Testing and Regression Analysis of Long-Term Relationships 长期关系的测试与回归分析
2024 S2 2024 年第二季度
Tony Shang | Discipline of Business Analytics 托尼·商 | 商业分析学科
1 Context 1 上下文
Long-term relationships are influenced by various factors that contribute to both satisfaction and longevity. Elements such as communication patterns, shared interests, and conflict resolution skills play key roles in shaping the dynamics of a relationship. In today’s data-driven world, applying statistical analysis to relationship data allows us to uncover patterns and insights that can inform our understanding of what contributes to successful, lasting relationships. 长期关系受到多种因素的影响,这些因素有助于满意度和持久性。沟通模式、共同兴趣和冲突解决技能等要素在塑造关系的动态中发挥着关键作用。在当今数据驱动的世界中,对关系数据应用统计分析使我们能够发现模式和洞察,从而帮助我们理解什么因素有助于成功和持久的关系。
In this assignment, you will explore key relationship factors using advanced statistical techniques, including hypothesis testing and regression analysis. By analysing realworld relationship variables, you will gain valuable insights into which factors significantly impact relationship satisfaction and longevity. The assignment will challenge you to apply your knowledge of hypothesis testing for the means, build and refine regression models, and assess the significance and fit of your models. 在本次作业中,您将使用高级统计技术探索关键关系因素,包括假设检验和回归分析。通过分析现实世界中的关系变量,您将获得有关哪些因素显著影响关系满意度和持久性的宝贵见解。该作业将挑战您应用均值的假设检验知识,构建和完善回归模型,并评估模型的显著性和拟合度。
2 Data Introduction 2 数据介绍
Data is stored in the excel data file “QBUS5001_GROUP ASSIGNMENT DATA_2024_S2.xlsx”. 数据存储在 Excel 数据文件“QBUS5001_GROUP ASSIGNMENT DATA_2024_S2.xlsx”中。
The dataset provided for this assignment contains information on 300 couples, capturing various aspects of their relationships. Key variables include the number of years together, age differences, daily communication time, number of shared hobbies, compatibility in love languages, and conflict resolution skills. Additionally, the dataset includes each couple’s self-reported satisfaction score and whether they have passed the 7-year relationship mark. 本次作业提供的数据集包含 300 对情侣的信息,捕捉了他们关系的各个方面。关键变量包括在一起的年数、年龄差异、每日沟通时间、共同爱好的数量、爱情语言的兼容性以及冲突解决技能。此外,数据集还包括每对情侣自我报告的满意度评分以及他们是否已超过 7 年的关系期限。
Here is a list of variables in the excel data file: 以下是 Excel 数据文件中的变量列表:
Variable Name 变量名称
Description 描述
CoupleID
Unique identifier for each couple. 每对情侣的唯一标识符。
Years_Together 多年来
Difference in age between the two partners (in years). 两位合伙人之间的年龄差(以年为单位)。
Difference in age between the two partners (in years).| Difference in age between the two partners (in years). |
| :--- |
Age_Gap 年龄差距
夫妻每天沟通的平均时间(以分钟计)。
Average time the couple spends communicating daily
(in minutes).
Average time the couple spends communicating daily
(in minutes).| Average time the couple spends communicating daily |
| :--- |
| (in minutes). |
Communication_Time 沟通时间
Shared_Hobbies 共享爱好
夫妻共同享受的爱好或活动的数量。
The number of hobbies or activities the couple enjoys
together.
The number of hobbies or activities the couple enjoys
together.| The number of hobbies or activities the couple enjoys |
| :--- |
| together. |
Love_Language_Match 爱_语言_匹配
夫妻的爱情语言是否匹配(1 = 是, 0=0= 否)。
Whether or not the couple's love languages match (1 =
yes, 0=0= no).
Whether or not the couple's love languages match (1 =
yes, 0= no).| Whether or not the couple's love languages match (1 = |
| :--- |
| yes, $0=$ no). |
Conflict_Resolution 冲突解决
夫妻处理冲突的能力,评分范围为 1(差)到 5(优秀)。
How well the couple handles conflict, rated on a scale
from 1 (poor) to 5 (great).
How well the couple handles conflict, rated on a scale
from 1 (poor) to 5 (great).| How well the couple handles conflict, rated on a scale |
| :--- |
| from 1 (poor) to 5 (great). |
Satisfaction_Score 满意度评分
自我报告的关系满意度评分,范围从 1 到 10。
Self-reported relationship satisfaction score, on a scale
from 1 to 10.
