STA 463 Simple Linear Regression Report
STA 463 Simple Linear Regression Report
Spring 2019
The goal of this part of the project is to perform a thorough simple linear regression analysis on data collected by each group. In addition, a report will be created to introduce and summarize your analysis finding.
By Wednesday, April 24, 11:40 am, each group should upload to the canvas website (1) a 2-3 pages report (the reference and appendix is not counted for the page limit); (2) a separate R file containing all the code you used, with clear notations for the program to indicate what you have done in your analysis.
1.The report should contain the following parts:
Title and authors;
Abstract: A paragraph-long summary of the research including the context, research questions, methods, and findings of your simple linear regression model;
Introduction: The introduction should include a brief description of the data you are analyzing, the important finding you had done in your EDA that leads you to this stage of analysis. And clearly state your simple linear regression research questions. You can also provide a summary of other existing research results/literatures on similar topic if there is any;
Methods and Analysis: Describe the whole analysis you have done. You should do a complete simple linear regression analysis for the research questions you have listed in the Introduction section. (hint: if you find any seriously violations in the assumptions, you should use appropriate remedial methods to edit your model;
Results: Use graphs or tables (make sure they are properly labeled, titled and formatted, please make sure no screenshot of the table/picture is allowed.) to answer all the research questions you raised in the introduction section. In this part, you should include the statistical conclusions based on the graphs/tables you get. Interpret your results assuming your audience are people who have some background in linear regression analysis;
Conclusion and Discussion: A conclusion paragraph that summarizes your findings from the project. Also include some questions you have and any idea for potential follow-up work;
STA 463作业代写、Linear留学生作业代做、R语言作业代做、R程序设计作业代做
References: Choose a particular citation format (for example APA, Chicago, MLA, etc, styles). You should cite any resources you used (it could be journal articles, website, etc. Remember to cite the source of the dataset as well. );
Appendix: Other graphs or tables that you didn’t include in the main part of the project, if there’s any.
2.Grading Rubric:
Different Aspects of the report Criteria Points
Abstract Clearly and concise summary the context, research questions, methods, and findings. 4
Introduction Clear statements of the findings and the research questions. With meaningful explanations. 4
Methods and Analysis Regression analysis is complete and correct. The assumptions are checked and violations of assumptions are appropriately addressed. 10
Results Clearly address the research questions through the tables/graphs. Only relevant outputs are included. Appropriate and meaningful interpretations of the results are included. 4
Conclusions and Discussions The results are clearly summarized and the research questions are adequately addressed. Future work or possible research directions has been mentioned. 4
Format The writing is well-done. The graphs/tables are properly labeled, titled and formatted. The references follow the required format. There’re very few issues with spelling/language/grammar, etc. 4
Readability of code The code is well documented and structured for readability. Appropriate comment is used to instruct users the functions of each part of your program. The code is properly indented. 2
Code reproducibility The results from the code are correct and the same as what you have provided in your report. 3
因为专业,所以值得信赖。如有需要,请加QQ:99515681 或邮箱:99515681@qq.com
微信:codinghelp
STA 463 Simple Linear Regression Report的更多相关文章
- Linear Regression with Scikit Learn
Before you read This is a demo or practice about how to use Simple-Linear-Regression in scikit-lear ...
- 机器学习---线性回归(Machine Learning Linear Regression)
线性回归是机器学习中最基础的模型,掌握了线性回归模型,有利于以后更容易地理解其它复杂的模型. 线性回归看似简单,但是其中包含了线性代数,微积分,概率等诸多方面的知识.让我们先从最简单的形式开始. 一元 ...
- 【cs229-Lecture2】Linear Regression with One Variable (Week 1)(含测试数据和源码)
从Ⅱ到Ⅳ都在讲的是线性回归,其中第Ⅱ章讲得是简单线性回归(simple linear regression, SLR)(单变量),第Ⅲ章讲的是线代基础,第Ⅳ章讲的是多元回归(大于一个自变量). 本文的 ...
