Publications by Jose Fernandez, Rudy Martinez, Brenda Parnin
Algo - Intro
Exercise 1: Descriptive Statistics (A) Create a combined mpg variable called MPG_Combo which combines 55% of the MPG_City and 45% of the MPG_Highway. Obtain a box plot for MPG_Combo and comment on what the plot tells us about fuel efficiencies. MPG_Combo <- 0.55*cars$MPG_City+0.45*cars$MPG_Highway cars=data.frame(cars, MPG_Combo) boxplot(...
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R Basics
This homework uses txhousing dataset from ggplot2 package, which is a part of the tidyverse. Additionally, it uses Consumer Price Index (CPI) dataset, which I downloaded from the BLS website (https://data.bls.gov/timeseries/CUUR0000SA0) and cleaned. I will provide the code for cleaning CPI data in the solution to this homework. txhousing consists...
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R using ggplot
In this homework, you will use diamonds data set from ggplot2 package. It is automatically loaded when you execute library(ggplot2) so you don’t have to separately load it. Please create a duplicate of diamonds and use that for homework. This will avoid corrupting the original data set. Make sure that you understand the variables in the data by...
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Algo Midterm
Data Sets: You need to download dataset birthweight.csv for Exercise 1-4. The birthweight data record live, singleton births to mothers between the ages of 18 and 45 in the United States who were classified as black or white. There are total of 400 observations in birthweight, and variables are: Weight: Infant birth weight (gram) Black: Categor...
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R using Interactive Visualizations
Before you begin, note that, in the header, the output format of this document is html_notebook. When you save this file, it automatically creates another file with the same file name but with .nb.html extension in the same directory. This is the file you will submit as your homework solution along with the .Rmd file. Warnings: Don’t delete t...
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Algo- Simple and Multiple Linear Regression
library(MASS); library(car); library(olsrr) ## Loading required package: carData ## Warning: package 'olsrr' was built under R version 4.0.3 ## ## Attaching package: 'olsrr' ## The following object is masked from 'package:MASS': ## ## cement ## The following object is masked from 'package:datasets': ## ## rivers Exercise 1: We wo...
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Statistical Learning: Assignment 1
Chapter 02 (page 54): 2, 5, 6, 8-10 Question 2 Explain whether each scenario is a classification or regression problem, and indicate whether we are most interested in inference or prediction. Finally, provide n and p. We collect a set of data on the top 500 firms in the US. For each firm we record profit, number of employees, industry and the C...
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Assignment 5_Linear Model Selection and Regularization
Chapter 06 (page 259): 2, 9, 11 2. For parts (a) through (c), indicate which of i. through iv. is correct. Justify your answer. (a) The lasso, relative to least squares, is: i. More flexible and hence will give improved prediction accuracy when its increase in bias is less than its decrease in variance. ii. More flexible and hence will give i...
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Linear Regression
Chapter 03 (page 120): 2, 9, 10, 12 2. Carefully explain the differences between the KNN classifier and KNN regression methods. The KNN Classifier is typically used to to solve classification problems (qualitative) while KNN regression method is used to solve regression problems (quantitative). 9. This question involves the use of multiple lin...
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Assignment 3_Classification
Chapter 04 (page 168): 10, 11, 13 10. This question should be answered using the Weekly data set, which is part of the ISLR package. This data is similar in nature to the Smarket data from this chapter’s lab, except that it contains 1, 089 weekly returns for 21 years, from the beginning of 1990 to the end of 2010. (a) Produce some numerical a...
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