Self-reported relationship satisfaction score, on a scale
from 1 to 10.| Self-reported relationship satisfaction score, on a scale |
| :--- |
| from 1 to 10. |
Post_7_Year_Itch 后_7 年之痒
该夫妇是否在一起超过 7 年(1 = 是,0 = 否)。
Whether the couple has been together for more than 7
years (1 = yes, 0 = no).
Whether the couple has been together for more than 7
years (1 = yes, 0 = no).| Whether the couple has been together for more than 7 |
| :--- |
| years (1 = yes, 0 = no). |
Variable Name Description
CoupleID Unique identifier for each couple.
Years_Together "Difference in age between the two partners (in years)."
Age_Gap "Average time the couple spends communicating daily
(in minutes)."
Communication_Time
Shared_Hobbies "The number of hobbies or activities the couple enjoys
together."
Love_Language_Match "Whether or not the couple's love languages match (1 =
yes, 0= no)."
Conflict_Resolution "How well the couple handles conflict, rated on a scale
from 1 (poor) to 5 (great)."
Satisfaction_Score "Self-reported relationship satisfaction score, on a scale
from 1 to 10."
Post_7_Year_Itch "Whether the couple has been together for more than 7
years (1 = yes, 0 = no)."| Variable Name | Description |
| :--- | :--- |
| CoupleID | Unique identifier for each couple. |
| Years_Together | Difference in age between the two partners (in years). |
| Age_Gap | Average time the couple spends communicating daily <br> (in minutes). |
| Communication_Time | |
| Shared_Hobbies | The number of hobbies or activities the couple enjoys <br> together. |
| Love_Language_Match | Whether or not the couple's love languages match (1 = <br> yes, $0=$ no). |
| Conflict_Resolution | How well the couple handles conflict, rated on a scale <br> from 1 (poor) to 5 (great). |
| Satisfaction_Score | Self-reported relationship satisfaction score, on a scale <br> from 1 to 10. |
| Post_7_Year_Itch | Whether the couple has been together for more than 7 <br> years (1 = yes, 0 = no). |
3 Tasks 3 个任务
In this assignment, you will complete two major tasks using statistical analysis. Each task will require you to apply the concepts of hypothesis testing and regression analysis to explore the dynamics of long-term relationships. 在本次作业中,您将使用统计分析完成两个主要任务。每个任务都将要求您应用假设检验和回归分析的概念,以探索长期关系的动态。
Task 1: Hypothesis Testing on the "7-Year Itch" 任务 1:关于“七年之痒”的假设检验
You will investigate whether there is a significant difference in average relationship satisfaction between couples who have been together for more than 7 years and those who have been together for fewer than 7 years. This test will help determine whether the “7-year itch” phenomenon-where couples may experience dissatisfaction after 7 years-is supported by the data. 您将调查在一起超过 7 年的情侣与在一起不足 7 年的情侣之间的平均关系满意度是否存在显著差异。此测试将帮助确定“七年之痒”现象——情侣在 7 年后可能会感到不满——是否得到了数据的支持。
Strategies 策略
Determine and justify the appropriate t-test: Decide whether to use an equal variance tt-test or unequal variance tt-test based on the characteristics of the data. Provide a clear justification for your choice. 确定并证明适当的 t 检验:根据数据的特征决定使用等方差 tt -检验还是不等方差 tt -检验。为您的选择提供明确的理由。
Formulate your hypotheses: Properly set up your null and alternative hypotheses, ensuring they are aligned with the research question. 制定你的假设:正确设定你的零假设和备择假设,确保它们与研究问题一致。
Conduct a comprehensive hypothesis test: Perform a full hypothesis test by: 进行全面的假设检验:通过以下方式进行完整的假设检验:
Stating the test statistic and any necessary assumptions or decisions related to the test. 陈述检验统计量及与检验相关的任何必要假设或决策。
Using both the rejection region approach and the p\mathbf{p}-value approach to define your decision rule. 使用拒绝区域方法和 p\mathbf{p} -值方法来定义您的决策规则。
Drawing your final conclusions based on the results of your hypothesis test. 根据假设检验的结果得出最终结论。
Reflect on the results: Discuss whether the test outcome aligns with your expectations. If the result is unexpected, explore possible reasons why this might have occurred. 反思结果:讨论测试结果是否符合您的预期。如果结果出乎意料,请探讨可能导致这种情况的原因。
