Yterzi (original) (raw)
Related papers
Power Analyse Review of Research Articles in Life Science Journals
In experimental studies, defining the suitable sample size is one of the important steps for statistical design. Power analysis is used for identifying reliability of the statistical analysis results in scientific researches. Power analysis is implemented in two different ways; in the process prior to the research by defining the suitable sample size and based on the sample size, impact size and type 1 error level for defining the statistical power level. In this study, 716 articles of last year's issues published in journals on life sciences and scanned in the Science Citation Index (SCI) and Science Citation Index Expanded (SCI-EXP.), has been reviewed under the concept of statistical methods, statistical software, sample numbers, error levels and statistical power calculation situation. As a result of the analysis, it was determined that awareness of power analysis is quite low and the number of articles which use power analysis has been found to be only one. However, it was found that statistical power is higher in the parametric tests than non-parametric tests.
International Journal of Economy, Management and Social Sciences, 2013
The purpose of this study was to measure the impact of Rate my professors.com (RMP) on college students' choices in class selection and professors. The controversial site RMP has been a social media phenomenon. Is RMP a device for disgruntled college students with a score to settle with a professor? This social media trend has had an impact on college undergraduate students 18-25. These behaviors have made popular social media such as Facebook and RMP a power tool for students' to use to connect or against individuals. As a social media tool, RMP has been used by college students to blog their comments concerning college professors' performance in the classroom. Are these blog comments valid and reliable? This study was guided by three research questions: (a) does RMP have a major influence on college students' choices of courses; (b) does RMP have an impact on students' choices of professors; (c) does RMP have an impact on future students' choices for selecting professors? This study used a principal component analysis (factor analysis) methodology. A pilot study of (N = 110) college students was taken conducted from two universities to test the instrument and data. What emerged from the factor analyses were six new factors that influenced student behavior.