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Exercise sheet 2 (Python) Submition deadline: 09.01.2019, by 10:30 am. Submit to: cklos@uni-bonn.de How to submit: • Change the notebook name to include your last name, e.g. “Exercise sheet 2 (Python) Memmesheimer” • Download your completed notebook (File -> Download as -> Notebook (.ipynb)) • Send it as an email attachment, set email subjuect to […]

Date: Name: WEBSITE DEVELOPMENT PROJECT Website: 16 Written Report and Presentation: 20 PROJECT TOTAL: 36 INSTRUCTIONS: Instructor: The following rubrics provide criteria for which marks are to be assigned. As you review each part of the assignment, assign a value for each criterion. Provide anecdotal comments as required. Each participant should receive a copy of

Date: Name: WEBSITE DEVELOPMENT PROJECT Website: 16 Written Report and Presentation: 20 PROJECT TOTAL: 36 INSTRUCTIONS: Instructor: The following rubrics provide criteria for which marks are to be assigned. As you review each part of the assignment, assign a value for each criterion. Provide anecdotal comments as required. Each participant should receive a copy of

Final Coursework Introduction to Quantitative Research Methods (PUBL0055) Instructions • The coursework will be posted on Moodle on 13th December 2019 at 6pm, and is due on 13th January 2020 at 2pm. Please follow all designated SPP submission guidelines for online submission as detailed on the PUBL0055 Moodle page. Standard late submission penalties apply. •

Lab 5 (Deadline 18:00 10/01/2020) Task You will be provided with a machine learning benchmark dataset (details below). The task focuses on the implementation and critical analysis of multiple regression methods: You should implement, evaluate, and analyse each of the following algorithms: ● Nearest neighbour ● Linear regression ● Regression forest ● Gaussian process The

In [ ]: library(MASS) library(testthat) library(tidyverse) library(gclus) library(GGally) # Plot size deppening on your screen resolution to 4 x 3 options(repr.plot.width=4, repr.plot.height=3) Assignment 1¶ For this assignment, you have to analyse two different data sets. For each plot, add appropriate titles and labels, do not leave the default one. Your submission should run without errors on jupyterhub

Instructions: The maximum length for this assessment is five single-sided A4 paper (Times New Ro- man, 1.5 spacing, 12 point). If you are required to make a decision while conducting a hypothesis test, use a 5% significance level (unless otherwise specified). Be sure to state your null and alternative hypotheses, rejection criterion and your decision.

Department of Accounting and Finance Lancaster University AcF 351b Career Skills in Accounting and Finance Python for Data Analysis Stream Assignment 2019/20 1. Overview Python for Data Analysis stream is designed to provide introductory programming knowledge to students who have no or little prior programming experience. Throughout the five sessions, this module has covered Python

Flood Emergency Planning 2nd Assignment 2 Instructions To complete this assignment, you need to build a Python application. Your task is to create a Python program named ‘main.py’ that does what explained in the following subsections. To do this, you are allowed to use only the packages presented in the module. The first 5 tasks

Lab goals The laboratory part of the ICT4TS focuses on the analysis of free floating car sharing data collected from open systems in the Internet. Data has been collected from websites of FFCS systems like car2go or Enjoy in Italy, and made available through a MondoDB database. The goal of the laboratory is twofold: •