# 代做STAT 3675Q作业、代写STATISTICAL课程作业、代做R程序语言作业、R实验作业代写代做R语言编程|代写Python编程

STAT 3675Q - STATISTICAL COMPUTING UCONN
Fall 2019 Marcos Prates
1. Objective
The IMDB Movies Dataset (file imdb.csv) contains information about over 10,000 movies.
The names of the first twelve columns are self-explanatory (the duration is in seconds). The
rest of the variables (Action, Adult, Adventure, . . .) are dummy variables (0/1) indicating
if the movie has the given genre.
In this project, you will apply a number of statistical methods that have been covered during
the course using R.
• Projects are to be completed individually, or with someone.
• The project is worth 25% of the final grade.
the following guidelines
2. Preliminary report [30 points]
• Provide a single file with the format name_3675_prelim.pdf (or name1_name2_3675_prelim.pdf
if you work with someone), where name is your full name.
• The preliminary report is due on Sunday, November 22, 2019 at 11:59 PM. Submit it
via HuskyCT. The pdf must be generated using Rmarkdown.
Your preliminary report must contain the following elements.
(a) A preliminary exploratory analysis including summary statistics and basic graphs (4
pages max)
(b) Pose scientific questions that are interesting to you and indicate what statistical methods
may help answer those questions (1 page)
(c) Include the R code and all outputs.
3. Report [70 points]
For the report, provide a single file with the format name_3675_report.pdf (or
name1_name2_3675_report.pdf), where name is your full name. The pdf must be
generated using Rmarkdown.
• The report must be at least 10 pages long, without exceeding 30 pages (including the
code and the graphs).
• The report is due on Sunday, December 8, 2019 at 11:59 PM. Submit it via HuskyCT.
(a) Include the preliminary report
(b) Include at least one regression method
(c) Include at least one ANOVA analysis
(d) Include at least one classification method
For each method,
• Express all statistical models using mathematical formulae, and clearly state the meaning
of the notations, and the assumptions.
• Insert R code and necessary comments. Your output must contain the R code (do not
use the echo=FALSE option).
• Interpret extensively all outputs and graphs that you include.
4. Important dates
• November 22, 2019: Preliminary report is due
• Decebmer 8, 2019: Report is due

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