This is an instruction of the course of Research Methods in Psychology: Design and Technology by Tao Xin from Collaborative Innovation Center of Assessment for Basic Education Quality of Beijing Normal University.
Teacher
The teacher Tao Xin, a professor in Collaborative Innovation Center of Assessment for Basic Education Quality whose research field is psychological and educational assessment, served as the instructor of this course. Pro. Xin features his low voice in the course so if you really want to listen carefully to what he says, be sure to get up early and find the seats near him.
Textbook
- McClelland, G. H., Ryan, C. S., Judd, C. M. (2017). Data Analysis: A Model Comparison Approach To Regression, ANOVA, and Beyond, Third Edition. (n.p.): Taylor & Francis.
The textbook written by Tao Xin is not recommended, for it is purely the translation version of the original textbook(if you check it in the flesh, you will arrive the same conclusion). Many georgous accounts, however, were excluded from Xin’s book, making it difficult to understand. Luckily, the original book is pretty suitable to read.
- Kabacoff, R. (2015). R in action: Data analysis and graphics with r. Manning.
I use R to do the statistics work, so a tutorial over R is required and this book is a bible for R.
Assignments
There are 5 assignments.
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结合个人研究方向，在国际SCI或SSCI刊物 上检索一篇英文学术论文，完成以下任务:
(1) 对该论文进行概要小结
(2)提出值得研究的问题和研究假设
(3) 给出研究设计
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Simple Regression
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Multiple Regression with Continuous Variables
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Oulier
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One-way ANOVA
The assignment is not hard. I upload my assignments, answers given by teacher, slides and some materials that may help you pass the exam.
If you want to run my code on your device, be sure to modify the path of the data files located in your computer.
Here is a quick look of my assignment. I don’t guarantee the accuracy of it.
Other Suggestions
- Learn at least a statical analysis software, say, R, SPSS and Matlab. R is my top priority for its little size and dynamic community. All you have to do to utilize a new package is to execute a command
install.packages(). R also enjoys a gorgeous graphical package,ggplot2, which can export wonderful statistical graphics and is easy to use. - Read the original text book.
- Don’t rely too much on the course and count on it to solve your statical problems. You should figure out what is the exact statistical tools you need to finish your scientific work and try your best to learn them.