Vincent Cheng 
This article conclude the study with P5(2017-2018) & P6(2018-2019) base on the previous analysis.
Foreword
- The target of this report is the students of P5(2017-2018) & P6(2018-2019).
- There is no description of the data process and source code of SAS. If you want to check, please click this link.
- Currently, there are just some simple report and diagram base on the part of statistical indicators, furthermore, some conclusion together the teacher’s opinions were attached.
- Later, if time is enough, I will add more comprehensive statistics.
- in the second part, there is cross-compared together with the students of P5(2016-2017) which are in the previous year of this statistics sample in this article. Some conclusion was attached as well.
1. Base on Different Classes in Each Grade
There are three classes in grade 5 of the academic year of 2017-2018, which contain around 72 students.
After they upgraded to P6, all students were mixed randomly and divided into three classes in grade 6 of the academic year of 2017-2018.
1.1 Class Comparision in P5 base on Mean
Conclusion:
- The mean of Class P5-1 score is distinctly higher than that both of Class P5-2 and P5-3. Compared with the other two classes, the STD(which quantify the amount of variation of a set of data values) is more stable.
- Overall, the situation of P5-3 is a little bit better than that of P5-2. But both of P5-2 and P5-3 is with a bigger STD which indicate the variation of score distribution is distinct.
- in summary, the situation in P5-1 is much better than P5-2 and P5-3, with more significant means score and more stable and uniform scores.
1.2 Class Comparision in P6 base on Mean
Conclusion:
- the mean of Class P6-1 is distinctly higher than P6-2 and P6-3, and P6-2 is distinctly higher than P6-3.
- the situation of P6-3 seems like unexpectedly low.
- STD in every term of P6-2 is higher than the other two classes. However, the means is smaller than P6-1.
2. Base on All Students performance in Each Grade
Different from the above one, the statistics in this chapter will be base on all students performance in each grade.
It will analyze the level and some statistical indicators base on all student score.
2.1 Overall Stat of P5 & P6 with box
Conclusion:
- From the first quartile of the box plot, we can see that in P6, there are more low scores around 70 than that in P5. Namely, more students get a lower score nearby 70 in P6.
- From the third quartile of the box plot, the third quartile of P6 is more near to the top score compared with that in P5. That means the variation in P6 is more significant than that in P5.
2.2 P5 Score Distribution
Conclusion:
- without seeing scores of term3, from term1 to term4, the score became better: the last bar which indicates score between 70 to 72.5 became shorter, and the total percentage of first three bar which reports score between 87.5 to 100 became more.
- score of term3 seems an exception; the overall score is distinctly lower than the other three terms. the detail reason why like this need more information to check.
2.3 P6 Score Distribution
Conclusion:
- The score of term3 is similar to that of P5, the overall score is distinctly lower than the other three terms. the detail reason why like this need more information to check.
- Dislike the situation of the other 3 term3 in P5, the score was growing up from term1 to term2 in P6. However, the first 4 bars in the term4 box shows that the amount of high score is deduced, and the mediocre score (82.5 to 87.5) is increased. The students might have the mind: this is the last term in this primary, and there is no any mandarin lesson any more, so they low their requirement to study.
2.3 P5 & P6 Score Distribution
Conclusion:
Good became better, bad became worse.
3. Base on each Student in Two Academic Years
3.1 Most unstable score
Conclusion:
There are some students whose score of 8 terms in P5 & P6 fluctuates with a distinct range. However, their mean score is not high, even lower. That means student sometimes got a high score, but sometimes score plummets, and finally, the mean score is not so high.
3.2 Most stable score
Conclusion:
good ones are always good. Worse ones remain worse.
Cross Compare Academic Year 2017-2018 and 2016-2017
1. Introduction
followed my teaching experience in this school, there are the following data in my hand:
| Grade | Academic Year |
|---|---|
| P5 | 2016-2017 |
| P5 | 2017-2018 |
| P6 | 2017-2018 |
| P6 | 2018-2019 |
Please be aware of that the students of P5(2016-2017) are the same with that of P6(2017-2018) after they stepped into a new grade.
So we can perform and compare the statistics on the same grade, but for the different academic year, maybe some outcomes will be found.
ps: I already standardize the scale on Y-axis for both figures.
2. P5 of Academic Year 2016-2017 VS P5 of Academic Year 2017-2018
2.1 Classes in P5
Conclusion:
- the variation and gap between different classes of the academic year 2017-2018 is more distinct than that of the academic year 2016-2018.
- base on what I knew, the process of mix and re-arrange from p5 to p6 is not reasonable, at least, that process doesn’t like what they said: based on random. Some teacher has the privilege to pick up the outstanding student, and some teacher doesn’t have. So that causes a significant variation between different classes.
2.2 Score distribution in P5
Conclusion:
The common situation of the academic year 2016-2017 is a little better than that of the academic year 2017-2018.
3. P6 of Academic Year 2017-2018 VS P5 of Academic Year 2018-2019
3.1 Classes in P6
Conclusion:
Same with above (what’s described in chapter 2.1)
3.2 Score distribution in P6
Conclusion:
- The situation of both figures is similar, and the gap of difference is not apparent. But as we can see(if we check them together with the figures in chapter 2.2), P6 students, no matter in the academic year 2016-2017, or the academic year 2017-2018, have less passion of study, then take the low score.