Task 2: Multiple Linear Regression Analysis 任务 2:多元线性回归分析
For this task, you are free to select your own dependent and independent variables from the dataset to perform a multiple linear regression analysis. Your goal is to explore factors that might influence relationship satisfaction, relationship longevity, or any other relevant dependent variable you choose. 对于此任务,您可以自由选择数据集中自己的因变量和自变量,以进行多元线性回归分析。您的目标是探索可能影响关系满意度、关系持久性或您选择的任何其他相关因变量的因素。
Strategies 策略
Correlation Analysis: Start by analysing the correlation between variables in the dataset to identify potential relationships. 相关性分析:首先分析数据集中变量之间的相关性,以识别潜在关系。
Model Building: Select your dependent and independent variables. Build a multiple linear regression model with ALL independent variables and estimate the regression coefficients. 模型构建:选择您的因变量和自变量。构建一个包含所有自变量的多元线性回归模型,并估计回归系数。
Model Refinement: Justify your variable selection and exclude insignificant variables and inappropriate variables as necessary to improve the model. 模型优化:合理化您的变量选择,并根据需要排除不显著变量和不适当变量,以改善模型。
Hypothesis Testing: Test the significance of individual coefficients (using t-tests) and the overall model (using an F-test). 假设检验:检验个别系数的显著性(使用 t 检验)和整体模型的显著性(使用 F 检验)。
Model Evaluation: Assess the fit of your model by looking at R^(2)R^{2} and Adjusted R^(2)\mathrm{R}^{2}. Evaluate whether your model meets regression assumptions, including linearity, homoscedasticity, normality of residuals, and multicollinearity. 模型评估:通过查看 R^(2)R^{2} 和调整后的 R^(2)\mathrm{R}^{2} 来评估模型的拟合度。评估您的模型是否满足回归假设,包括线性、同方差性、残差的正态性和多重共线性。
Interpret Results: Provide a thorough interpretation of your findings, including the significance of each variable and the overall strength of your model. 解释结果:对您的发现进行全面解释,包括每个变量的重要性和模型的整体强度。
Draw a Conclusion Based on Context: Finally, draw a conclusion based on the context of the problem. Explain the practical implications of your findings and how they relate to the factors influencing longterm relationships. 根据上下文得出结论:最后,根据问题的上下文得出结论。解释您的发现的实际意义以及它们与影响长期关系的因素之间的关系。
4 Instructions for Writing the Report 撰写报告的 4 条指示
A report template file, “QBUS5001_Report Template.docx”, is provided for your use. You are required to write a professional report of no more than 1,000 words. The main body of the report should focus on presenting your results and discussions. All calculations, Excel outputs, and some unnecessary charts should be included in the Appendices, and they will not count towards the word limit. For example, if you performed an F-test for equal variances, you should create an appendix titled “Appendix 1 - F-test for Equal Variances”, attach an Excel output and your calculation of the two-tailed p-value, and refer to it in the report by stating “See Appendix 1.” 提供了一个报告模板文件“QBUS5001_Report Template.docx”供您使用。您需要撰写一份不超过 1000 字的专业报告。报告的主体应重点展示您的结果和讨论。所有计算、Excel 输出以及一些不必要的图表应包含在附录中,这些内容不计入字数限制。例如,如果您进行了方差齐性检验的 F 检验,您应创建一个标题为“附录 1 - 方差齐性检验的 F 检验”的附录,附上 Excel 输出和您计算的双尾 p 值,并在报告中提到“见附录 1”。
Report Structure 报告结构
Title Page (Not included in the word count) 标题页(不计入字数)
List the course name (QBUS5001) and assignment title. 列出课程名称(QBUS5001)和作业标题。
Include a concise, informative title for the report. 包含一份简明扼要、信息丰富的报告标题。
Include the student ID of all group members. 包括所有小组成员的学生 ID。
Provide a brief overview of the report. 提供报告的简要概述。
Summarise the key findings from both the hypothesis testing and regression analysis. 总结假设检验和回归分析的关键发现。
Highlight main conclusions without technical details. 突出主要结论,无需技术细节。
Introduction (150-200 words): 引言(150-200 字):
Briefly describe the dataset and the key variables being analysed. 简要描述数据集及正在分析的关键变量。
Explain the goal of each task (hypothesis testing on the 7-year itch, regression analysis). 解释每个任务的目标(关于七年之痒的假设检验,回归分析)。
Hypothesis Testing on the "7-Year Itch" (200-250 words): 假设检验“七年之痒”(200-250 字):
