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The project is focused on the analysis of data to determine the association between study hours and grades in an educational facility. Such techniques as correlation and regression were selected because they have proven to be effective, and are often utilized in such studies (Chatterjee & Hadi, 2015). Analysis of the data suggests that a positive relationship between these two variables is present, and it is 0,684. A coefficient of determination is 0,468, and y(x)=5,659x+51,888. Such results are statistically significant and indicate a close association. The findings suggest that educators should provide information regarding such connections to ensure that students are aware of possible consequences. Additional research on this subject matter and it would be beneficial to explore the influence of other factors on grades.
It is imperative to mention that correlation and regression are efficient analysis methods that are commonly used by researchers to determine associations between particular variables. The second one is obtained from the first one, and it helps to determine the value (Linear regression analysis, 2012). It would be reasonable to utilize the approach to improve the process of education. The hypothesis is that study hours have an influence on test results, and a positive correlation is expected. The research topic is quite important because many educational facilities are trying to minimize unnecessary expenses.
Several peer-reviewed articles and books on this topic were examined to get a better understanding of the subject matter. One of the studies suggests that the 0,11 correlation coefficient between these variables is present (Harrington, 2012).
However, research design plays a critical role, and participants were from different fields in this case. Therefore, it needs to be modified to avoid possible errors and increase the reliability of the received results. Microsoft Word will be used as a primary analysis instrument. Twenty students were selected to participate in the study. All of them have similar grades for the math course and have an outstanding knowledge of the subject.
They were not informed about the purpose of the research to avoid bias. All of them utilized suggested course books and websites on the topic. A standard test that is commonly used was chosen in this case, and the time limit was thirty minutes. The highest possible score is one hundred points. Participants were interviewed after the process, and questions regarding the time for preparation were asked. The data related to students’ marks were collected and put into Microsoft Excel spreadsheets for further analysis (Salkind, 2012).
The results of the interview show that three students have prepared for one hour, six individuals needed two. Four participants studied four three hours, five for two, and the rest stated that it was close to five. The outcome is quite intriguing and should be discussed. Students in the last group have shown the best results as a whole (see Table 1).
|Number of Students||Study Time, Hours||Results, Points|
Table 1. Test outcomes.
The data were analyzed with the use of an appropriate function, and it was determined that a correlation coefficient is 0,684. A graph was built with the use of Microsoft Excel, and it highlights a positive relationship (see Figure 1).
Such findings are fascinating because they shown than the impact of the time spent studying on the grade is enormous. On the other hand, it can be seen that some of the students needed only two to three hours to get outstanding results.
However, the dissimilarity between the results achieved by the first and the last group is rather significant. Linear regression coefficients are 5,659 and 51,88. R² suggests that 46,8 percents of the first variable are dependent on the second. Such a number is rather low but still supports the hypothesis. However, limitations also should be acknowledged. For example, a student can be distracted during the process, or other complications could also occur.
Moreover, some individuals could have an overall better understanding of the subject than others. Another aspect that must be considered is that only the results of a single test were examined, and selective sampling also could be quite problematic. The sample size is also relatively small, and it may be reasonable to conduct additional studies (Ryan, 2013).
In summary, it is possible to state that a positive correlation between the preparation time and test score is present. It is necessary to mention that such findings are not surprising, but they are still incredibly important. They signify that students should devote much more attention to studying, and should not be overconfident in their abilities. It is quite evident that additional time spent on the process of preparation has an enormous impact on the outcome in most cases.
The study has shown that some of the students received higher marks on the test regardless of studying, but a particular trend still can be identified. Such data is incredibly valuable and should be analyzed to determine an appropriate time that an average student would need to get satisfactory grades on a subject. It is not an easy task to determine the relationship between these two variables because they are influenced by numerous internal and external factors. It is impossible to state that such a trend will be present in all situations. The problem is that the difference between the subjects and assessment methods utilized by most professors is tremendous.
It is necessary to understand that the process of studying is also affected by numerous internal and external factors. For instance, one individual may require much more time to get a better understanding of a particular topic. Therefore, it would be reasonable to conduct additional studies to determine variables that could have affected the results. It is quite evident that the project has several limitations.
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Only time spent studying and grades received were analyzed, and additional information is required to determine an appropriate relationship. Also, the study only examines one subject, and an enormous difference between the approaches utilized by some professors is present. Psychological aspects also play a critical role most of the time and the correlation between study time and anxiety need to be examined.
All the data received may be combined to determine appropriate preparation time, and such recommendations could improve grades as a whole. The reduction in study hours may lead to other severe consequences. For instance, individuals are more likely to drop out (Ascione & Bramley, 2013). It would be reasonable to apply statistics in this case because it may help to improve the educational system and increase the number of positive outcomes. The strategies would be much more reliable if they were based on evidence and research.
Ascione, J., & Bramley, N. (2013). Reducing teaching hours in tertiary Japanese: a case study. Bebel, 47(2), 24-29.
Chatterjee, S., & Hadi, A. S. (2015). Regression analysis by example (4th ed.). New York, NY: John Wiley & Sons.
Harrington, C. (2012). Student success in college. Boston, MA: Cengage Learning.
Linear regression analysis. (2012). Web.
Ryan, T. P. (2013). Sample size determination and power. New York, NY: John Wiley & Sons.
Salkind, N. J. (2012). Excel statistics: A quick guide (2nd ed.). New York, NY: SAGE Publications.