Multivariate Analysis: Assignment 1 The University of New South Wales School of Mathematics Department of Statistics 2019 T3: Due at the start of class on Friday, 4 October • Submission instructions will be posted shortly. • No late assignments will be accepted without a successful application for a Special Consideration. • For computational and applied […]
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LECTURES: Lecture Times: STA302H5 – Regression Analysis Fall 2018 Course Outline Tuesday, 16:00 – 18:00 CC 1140 Thursday, 12:00 – 13:00 IB 150 Instructor: Al Nosedal Office Location: DH 3030 (Deerfield Hall) E-mail Address: al.nosedalsanchez@utoronto.ca Office Hours: Tuesday, 18:15 – 19:15 Thursday, 16:15 – 18:15 or by appointment. (Office hours may change before tests) Course
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ITECH5403 – Comparative Programming Languages School of Science, Engineering and Information Technology ITECH5403 – Assignment 2 – Parallel Implementations Due Date: 5pm, Friday of Week 11 This assignment will test your skills in programming applications to specification in a number of different programming languages, and is worth 20% of your non-invigilated (type A) marks for
2B03 Assignment 2 Probability Theory (Chapters 4 & 5) Your Name and Student ID Due Wednesday October 2 2018 (due in class prior to the start of the lecture) Instructions: You are to use R Markdown for generating your assignment (see the item Assignments and R Markdown on the course website for helpful tips and
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Data Analysis Project [15 marks] Due date: 5pm, October 4, 2019 Requirement: Pls finish the tasks according to the requirements. Pls copy all of your R code in the end of this word file, and then submit your word file via the Turnitin link in iLearn. You do not need to upload your data file.
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FIT2086 Assignment 2 Due Date: 11:55PM, Sunday, 29/9/2019 1 Introduction There are total of four questions worth 10 + 10 + 9 + 10 = 39 marks in this assignment. There is one bonus question worth an additional 2 marks. The total marks awarded will be capped at 39, but the bonus marks can compensate
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FIT5141 Assignment 2 2019 Due Date Sunday 15th Sept Deployment of Dataset on MongoDB and R based simple analysis of Data Introduction This assignment is due by 11:55pm Sunday 15th Sept. It is worth 20% of the marks for your final assessment in this unit. A penalty of 10% (of the 20 Marks) per day,
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STATS 380, 2019 Assignment 2 Due: 8pm Fri 20 Sep Submit your assignment online on Canvas before due date. Your submission should include two files: a written report in MS Word or PDF format that contains your answers to the assignment questions, and an R file that includes all your R code. Both files should
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# introduction – Example from – Raw data from “`{r message=FALSE} #install.packages(“tidyverse”) library(tidyverse) library(lubridate) #install.packages(“fpp2”) library(fpp2) library(zoo) “` “`{r message=FALSE} if(!file.exists(“co2_mm_mlo.txt”)) download.file(“ftp://aftp.cmdl.noaa.gov/products/trends/co2/co2_mm_mlo.txt”, “co2_mm_mlo.txt”) co2 % gather(series, co2_conc, average, interpolated, trend) %>% ggplot(aes(x = decimal_date, y = co2_conc, col = series)) + geom_line() “` “`{r} co2 %>% ggplot(aes(x = decimal_date)) + geom_line(aes(y = trend, color =
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GISC 412 – 2019 Exercise 2 Web page topic To demonstrate potential applications of maps and geographic information in a web context, we ask you to develop a web page targeting at least one of the UN sustainability goals: https://www.un.org/sustainabledevelopment/sustainable- development-goals/. A topic for your web page could be, for instance, the 4th goal “Good
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