- 机器学习:线性回归法(Linear Regression)
# 注:使用线性回归算法的前提是,假设数据存在线性关系,如果最后求得的准确度R < 0,则说明很可能数据间不存在任何线性关系(也可能是算法中间出现错误),此时就要检查算法或者考虑使用其它算法: ...
- [Sklearn] Linear regression models to fit noisy data
Ref: [Link] sklearn各种回归和预测[各线性模型对噪声的反应] Ref: Linear Regression 实战[循序渐进思考过程] Ref: simple linear regre ...
- Simple tutorial for using TensorFlow to compute a linear regression
"""Simple tutorial for using TensorFlow to compute a linear regression. Parag K. Mita ...
- Regularized Linear Regression with scikit-learn
Regularized Linear Regression with scikit-learn Earlier we covered Ordinary Least Squares regression ...
- Linear Regression with machine learning methods
Ha, it's English time, let's spend a few minutes to learn a simple machine learning example in a sim ...
- 多重线性回归 (multiple linear regression) | 变量选择 | 最佳模型 | 基本假设的诊断方法
P133,这是第二次作业,考察多重线性回归.这个youtube频道真是精品,用R做统计.这里是R代码的总结. 连续变量和类别型变量总要分开讨论: 多重线性回归可以写成矩阵形式的一元一次回归:相当于把多 ...
随机推荐
- Centos7.5 安装VirtualBox增强工具
一.安装 1.自带tools: 选择VirtualBox工具栏 => 设备 => 安装增强功能 2.挂载光驱 3.进入光驱目录,执行(一定要用root权限执行) ①安装gcc yum i ...
- java.lang.NoClassDefFoundError: org/apache/commons/lang3/StringUtils
♦ 问题所在:项目lib包里少一个jar包 ♦ 解决办法: commons-lang3-3.1.jar 导入到项目就ok
- Oracle 数据文件迁移
背景 这两天做一个oracle数据库迁移,以前都是用exp.imp来走,这次用到了expdp.impdp,的确有些优势,但同时又想起了只是拷贝数据文件迁移的方式,其实这个方式不常用做迁移,更多用在磁盘 ...
- lnmp.org 安装环境的,root权限都没法删除网站文件夹,问题解决-转
rm -rf删除网站目录时出现rm: cannot remove `.user.ini': Operation not permitted rm -rf删除网站目录时出现rm: cannot remo ...
- 【java】Java组件概览(1)
如上图所示,Oracle的Java SE8有两个产品:JDK和JRE.其中,JRE的内容包括图中①~⑤,它是JDK的子集. ⑥中的红色部分与JRE有重合. [参考] 1.https://docs.or ...
- js编译原理(你不知道的javascript)
虽然通常将js归类为"动态"或"解释执行"语言,但其实也可把它看成是一门编译语言.只不过这个所谓的编译与传统的编译语言不同,它不是提前编译的,编译结果也不能在分 ...
- django 实战篇之模板层
模板层 {{}} 变量相关 {%%} 逻辑相关 前端获取容器类型的数据统一使用 句点符(.) 两种给模板传递值的方式 return render(request,'index.html ...
- Django—入门
索引 1.搭建环境 2.创建项目 3.设计模型 4.管理站点 5.视图及URL 6.模板 软件框架 问题1:什么是软件框架? 举个简单的例子,对于一个公司来说,公司中有各个职能部门,每个部门各司其职, ...
- [慢更]Sublime Text 快捷键及使用过的插件
整理自己常用的sublime text命令和插件 1.pretty json Json 快速格式化,免去url访问json站点的烦恼. 摘自:https://segmentfault.com/a/11 ...
- angular 2+ 变化检测系列三(Zone.js在Angular中的应用)
在系列一中,我们提到Zone.js,Zones是一种执行上下文,它允许我们设置钩子函数在我们的异步任务的开始位置和结束位置,Angular正是利用了这一特性从而实现了变更检测. Zones.js非常适 ...