RSM1: Coursework Report (25% final grade)Research Methods and Statistics 1 - PPLS08001Coursework set: 12noon, Friday 1st March 2019Coursework due: 12noon, Thursday 28th March 2019Feedback returned: Thursday 19th April 2019Online hand-in: read carefully!An electronic copy of your report should be submitted online via the Turnitin link on the LEARN page forRMS1. This will be located under the ‘Assessment Details & Submission’ tab. You should also submit yourR-code through the same link. The submission link will become available after you click on the “Own workdeclaration” link.IMPORTANT: Please name your files using your exam number onlyDo not include any identifying information in the file name(no name and no matriculation number)You must follow this naming convention EXACTLY so that we can match your R-code to your script. Failureto do so may result in your coursework not being graded.Example of submission if your exam number was B00001 (you will use your own exam number, obviously!):1. B000001.doc (or B000001.docx or B000001.pdf etc) file containing your report Include your exam number inside the report too! In the header or footer of each page.2. B000001.R file containing your R code Include your exam number inside your R code too! This student could have used # B000001 asfirst line in her scriptYou will be contacted by email by the course administrator, Alex McAndrew, to confirm all hand ininstructions.TaskYou are provided with a data set, a description of the data set, and a set of research questions. Your taskis to analyse the data in order to provide answers to the research questions. Analyses will draw on theanalytic procedures we have discussed in lectures and labs. You also have one conceptual question toanswer using knowledge you have built during this year.Page 2 of 4Queries concerning the taskThis document contains a basic overview of the task and of how to submit it.If you have any questions concerning the coursework report, we ask that you post them on thedesignated section of the on-line discussion board on Learn. If you have a question, it is likely yourclassmates may have the same question. Before posting a question, please check the on-line board incase it has already been answered.GradingMarks will be awarded for providing correct information for each element in the list above, for each of thequestions you are asked. Marks will be evenly distributed across questions.You are required to submit your R-code which reproduces the answers you in the report. If the submittedcode runs and reproduces exactly the results reported, you will be awarded 10%. If the code fails to run,or does not exactly reproduce the results reported, you will lose 10%.Coursework bodyBelow are four research questions and one conceptual question. The research questions refer to datafrom the file RMS1_1718_coursework_data.csv (available on Learn). Names of variables correspond tocolumn names from that file.Your answer to each research question should include your analysis strategy and rationale why you arechoosing a particular method/analytical tool. You should aim to show us what you’ve learnt during thecourse, making clear references to appropriate statistical tests, assumptions and providing detailedinterpretations.These are some of the guidelines on what your answer should include.Research Questions (Max:1750): Data presentation: all necessary checks and data descriptions need to be reported Analysis strategy (i.e. the hypotheses; choice of the test; where assumptions are required thoseneed to be referred to) Present clearly the results from your analysis in R and provide clear interpretation. Discuss the results in the context of the original research question using your own words. Is thisconsistent with what you expected? Outline briefly the limitations of this research design, bothstatistically and practically.Conceptual Question (Max:250): Provide a detailed answer to the question using your own words and statistical terminology.Provide a clear example for illustration. Page 3 of 4Research QuestionsQuestion 1A research team conducts a study examining the effects of various manipulations on participants’ ability tolearn novel categories. The experimenters create a set of cartoon aliens. Each alien belongs to one of fiveimaginary alien species created by the experimenters.In one study, participants study labelled examples of these cartoon aliens then take a categorisation test.Participants either (a) study a set of 50 exemplars presented one at a time in a random order, (b) study 25pairs of exemplars, each from the same category, (c) study 25 pairs of exemplars, each from a differentcategory, or (d) study 50 exemplars presented one at a time, but blocked by category (i.e., all the exemplarsfrom one category are presented, followed by the exemplars from the next category, and so on). The same50 exemplars are used for each study condition.The research team is interested in whether study type (study_type) has an effect on how well participantsperform in the categorisation test (scores are given in cat_test).Did study type have any effect on categorisation performance? If so, what were those effects?Question 2The same team is interested in how caffeine intake might affect how quickly exemplars are categorised.They teach a group of participants 3 new categories until they can identify members of the categories with100% accuracy.The next day, they ask all participants to return to complete a timed categorisation task on which theymeasure reaction time (cat_RT; milliseconds). They estimated individuals’ caffeine intake that morning byasking respondents to recall all food and drink consumed prior to testing (caffeine; mg).Did caffeine affect reaction time?Question 3The team are then interested in whether participants learned all the different categories during study. Theywant to look at whether there were any differences in whether or not participants learned all five of thealien categories from question 1 (learned_cat, 0=no; 1=yes), depending on which study condition(study_type) they were in.Is there a relationship between study type and whether all five categories were learned or not?Question 4The research team were also interested in whether participating in the experiment has an effect on workingmemory (WM) ability. Each participant also received a WM test before and after completing theexperiment (WM_before, WM_after).Was there any difference in WM before and after the experiment?Page 4 of 4Conceptual Question (choose one)a) Discuss the difference between standard deviation and standard error.b) Illustrate the qualities of a good estimator.c) Illustrate the approaches that one can use to test a hypothesis.本团队核心人员组成主要包括硅谷工程师、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
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