許多心理學課程都要求學生們設計實驗、撰寫實 驗報告或研究報告。這本由彼得·哈裡斯著的《心理 學實驗的設計與報告(英文版第3版)》旨在為撰寫實 驗報告和設計實驗提供具體的指導。 本書共分兩編，第一編圍繞如何撰寫實驗報告而 展開，詳略得當地介紹了報告的每個主要組成部分， 指出了各部分在撰寫中應該注意的問題，並根據最新 版的《APA論文寫作與發表規範》，提供了相應的實 驗示例。第二編是關於實驗設計與統計方法的內容。 就心理學研究中經常采用的幾種實驗設計方法以及相 關的統計方法做出了概要的介紹和評價，介紹了學生 在日常學習中容易忽視，但卻非常重要的兩個概念： 效力和效應大小；同時對報告中如何呈現圖、表的問 題進行了具體說明。 《心理學實驗的設計與報告》(第3版)與前兩版 相比，在每一章都增加了新的小節，補充了新的內容 ，使內容更加豐富詳實，更具操作性和指導性。 本書既可作為心理學、教育學等社會科學研究專 業的學生的教科書，也可作為研究人員在設計實驗和 撰寫研究報告時的參考書。

　彼得·哈裡斯（Peter Harris），獲倫敦大學心理學博士學位，現為英國謝菲爾德大學心理學繫的高級講師。他曾先後任職薩賽克斯大學、赫特福德大學和諾丁漢大學，也曾在阿姆斯特丹大學和牛津大學做過訪問學者。他主要的研究方向是社會和健康心理學。

