STAT 3401/STAT 4065Assignment OneImportant: This assignment is assessed, and carries weight 20% towards your final mark for theSTAT3401 unit. Your work for this assignment must be submitted to the unit lecturer by 5pm onMonday, 29 April 2019.You may hand in your work during the lectures/computer labs of the STAT3401 on 29 April, or electronicallyat any time before the due date and time. Any student failing to submit work by the deadlinewill receive a penalty for late submission (5% per day late) unless the unit lecturer is advised as soonas possible of any extenuating circumstances. Please ensure that you include your name and studentnumber on your work.Plagiarism: The work that you submit must be your sole effort (i.e. not copied from anyone else). Ifyou are found guilty of plagiarism you may be penalised.The two assignment questions involve the analysis of some data. The data sets mentioned are availablefrom LMS. If you have difficulty accessing the data sets you should contact the lecturer immediately.For these two assignments you should hand in a mini-report. The mini-report for each exercise shouldbe no longer than a single side of A4 paper (excluding any relevant Figures, Tables or computer output,which can be attached as an appendix). You will be marked down for exceeding this page limit. Theaim of the mini-report is to convey the aims, methodology and results of your data analysis in a concise,readable fashion. It is strongly recommended that you structure your report into sections, along thefollowing lines. Introduction: Summarise the data and the aims of the analysis. Methodology: Describe the statistical methods that you use (technical details not required). Results: Describe the results of your analysis and their interpretations. Discussion: Draw conclusions (based on your results) as necessary. Discuss any interesting issuesarising from your analysis.Marks for each mini-report will be awarded (with a relative weighting of 2:3) for Exposition: your mini-reports should be well organised. You should aim to write in a concise, yetreadable, manner. Statistical content: marks will be awarded for the correct use of appropriate statistical techniques,and for the correct interpretation of results from these techniques.1Question oneThe file asian.rda contains the data frame asian with data reported by Rabe-Hesketh and Skrondal(2005, Multilevel and Longitudinal Modeling Using Stata, Stata Press) on the weight gain of Asianchildren in a British community — between 1 and 5 weight measurements were taken for each child.Specifically, the following variables are contained in this data frame:id: a unique identifier for each childocc: on which occasion (visit) the measurement was takenage: the age (in years) of the child when the measurement was takenweight: the weight (in kilograms) of the childbrthwt: the birth weight of the child (in grams)gender: factor indicating whether the child is a boy or a girlAims of the analysis: To investigate which covariates (and possibly which interactions) have an influenceon how the weight of these children develops as they grow older. Use weight as the response, and age,brthwt and gender and as possible covariates to model the mean structure.Note: You may also want to consider polynomial terms in some of the covariates (and interactions ofthese polynomial terms with other covariates). Ensure that you have fitted an appropriate model forthe residuals (heterogeneity and correlation) before investigating the mean structure.2Question twoThe file ratpup.csv contains data on the birth weights of rat pups born to mothers who were randomlyassigned to receive one of three doses (high, low, control) of an experimental compound. When analysingthis data previously in lectures and computer labs, we noticed that the data set may contain outlyingvalues. Identify the data point corresponding to the largest (in absolute value) Pearson residual andremove it from the data before re-analysing the data.Aims of the analysis: To compare the birth weights of pups from litters born to female rats that receivedthe high- and low-dose treatments to the birth weights of pups from litters that received the controltreatment, and to quantify the influence the treatments have on the birth weights.Note: In your report you should clearly state which observation you have removed, whether this removal changed the results of the analysis qualitatively (i.e. did you arrive at adifferent final model? If not, did the outlying observation have an undue influence on the estimatedfixed effects, especially those associated with treatment, in the original analysis?); and is there any indication that there are further outlying observations present in the data.3本团队核心人员组成主要包括BAT一线工程师，精通德英语！我们主要业务范围是代做编程大作业、课程设计等等。我们的方向领域：window编程 数值算法 AI人工智能 金融统计 计量分析 大数据 网络编程 WEB编程 通讯编程 游戏编程多媒体linux 外挂编程 程序API图像处理 嵌入式/单片机 数据库编程 控制台 进程与线程 网络安全 汇编语言 硬件编程 软件设计 工程标准规等。其中代写编程、代写程序、代写留学生程序作业语言或工具包括但不限于以下范围:C/C++/C#代写Java代写IT代写Python代写辅导编程作业Matlab代写Haskell代写Processing代写Linux环境搭建Rust代写Data Structure Assginment 数据结构代写MIPS代写Machine Learning 作业 代写Oracle/SQL/PostgreSQL/Pig 数据库代写/代做/辅导Web开发、网站开发、网站作业ASP.NET网站开发Finance Insurace Statistics统计、回归、迭代Prolog代写Computer Computational method代做因为专业，所以值得信赖。如有需要，请加QQ：99515681 或邮箱：99515681@qq.com 微信：codehelp QQ：99515681 或邮箱：99515681@qq.com 微信：codehelp
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