Formulate Hypotheses: Clearly state the null and alternative hypotheses. 制定假设:清楚地陈述零假设和备择假设。
Justify Test Selection: Decide whether to use an equal or unequal variance t-test and explain why. 选择测试的理由:决定是使用等方差 t 检验还是不等方差 t 检验,并解释原因。
Perform the Hypothesis Test: Include test statistics, p-values, and decision rules (both rejection region and p-value approaches). 进行假设检验:包括检验统计量、p 值和决策规则(拒绝域和 p 值方法)。
Draw Conclusions: Explain the outcome of the test in relation to the “7-year itch.” 得出结论:解释测试结果与“七年之痒”的关系。
Multiple Linear Regression Analysis (350-450 words): 多元线性回归分析(350-450 字):
Correlation Analysis: Discuss the correlation between the variables and the rationale for choosing your dependent and independent variables. 相关性分析:讨论变量之间的相关性以及选择因变量和自变量的理由。
Model Building: Explain the initial model and any refinements made, such as removing insignificant variables. 模型构建:解释初始模型及所做的任何改进,例如去除不显著的变量。
Hypothesis Testing for Coefficients: Conduct t-tests for the significance of the variables and the F-test for the overall model. 系数的假设检验:对变量的显著性进行 t 检验,对整体模型进行 F 检验。
Model Evaluation: Report R ^(2){ }^{2} and Adjusted R^(2)\mathrm{R}^{2} and evaluate the overall model fit. 模型评估:报告 R ^(2){ }^{2} 和调整后的 R^(2)\mathrm{R}^{2} ,并评估整体模型拟合度。
Test Regression Assumptions: Verify linearity, normality, homoscedasticity, and multicollinearity. 测试回归假设:验证线性、正态性、同方差性和多重共线性。
Draw a Conclusion: Provide a practical interpretation of your results in the context of the problem. 得出结论:在问题的背景下对您的结果提供一个实际的解释。
Conclusion (100-150 words): 结论(100-150 字):
Summarise the key findings from both tasks. 总结两个任务的关键发现。
Reflect on any unexpected results or limitations in your analysis. 反思您分析中任何意外结果或局限性。
Suggest possible areas for further research or improvements. 建议进一步研究或改进的可能领域。
Reference (Not included in the word count) 参考(不计入字数)
If you conducted your own research, ensure that you cite it using APA 7th edition format. 如果您进行了自己的研究,请确保使用 APA 第七版格式引用。
Appendices (Charts, Tables, and Excel outputs; not included in the word count): 附录(图表、表格和 Excel 输出;不计入字数):
Include relevant charts, tables, Excel output, or figures that support your analysis. 包括支持您分析的相关图表、表格、Excel 输出或数据。
Refer to these in the main body of the report. 在报告的主体中参考这些。
5 Marking Rubric 5 评分标准
Tony knows you well! I completely understand that you’re looking for a clear structure on how to achieve an HD in this assignment, so here’s a detailed marking rubric to guide you! 托尼对你很了解!我完全理解你在寻找一个清晰的结构,以便在这个作业中获得高分,所以这里有一个详细的评分标准来指导你!
Marking Rubric for QBUS5001 Group Assignment (Total: 60 marks) QBUS5001 小组作业评分标准(总分:60 分)
1. Report Quality and Professionalism (20 marks) 报告质量与专业性(20 分)
Criteria 标准
Marks 标记
Description 描述
Executive Summary 执行摘要
2 marks 2 分
清晰、简洁,并提供了关键发现和方法论的强有力概述。
Clear, concise, and provides a strong
overview of the key findings and
methodology.
Clear, concise, and provides a strong
overview of the key findings and
methodology.| Clear, concise, and provides a strong |
| :--- |
| overview of the key findings and |
| methodology. |
Introduction 介绍
2 marks 2 分
清楚地介绍了问题、简要的数据描述和分析的目标。
Clearly introduces the problem, a brief data
description, and objectives of the analysis.
Clearly introduces the problem, a brief data
description, and objectives of the analysis.| Clearly introduces the problem, a brief data |
| :--- |
| description, and objectives of the analysis. |
Conclusion 结论
2 marks 2 分
有效总结了研究结果,并与分析的目标相联系。
Summarises the findings effectively and
connects back to the objectives of the
analysis.
Summarises the findings effectively and
connects back to the objectives of the
analysis.| Summarises the findings effectively and |
| :--- |
| connects back to the objectives of the |
| analysis. |
Structure and 结构和
4 marks 4 分
适当使用附录,所有附录在报告中组织良好并正确引用。
Proper use of appendices and all
appendices are well-organised and
correctly cited in the report.