Contents of the Web site
Preface
To students
How to use this book
To tutors
Part 1 Writing reports
1 Getting started
1.1 Experienced students, inexperienced students,
and the report
1.2 Writing the report
1.3 The importance of references in text
1.4 The practical report and the research paper
1.5 Finding references for your INTRODUCTION
1.5.1 How to structure your reading and what
to look for
1.5.2 Generating potential references
1.5.3 Locating the references
1.5.4 Rubbish and temptation on the Internet
1.6 Ethics
1.7 The rest of the book and the book's Web site
2 The INTRODUCTION section
2.1 The first part of the INTRODUCTION: reviewing the
background to your study
2.2 Inexperienced students, experienced students,
and the INTRODUCTION
2.3 Your own study
3 The METHOD section
3.1 The DESIGN subsection
3.2 The PARTICIPANTS subsection
3.3 The APPARATUS or MATERIALS subsection
3.4 The PROCEDURE subsection
3.5 Interacting with and instructing participants
3.6 Optional additional subsections of the METHOD
3.6.1 Pilot test
3.6.2 Ethical issues
3.6.3 Statistical power
3.7 Writing a METHOD when your study is not
an experiment
4 The RESULTS section
4.1 Describing the data: descriptive statistics
4.2 Analysing the data: inferential statistics
4.3 An example RESULTS section
4.4 Nine tips to help you avoid common mistakes in
your RESULTS section
4.5 Rejecting or not rejecting the null hypothesis
4.6 Reporting specific statistics
4.6.1 Chi-square, Z2
4.6.2 Spearman rank correlation coefficient (rho), rs
4.6.3 Pearson's product moment correlation
coefficient, r
4.6.4 Mann-Whitney U test, U
4.6.5 Wilcoxon's Matched-Pairs Signed-Ranks Test, T
4.6.6 Kruskal-Wallis one-way analysis of variance, H
4.6.7 Friedman's ANOVA, ;(2r
4.6.8 The independent t test, t
4.6.9 The related t test, t
4.6.10 Analysis of variance (ANOVA), F
4.6.11 Four tips to help you avoid common mistakes
when reporting ANOVA
4.6.12 Linear regression
4.6.13 Statistics of effect size
4.7 What you can find on the book's Web site
4.8 What you can find in the statistics textbooks
paired with this book
5 The DISCUSSION section
5.1 How well do the findings fit the predictions?
5.2 What do the findings mean?
5.3 What are the implications of these findings?
5.4 What to do when you have been unable to
analyse your data properly
5.5 External validity: the generalizability of findings
5.6 Six tips to help you to avoid some common
failings in the DISCUSSION
5.7 Two example DISCUSSION sections
5.7.1 The cheese and nightmare experiment
5.7.2 The mnemonic experiment
5.8 Writing a DISCUSSION when your study is not
an experiment
6 The TITLE and ABSTRACT
6.1 The TITLE
6.2 The ABSTRACT
7 REFERENCES and APPENDICES
7.1 The REFERENCES section
7.2 General rules for the REVERENCES section
7.3 An example REFERENCES section
7.4 Key to the example REFERENCES section
7.5 Electronic references
7.5.1 Published material obtained electronically
7.5.2 Unpublished material obtained electronically
7.6 Appendices
8 Producing the final version of the report
8.1 Writing style
8.2 Definitions and abbreviations
8.3 References in the text
8.3.1 Using et al. properly
8.3.2 Quotations and plagiarism
8.4 Tables and figures
8.5 Graphing data
8.5.1 One IV with two levels
8.5.2 Error bars
8.5.3 One IV with more than two levels
8.5.4 More than one IV
8.5.5 Tips to help you produce better graphs
8.6 Drafting the report
8.7 Producing the final version
Check list for report writing
What the marker is looking for
Mistakes to avoid
Part 2 Design and statistics
9 Experiments, correlation and description
9.1 Experimenting
9.1.1 The experiment
9.1.2 Experimental and control conditions
9.1.3 Control: eliminating confounding variables
9.1.4 Experimental and null hypotheses
9.1.5 More on controlling variables
9.2 Correlation
9.3 Description
Consolidating your learning
10 Basic experimental design
10.1 Unrelated and related samples independent
variables
10.2 Other names for unrelated and related samples
independent variables
10.3 Deciding whether to use related or unrelated
samples
10.4 Related samples
10.4.1 Advantages
10.4.2 Disadvantages
10.4.3 Controlling for order effects
10.5 Principal alternatives to related samples
10.6 Unrelated samples
10.6.1 Advantages
10.6.2 Disadvantages
10.6.3 Ways around these disadvantages
10.7 Matching participants
10.8 External validity
10.9 Internal validity
10.10 Ethics: The self-esteem and well-being of
your participants
10.10.1 Informed consent
10.10.2 Debriefing your participants
10.10.3 Studies on the Internet
10.10.4 Data confidentiality
Consolidating your learning
11 Statistics: significance testing
11.1 Inferential statistics
11.2 Testing for statistical significance
11.3 Type I and type II errors
11.4 Choosing a statistical test
11.5 Two-tailed and one-tailed tests
11.6 Testing for statistical significance: summary of the
procedure
Consolidating your learning
12 Statistics: effect size and power
12.1 Effect size
12.2 Power
12.2.1 Estimating power
12.2.2 Increasing the power of our experiments
12.3 Effect size and power: reporting and interpreting
findings
12.3.1 Reporting for those who do not know how to
calculate power or effect size statistics
12.3.2 Reporting for those who have been taught how to
calculate power or effect size statistics
Consolidating your learning
13 More advanced experimental design
13.1 Extending the number of levels on the
independent variable
13.1.1 Unrelated samples IVs
13.1.2 Related samples IVs
13.2 Experimental designs with two or more independent
variables
13.3 Labelling designs that have two or more independent
variables
13.4 Main effects of independent variables
13.5 Statistical interactions
13.6 Analysing designs involving two or more IVs
13.7 Graphing statistical interactions
13.8 Watch out for "IVs" that are not true independent
variables
13.9 Some tips to help you to design better experiments
and write better reports
13.9.1 The basic rule
13.9.2 Getting reliable measures of the dependent variable
13.9.3 Pilot testing
13.9.4 The post-experimental interview
13.9.5 Check and screen your data prior to statistical
analysis
13.10 Above all, randomize properly
Consolidating your learning
Commentary
Recommended reading
Appendix 1: Confusing predictions from the null hypothesis with those
from the experimental hypothesis
Appendix 2: Randomizing
Appendix 3: How to use tables of critical values of inferential statistics
Answers to SAQs
Answers to diagnostic questions
References
Index of concepts