— title: “Homework 3” subtitle: “Psychology 2812B FW22” — # Lab Component ## 1. LGA mean departure delay Load the `tidyverse` package and the `nycflights` dataset. Note that you will first need to install the nycflights13 dataset: “`{r} #| echo: true #| eval: false install.packages(“nycflights13”) “` “`{r} #| echo: TRUE #| output: FALSE library(tidyverse) library(nycflights13) […]
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1. Write a short comment about what this R script is about. 2. Remove all existing objects in your “environment”. 3. Create a vector called “HousePrices”, which consists of 100 random numbers generated from a Normal distribution, mean and the standard deviation of which are 300,000 and 50,000 respectively. Hint: use function “norm” to generate
Higher-Order Functions, Tuples, same_arg twice The purpose of this question is to help the student master: • pattern matching, which is a major method used in functional programming. Using VSCode – General Instructions Problem Write a function same_arg_twice : (a ‘b) “b that takes a function and then an argument as inputs and returns the
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Consider the following statements about Java programs: • Statement A: In Java, two different classes can define a field with the same name and type. • Statement B: In Java, one class can define two fields with the same name as long as they have different types. • Statement C: In Java, two different methods
Optimal Versus Naive Diversification: How Inefficient is the 1/N Portfolio Strategy? Victor DeMiguel London Business School Lorenzo Garlappi University of Texas at Austin Raman Uppal London Business School and CEPR We evaluate the out-of-sample performance of the sample-based mean-variance model, and its extensions designed to reduce estimation error, relative to the naive 1/N portfolio. Of
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MSc Finance & MSc IWM: Financial Econometrics Assessed Exercise Instructions Please complete the Exercise below and submit: Point 1. before 6/2/2023 at 15:59 on The Hub. Submission will only be possible via The Hub. Late submissions will not be considered. Points 2. and 3. before 6/3/2023 at 15:59 on The Hub. Submission will
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Financial Econometrics CW Tutorial Outline 1 Assignment Outcomes and Milestones 2 Brief Summary of Replication Paper 3 Data and methodology 4 FAQ and hints Assignment Outcomes and Milestones learn how to construct portfolios and strategies, and calculate their expected returns improve your programming skills (running regressions, producing plots, computing descriptive statistics, cleaning data) exercise fin.
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Exam 2 Exam 2 will cover lessons 13 (Planning) through 25 (Advanced Topics). There will not be any questions specifically about earlier lessons, although there may be questions that require knowledge from earlier lessons to answer questions about later lessons (for example, you might need to know the operators from the Logic lesson to answer
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Exam 1 Exam 1 will cover lessons 01 (Introduction to Knowledge-Based AI) through 12 (Logic). The exam will consist of 22 five-answer multi-correct multiple-choice questions. All questions come from the lectures; no readings are tested on the exam. Each of the five-answer multi-correct multiple-choice questions is eligible for partial credit. You will receive one point
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RPM project Overview Our semester-long class project in involves constructing an AI agent to address a human intelligence test. The project is due at the end of the semester, but there are a number of required milestones to pass along the way. These are (a) to ensure that you are getting an early enough start
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