Proper use of appendices and all
appendices are well-organised and
correctly cited in the report.| Proper use of appendices and all |
| :--- |
| appendices are well-organised and |
| correctly cited in the report. |
Presentation 演示文稿
4 marks 4 分
报告结构合理,专业呈现,逻辑顺序清晰。所有图表和表格应适当标注。
Report is well-structured, professionally
presented, and follows logical order. All
charts and tables should be appropriately
labelled
Report is well-structured, professionally
presented, and follows logical order. All
charts and tables should be appropriately
labelled| Report is well-structured, professionally |
| :--- |
| presented, and follows logical order. All |
| charts and tables should be appropriately |
| labelled |
Mathematical Notations 数学符号
4 marks 4 分
在整个报告中正确使用数学符号和符号。
Correct use of mathematical notations and
symbols throughout the report.
Correct use of mathematical notations and
symbols throughout the report.| Correct use of mathematical notations and |
| :--- |
| symbols throughout the report. |
Overall Cohesiveness 整体凝聚力
2 marks 2 分
报告流畅,各部分之间过渡清晰;讨论和展示紧密结合。
Report flows well with clear transitions
between sections; cohesive discussion and
presentation.
Report flows well with clear transitions
between sections; cohesive discussion and
presentation.| Report flows well with clear transitions |
| :--- |
| between sections; cohesive discussion and |
| presentation. |
Criteria Marks Description
Executive Summary 2 marks "Clear, concise, and provides a strong
overview of the key findings and
methodology."
Introduction 2 marks "Clearly introduces the problem, a brief data
description, and objectives of the analysis."
Conclusion 2 marks "Summarises the findings effectively and
connects back to the objectives of the
analysis."
Structure and 4 marks "Proper use of appendices and all
appendices are well-organised and
correctly cited in the report."
Presentation 4 marks "Report is well-structured, professionally
presented, and follows logical order. All
charts and tables should be appropriately
labelled"
Mathematical Notations 4 marks "Correct use of mathematical notations and
symbols throughout the report."
Overall Cohesiveness 2 marks "Report flows well with clear transitions
between sections; cohesive discussion and
presentation."| Criteria | Marks | Description |
| :--- | :--- | :--- |
| Executive Summary | 2 marks | Clear, concise, and provides a strong <br> overview of the key findings and <br> methodology. |
| Introduction | 2 marks | Clearly introduces the problem, a brief data <br> description, and objectives of the analysis. |
| Conclusion | 2 marks | Summarises the findings effectively and <br> connects back to the objectives of the <br> analysis. |
| Structure and | 4 marks | Proper use of appendices and all <br> appendices are well-organised and <br> correctly cited in the report. |
| Presentation | 4 marks | Report is well-structured, professionally <br> presented, and follows logical order. All <br> charts and tables should be appropriately <br> labelled |
| Mathematical Notations | 4 marks | Correct use of mathematical notations and <br> symbols throughout the report. |
| Overall Cohesiveness | 2 marks | Report flows well with clear transitions <br> between sections; cohesive discussion and <br> presentation. |
2. Hypothesis Testing (16 marks) 假设检验(16 分)
Criteria 标准
Marks 标记
Description 描述
F 检验等方差
F-test for Equal
Variance
F-test for Equal
Variance| F-test for Equal |
| :--- |
| Variance |
2 marks 2 分
正确执行和讨论 F 检验以检验方差是否相等。
Correct execution and discussion of the F-
test for equal variances.
Correct execution and discussion of the F-
test for equal variances.| Correct execution and discussion of the F- |
| :--- |
| test for equal variances. |
Null and Alternative
Hypotheses (H_(0)//H_(1))| Null and Alternative |
| :--- |
| Hypotheses $\left(\mathbf{H}_{0} / \mathbf{H}_{\mathbf{1}}\right)$ |
1 mark 1 马克
适当的零假设和备择假设的制定。
Proper formulation of the null and
alternative hypotheses.
Proper formulation of the null and
alternative hypotheses.| Proper formulation of the null and |
| :--- |
| alternative hypotheses. |
检验统计量和中心极限定理讨论
Test Statistic and CLT
Discussion
Test Statistic and CLT
Discussion| Test Statistic and CLT |
| :--- |
| Discussion |
1 mark 1 马克
正确的检验统计量,并在适用的情况下适当讨论中心极限定理(CLT)。
Correct test statistic, with appropriate
discussion of the Central Limit Theorem
(CLT) where applicable.
Correct test statistic, with appropriate
discussion of the Central Limit Theorem
(CLT) where applicable.| Correct test statistic, with appropriate |
| :--- |
| discussion of the Central Limit Theorem |
| (CLT) where applicable. |
Calculation of t-statistic t 统计量的计算
1 mark 1 马克
Accurate calculation of the t-statistic. t 统计量的准确计算。
P-value Calculation P 值计算
1 mark 1 马克
正确计算和解释 p 值。
Correct calculation and interpretation of the
p-value.
