Publications by Frederick Morris Jones
Document Final
Part I Please put the answers for Part I next to the question number (please enter only the letter options; 4 points each): B A D B B E D E B C Part II Consider the three datasets, each with two columns (x and y), provided below. Be sure to replace the NA with your answer for each part (e.g. assign the mean of x for data1 to the data1.x.mean...
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Airline-Safety-Dataset-final-solutions
Data Preparation library(tidyverse) Motivation Motivation: The motivation behind this analysis goes beyond simple counts of accidents and incidents. We aim to delve into the rates of accidents, such as accidents per 100,000 flight miles. This metric allows us to account for changes in flight activity over time. For instance, if the number of ...
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Analyzing messages
Introduction This report presents an analysis of the message exchanges between a wife and a man named Gerald. The data is explored to understand the nature, intensity, and dynamics of their relationship over various phases. Data Preparation The data was cleaned and organized to facilitate analysis. Message categories were identified, and the messa...
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This is some data between texting between wife and man on job. during seperation of husband and wife.
# Load necessary libraries library(ggplot2) library(lubridate) ## ## Attaching package: 'lubridate' ## The following objects are masked from 'package:base': ## ## date, intersect, setdiff, union library(dplyr) ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following ob...
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Calculus page 496 problem 17
# Load the ggplot2 library for plotting library(ggplot2) # Define the Taylor series function for cosine cos_taylor_series <- function(x, terms = 10) { # Initialize the sum of the series sum <- 0 # Loop to calculate each term in the Taylor series for (n in 0:(terms - 1)) { # Compute the nth term of the series: (-1)^n / (2n)! * ...
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Taylor Series
# Load the ggplot2 library for plotting library(ggplot2) # Define the Taylor series function for cosine cos_taylor_series <- function(x, terms = 10) { # Initialize the sum of the series sum <- 0 # Loop to calculate each term in the Taylor series for (n in 0:(terms - 1)) { # Compute the nth term of the series: (-1)^n / (2n)! * x^(2n) ...
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Sentiment Analysis
Sentiment Analysis When a human reader reads a text he uses his intellect to categorize the text as positive or negative or some other category. Similarly, this can be done programmatically. To make a program able to categorize a text into some categories, programmers use the strategy which is known as sentiment analysis. The textbook ‘The Te...
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Collaborative tidyverse project
Introduction This project is all about divorce rate in variaous socio-economic section in the US. The source for all data is Decennial Census (years 1960 to 2000) and American Community Survey (years 2001-2012), via IPUMS USA. The summary of variable names is as follows: Header Description all Total (or all men/women in sex-specific fil...
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Poll analysis
The R code you provided is typically found in R Markdown documents, which are used for creating dynamic reports that combine text, code, and the output of code chunks. Here’s what this specific code does: {r setup, include=FALSE}: This is called a code chunk header in R Markdown. It specifies the settings for a code chunk that follows. In this ...
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Working with XML and JSON in R
Objective The goal of this assignment was to work with different data formats: HTML, XML, and JSON in R. We selected data about three books and stored this data in the three different formats. Subsequently, we wrote R code to load this data into R and convert it into data frames. Selected Data We chose three books related to programming and sof...
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