choice may not have been visually appealing. However, the research is valid. Besides, the conclusions made are also valid and related to the data obtained.
Plichta, B., & Kelvin, A. (2012). Munro’s statistical methods for health care research. Philadelphia: Wolters Kluwer Health/Lippincott Williams & Wilkins.
Yildirim, S., & Çam, O. (2012). Nursing academicians’ attitudes towards work life and their personality traits. Journal of Psychiatric and Mental Health Nursing, 19(1), 709–714.