Correct calculation and interpretation of the
p-value.| Correct calculation and interpretation of the |
| :--- |
| p-value. |
Decision Rule 决策规则
1 mark 1 马克
明确的决策规则说明,使用拒绝区域和 p 值
Clear statement of the decision rule, using
both the rejection region and p-value
Clear statement of the decision rule, using
both the rejection region and p-value| Clear statement of the decision rule, using |
| :--- |
| both the rejection region and p-value |
假设检验的结论
Conclusion from
Hypothesis Test
Conclusion from
Hypothesis Test| Conclusion from |
| :--- |
| Hypothesis Test |
1 mark 1 马克
基于测试结果的准确和逻辑结论。
Accurate and logical conclusion based on
the test result.
Accurate and logical conclusion based on
the test result.| Accurate and logical conclusion based on |
| :--- |
| the test result. |
Critical Thinking 批判性思维
Critical Thinking| Critical Thinking |
| :--- |
8 marks 8 分
对测试结果及其影响的深刻和批判性讨论,展示了
Insightful and critical discussion of the test
result and its implications, demonstrating
Insightful and critical discussion of the test
result and its implications, demonstrating| Insightful and critical discussion of the test |
| :--- |
| result and its implications, demonstrating |
Discussion 讨论
strong understanding of the findings. 对研究结果有深入的理解。
strong understanding of the findings.| strong understanding of the findings. |
| :--- |
Criteria Marks Description
"F-test for Equal
Variance" 2 marks "Correct execution and discussion of the F-
test for equal variances."
"Null and Alternative
Hypotheses (H_(0)//H_(1))" 1 mark "Proper formulation of the null and
alternative hypotheses."
"Test Statistic and CLT
Discussion" 1 mark "Correct test statistic, with appropriate
discussion of the Central Limit Theorem
(CLT) where applicable."
Calculation of t-statistic 1 mark Accurate calculation of the t-statistic.
P-value Calculation 1 mark "Correct calculation and interpretation of the
p-value."
Decision Rule 1 mark "Clear statement of the decision rule, using
both the rejection region and p-value"
"Conclusion from
Hypothesis Test" 1 mark "Accurate and logical conclusion based on
the test result."
"Critical Thinking" 8 marks "Insightful and critical discussion of the test
result and its implications, demonstrating"
Discussion "strong understanding of the findings."| Criteria | Marks | Description |
| :--- | :--- | :--- |
| F-test for Equal <br> Variance | 2 marks | Correct execution and discussion of the F- <br> test for equal variances. |
| Null and Alternative <br> Hypotheses $\left(\mathbf{H}_{0} / \mathbf{H}_{\mathbf{1}}\right)$ | 1 mark | Proper formulation of the null and <br> alternative hypotheses. |
| Test Statistic and CLT <br> Discussion | 1 mark | Correct test statistic, with appropriate <br> discussion of the Central Limit Theorem <br> (CLT) where applicable. |
| Calculation of t-statistic | 1 mark | Accurate calculation of the t-statistic. |
| P-value Calculation | 1 mark | Correct calculation and interpretation of the <br> p-value. |
| Decision Rule | 1 mark | Clear statement of the decision rule, using <br> both the rejection region and p-value |
| Conclusion from <br> Hypothesis Test | 1 mark | Accurate and logical conclusion based on <br> the test result. |
| Critical Thinking | 8 marks | Insightful and critical discussion of the test <br> result and its implications, demonstrating |
| Discussion | | strong understanding of the findings. |
3. Regression Analysis (24 marks) 回归分析 (24 分)
Criteria 标准
Marks 标记
Description 描述
Stating the Full Model 阐述完整模型
1 mark 1 马克
清楚地说明完整模型,识别因变量和自变量。
Clearly states the full model, identifying
dependent and independent variables.
Clearly states the full model, identifying
dependent and independent variables.| Clearly states the full model, identifying |
| :--- |
| dependent and independent variables. |
完整模型的估计(附录中有输出)
Estimation of Full Model
(with output in
Appendix)
Estimation of Full Model
(with output in
Appendix)| Estimation of Full Model |
| :--- |
| (with output in |
| Appendix) |
1 mark 1 马克
正确的模型估计,结果见附录。
Correct model estimation with results
shown in the appendix.
Correct model estimation with results
shown in the appendix.| Correct model estimation with results |
| :--- |
| shown in the appendix. |
Correlation Analysis 相关性分析
2 marks 2 分
适当的相关性分析和变量之间关系的讨论。
Proper correlation analysis and discussion
of the relationships between variables.
