Publications by Abdelmalek Hajjam
Data605-FinalExam
Video Link: https://youtu.be/KD21iznAR9g library(MASS) library(Matrix) library(matlib) library(dplyr) library(ggplot2) library(tidyr) library(kableExtra) library(purrr) library(Hmisc) Problem 1 Using R, generate a random variable X that has 10,000 random uniform numbers from 1 to N, where N can be any number of your choosing greater th...
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Data 621 - Blog 5
Introduction Today, I decided to blog about an R package memisc, which is available at CRAN, that provides tools for the management of survey data, as well as the creation of tables of summary statistics and model estimates. One of the aims of this package is to make life easier for R users who deal with survey data sets. It provides an infrastr...
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Data 621 - Blog 4
In this post, I choose to talk about linear regression; what it means, what does it do and why we care about it so much. Here I go! What is Linear Regression? Linear regression is a basic and commonly used type of predictive analysis. The overall idea of regression is to examine two things: does a set of predictor variables do a good job in p...
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Data621-Blog3
descriptive statistics is a branch of statistics aiming at summarizing, describing and presenting a series of values or a dataset. Descriptive statistics is often the first step and an important part in any statistical analysis. It allows to check the quality of the data and it helps to “understand” the data by having a clear overview of it. ...
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Data621-Blog2
Introduction As time goes on, R scripts are probably getting longer and more complicated. Timing parts of the script could save us precious time when re-running code over and over again. There are many different ways we can to benchmark R code. usually, such thing will not bother us if we are using small data. But some times, with lot of data, we...
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Blog1
Introduction Today, I choose to blog about something that is always in the way before start modeling, that is one-hot-encoding. Getting started in applied machine learning can be difficult, especially when working with real-world data. Often, machine learning problems will recommend or require that you prepare your data in specific ways before fi...
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Data605-Assignment15
Question 1 Find the equation of the regression line for the given points. Round any final values to the nearest hundredth, if necessary. \((5.6, 8.8), (6.3, 12.4), (7, 14.8), (7.7, 18.2), (8.4, 20.8)\) Answer: x <- c(5.6, 6.3, 7, 7.7, 8.4) y <- c(8.8, 12.4, 14.8, 18.2, 20.8) model <- lm(y~x) model ## ## Call: ## lm(formula = y ~ x) ## ##...
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Data605-Discussion15
Page 496 - Exercise 26 In Exercises 25 – 30, use the Taylor series given in Key Idea 8.8.1 to create the Taylor series of the given functions. \(\text{26.}\) \(f(x) = e^{−x}\) Instead of using the taylor expension for \(e^{x}\) and substitute x by -x, let’s actually do the math, and derive the Taylor series expension of \(e^{-x}\). Let’s...
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Data605-Discussion14
Page:173 - Chapter:4 - Exercise 6 consider \(f(x) = x^2 -2\) and \(x_{0} = 1.5\) To approximate the value of the root of \(f(x)\) accurately to d decimal places using Newtons Method, we follow this plan: Choose a value x0 as an initial approximation of the root. Create successive approximations iteractevely. i.e. given an approximation \(x_{n}\...
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Data 605 - Homework 11
Using the “cars” dataset in R, build a linear model for stopping distance as a function of speed and replicate the analysis of your textbook chapter 3 (visualization, quality evaluation of the model, and residual analysis.) Visualization The cars has 2 variables, namely speed and stopping distance (dist) in feet. str(cars) ## 'data.frame': ...
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