Proper correlation analysis and discussion
of the relationships between variables.| Proper correlation analysis and discussion |
| :--- |
| of the relationships between variables. |
最终模型及其理由
Final Model with
Justification
Final Model with
Justification| Final Model with |
| :--- |
| Justification |
2 marks 2 分
适当选择最终模型,并对所选和排除的变量提供明确的理由。
Appropriate selection of the final model with
clear justification for the variables chosen
and excluded.
Appropriate selection of the final model with
clear justification for the variables chosen
and excluded.| Appropriate selection of the final model with |
| :--- |
| clear justification for the variables chosen |
| and excluded. |
Criteria Marks Description
Stating the Full Model 1 mark "Clearly states the full model, identifying
dependent and independent variables."
"Estimation of Full Model
(with output in
Appendix)" 1 mark "Correct model estimation with results
shown in the appendix."
Correlation Analysis 2 marks "Proper correlation analysis and discussion
of the relationships between variables."
"Final Model with
Justification" 2 marks "Appropriate selection of the final model with
clear justification for the variables chosen
and excluded."| Criteria | Marks | Description |
| :--- | :--- | :--- |
| Stating the Full Model | 1 mark | Clearly states the full model, identifying <br> dependent and independent variables. |
| Estimation of Full Model <br> (with output in <br> Appendix) | 1 mark | Correct model estimation with results <br> shown in the appendix. |
| Correlation Analysis | 2 marks | Proper correlation analysis and discussion <br> of the relationships between variables. |
| Final Model with <br> Justification | 2 marks | Appropriate selection of the final model with <br> clear justification for the variables chosen <br> and excluded. |
Overall Significance ( FF test) 整体意义 ( FF 测试)
Correct execution and interpretation of the overall significance of the model using the F-test. 使用 F 检验正确执行和解释模型的整体意义。
Individual Significance (t-tests) 个体显著性(t 检验)
Correct execution and interpretation of the individual significance of variables using ttests. 正确执行和解释使用 t 检验的变量个体重要性。
模型拟合 ( R^(2)\mathbf{R}^{2} 和调整后的 R ^(2){ }^{2} )
Model Fit ( R^(2)\mathbf{R}^{2} and
Adjusted R ^(2){ }^{2} )
Model Fit ( R^(2) and
Adjusted R ^(2) )| Model Fit ( $\mathbf{R}^{2}$ and |
| :--- |
| Adjusted R ${ }^{2}$ ) |
2 marks 2 分
Clear and accurate discussion of the model fit using R^(2)\mathrm{R}^{2} and Adjusted R^(2)\mathrm{R}^{2}. 清晰准确地讨论模型拟合使用 R^(2)\mathrm{R}^{2} 和调整后的 R^(2)\mathrm{R}^{2} 。
Thorough checking of regression assumptions (linearity, homoscedasticity, multicollinearity, normality). 彻底检查回归假设(线性、同方差性、多重共线性、正态性)。
Critical Discussion of Findings in Context 在背景下对发现的关键讨论
8 marks 8 分
Deep, insightful analysis of the findings within the context of the problem, demonstrating strong understanding and analysis. 深入、深刻的分析结果,结合问题背景,展现出强大的理解和分析能力。
Overall Significance ( F test) Correct execution and interpretation of the overall significance of the model using the F-test.
Individual Significance (t-tests) Correct execution and interpretation of the individual significance of variables using ttests.
"Model Fit ( R^(2) and
Adjusted R ^(2) )" 2 marks Clear and accurate discussion of the model fit using R^(2) and Adjusted R^(2).
"Testing Regression
Assumptions" 4 marks Thorough checking of regression assumptions (linearity, homoscedasticity, multicollinearity, normality).
Critical Discussion of Findings in Context 8 marks Deep, insightful analysis of the findings within the context of the problem, demonstrating strong understanding and analysis.| Overall Significance ( $F$ test) | | Correct execution and interpretation of the overall significance of the model using the F-test. |
| :---: | :---: | :---: |
| Individual Significance (t-tests) | | Correct execution and interpretation of the individual significance of variables using ttests. |
| Model Fit ( $\mathbf{R}^{2}$ and <br> Adjusted R ${ }^{2}$ ) | 2 marks | Clear and accurate discussion of the model fit using $\mathrm{R}^{2}$ and Adjusted $\mathrm{R}^{2}$. |
| Testing Regression <br> Assumptions | 4 marks | Thorough checking of regression assumptions (linearity, homoscedasticity, multicollinearity, normality). |
| Critical Discussion of Findings in Context | 8 marks | Deep, insightful analysis of the findings within the context of the problem, demonstrating strong understanding and analysis. |
As you can see, critical thinking plays a significant role in this assignment. So, DO NOT just focus on the numbers-make sure they tell a meaningful story and make sense in the context of the problem. 如您所见,批判性思维在此任务中发挥着重要作用。因此,请不要仅仅关注数字——确保它们讲述一个有意义的故事,并在问题的背景下有意义。
6 Other instructions 6 其他指示
Assignment submission 作业提交
Only one person from each group should submit the assignment. You can submit your assignment an unlimited number of times before the deadline, but only the most recent version will be marked. 每个小组只需一人提交作业。您可以在截止日期之前无限次提交作业,但只有最新版本会被评分。
To preserve the formatting of your work, you are required to submit your report as a PDF. You do not need to submit your Excel datasheet; however, as mentioned above, you can include Excel outputs in the appendices when necessary. 为了保持您工作的格式,您需要将报告提交为 PDF 文件。您不需要提交 Excel 数据表;但是,如上所述,您可以在必要时将 Excel 输出包含在附录中。
The formatting requirements are already specified in the Word template file, “QBUS5001_Report Template.docx.” 格式要求已在 Word 模板文件“QBUS5001_Report Template.docx”中指定。
Submission deadline 提交截止日期
The deadline is 23:59 on Sunday, 27 Oct 2024. However, I’m giving everyone a 5day simple extension automatically, so no penalties will apply if you submit by 23:59 on Friday, 1 Nov 2024. After that, a late penalty of 5%5 \% of the total possible marks will be applied per day. If you submit after 23:59 on 1 Nov 2024, you’ll start with a 25%25 \% penalty (as the official deadline is 27 Oct) plus 5%5 \% for each additional day. Please submit on time to avoid penalties! I really don’t want to penalise anyone, but this is university policy. 截止日期是 2024 年 10 月 27 日星期日 23:59。然而,我将自动给予每个人 5 天的简单延期,因此如果您在 2024 年 11 月 1 日星期五 23:59 之前提交,将不适用任何罚款。之后,每延迟一天将会对总分的 5%5 \% 施加迟交罚款。如果您在 2024 年 11 月 1 日 23:59 之后提交,您将面临 25%25 \% 的罚款(因为正式截止日期是 10 月 27 日)加上每延迟一天的 5%5 \% 。请按时提交以避免罚款!我真的不想对任何人施加罚款,但这是大学政策。
Use of generative AI 生成性人工智能的使用
You are allowed to use generative AI tools like ChatGPT to assist in generating material for evaluation and analysis. However, you must clearly indicate where AI tools were used. Al-generated content cannot be represented as your own work. Failing to declare the use of Al will be treated as a serious breach of policy. 您可以使用生成性人工智能工具,如 ChatGPT,来协助生成评估和分析材料。然而,您必须清楚地指明使用了哪些人工智能工具。人工智能生成的内容不能被视为您自己的作品。未能声明使用人工智能将被视为严重违反政策。
You are not permitted to submit Al-generated content directly for your assignment. Al tools do not provide sufficient responses to meet the assessment criteria, and their undeclared use will result in a breach of policy. 您不被允许直接提交由人工智能生成的内容作为您的作业。人工智能工具提供的响应不足以满足评估标准,未声明的使用将导致违反政策。
According to the Academic Integrity Procedures (2022), minor breaches (e.g., poor paraphrasing, failure to credit sources, incorrect citations) may result in a penalty of 根据《学术诚信程序》(2022),轻微违规(例如,糟糕的改写、未能注明来源、不正确的引用)可能会导致处罚。
up to 15%15 \% of the total marks. Major breaches will be submitted for investigation by the Faculty’s Academic Integrity team. 最高可达 15%15 \% 的总分。重大违规行为将提交给学院的学术诚信团队进行调查。
Peer review 同行评审
Peer review is optional, as different group members may contribute in varying ways. However, if a student makes no contribution to the group assignment, you can submit a peer review form to notify me. 同行评审是可选的,因为不同的组员可能以不同的方式做出贡献。然而,如果学生对小组作业没有任何贡献,您可以提交同行评审表格通知我。
Briefly describe the issue with reference to specific student name and student ID 简要描述问题,参考具体学生姓名和学生 ID
Take a picture of your student ID card with a signature next to it from all group members who wishes to submit this form. (Tip: Place your ID card on a blank sheet of paper, sign next to it, and take the photo.) 请拍摄所有希望提交此表格的组员的学生证照片,并在旁边签名。(提示:将您的学生证放在一张空白纸上,旁边签名,然后拍照。)
Finally, best of luck with your group assignment! I hope you all get HD! 最后,祝你们小组作业顺利!希望你们都能拿到高分!