I a new to coding and I didnt realize how much time it would take to over come erros. I need some clarification on the work I have already started and I want to compare it to your code so I can move on to the next subject. If you do a good job I will always pick you for the rest of the year. I am kinda in a rush because my assignment is already 1 and a half past due. I have included some code below that my instructor provided but I dont know if it similar to the assignment csv file I have uploaded in a zip file. If you have more questions please let me know. IChapter 14: Word Perfect (page 174 – 186 of “An Introduction to Data Science” by Jeffrey Saltz and Jeffrey Stanton# ———– Chapter 14: Chapter 14: Word Perfect ———–library(XML)library(tm)#read the speech – the actual file location will need to be updatedsbaFile <- “/Users/jsaltz/Google Drive/Courses/IST 687/2U/Week 8 – Text Mining/data/sba-speech.txt”sbaFile <-read.csv(“sample.csv”, stringsAsFactors = F )head(sbaFile) sbaFile <-sbaFile$texthead(sbaFile)#use scan#sba <- scan(sbaFile, character(0),sep = “n”)#sba <- scan(sbaFile, character(0))#head(sba, 10)#use readLines# sba <- readLines(sbaFile)# head(sba, 3)#Use a web file: Note the web location for the speechsbaLocation <- URLencode(“http://www.historyplace.com/speeches/anthony.htm”)# Read and parse HTML filedoc.html = htmlTreeParse(sbaLocation, useInternal = TRUE)# Extract all the paragraphs (HTML tag is p, starting at# the root of the document). Unlist flattens the list to# create a character vector.sba = unlist(xpathApply(doc.html, ‘//p’, xmlValue))head(sba, 3)words.vec <- VectorSource(sba)words.corpus <- Corpus(words.vec)words.corpuswords.corpus <- tm_map(words.corpus, content_transformer(tolower))words.corpus <- tm_map(words.corpus, removePunctuation)words.corpus <- tm_map(words.corpus, removeNumbers)words.corpus <- tm_map(words.corpus, removeWords, stopwords(“english”))tdm <- TermDocumentMatrix(words.corpus)tdmm <- as.matrix(tdm)wordCounts <- rowSums(m)wordCounts <- sort(wordCounts, decreasing=TRUE)head(wordCounts)library(wordcloud)cloudFrame <- data.frame(word = names(wordCounts), freq=wordCounts)wordcloud(cloudFrame$word, cloudFrame$freq)wordcloud(names(wordCounts), wordCounts, min.freq=2, max.words=50, rot.per=0.35, colors=brewer.pal(8, “Dark2”))

Data Science , R programming wordcloud

## net force, physics questions

net force, physics questions.

What is the net force exerted by these two charges on a third charge q3 = 55.0 nC placed between q1and q2 at x3 = -1.130 m ?q3=At what separation is the electrostatic force between a +11.9 μC point charge and a +29.2 μC point charge equal in magnitude to 1.95 N?r=When two identical ions are separated by a distance of 2.0×10−10 m , the electrostatic force each exerts on the other is 5.5×10−9 N. How many electrons are missing from each ion?Ne=

net force, physics questions

## Unit VII Article Critique

help me with my homework Unit VII Article Critique.

As a leader, it is expected for you to be able to identify with the workers within the organization. This process can take place

during basic observation, performance evaluations, attendance, interaction with others, and basic characteristics or

behaviors. The leader must identify different personality types or behaviors and apply the suggested tactics for properly

handling each type. Research the CSU Online Library or another external source for an article(s) that addresses different personality types or

behaviors in the work place and how to apply tactics for properly handling of each type.

Provide your opinion on the article as it applies to the following questions: What is the author’s main point? Who is the author’s intended audience? Do the author’s arguments support his or her main point? Explain different personality types or behaviors and how to

apply the suggested tactics for properly handling of each type. What evidence supports the main point? What is your opinion of the article? (Do not simply summarize the article.) What evidence, either from the textbook or additional sources, supports your opinion? Your article critique should be at least two pages in content length, including an introduction, a body of supportive material

(paragraphs), and a conclusion. Be sure to include a title page and a reference page and follow all other APA formatting

requirements. The title page and reference page do not count toward the total page requirement.

Unit VII Article Critique

## Colorado Technical University Investing in A Surging Stock Market Discussion

Colorado Technical University Investing in A Surging Stock Market Discussion.

Unit: Investment AnalysisDue Date: Tue,8/4/20Grading Type: NumericPoints Possible: 60Points Earned: Points Earnednot availableDeliverable Length: 400-600 wordsView objectives for this assignmentGo To:Assignment DetailsLearning MaterialsReading AssignmentMy Work:Online Deliverables: Discussion BoardLooking for tutoring? Go to SmarthinkingAssignment DetailsAssignment DescriptionPrimary Discussion Response is due by Friday (11:59:59pm Central), Peer Responses are due by Tuesday (11:59:59pm Central).What are the 7 steps to follow when investing in a surging stock market?Use the CTU library to select and read the article for this discussion. Be sure to first review: the instructions for accessing the WSJ.To answer this week’s question, locate the following articles (see below) by visiting ProQuest/Source Type: Newspapers/Publication title: Wall Street Journal (online)The Surging Stock Market: Too Late to Buy?; How to Think About Investing When Prices Are This HighArends, Brett. Wall Street Journal (Online); New York, N.Y. [New York, N.Y]21 June 2014: n/a.For assistance with your assignment, please use your text, Web resources, and all course materials.

Colorado Technical University Investing in A Surging Stock Market Discussion

## Let x, y, and z denote the three coordinate axes in the three dimensional space R3 . A point p ∈ R3 is specified by its coordinates along the three axes: p = (x(p), y(p), z(p)). For p, q ∈ R3 , we say

A point p ∈ R3 is specified by its coordinates along the three axes: p = (x(p), y(p), z(p)). For p, q ∈ R3 , we say that p is dominated by q, if x(p) ≤ x(q), y(p) ≤ y(q) and z(p) ≤ z(q). Let S = {p0, p1, . . . , pn−1} be a set of n points in R3 . pi ∈ S is called a maximal element of S, if pi is not dominated by any other element of S. The set of all maximal elements of S is denoted by maxima(S). The maxima problem is: Given S, find maxima(S). You will write an efficient program to solve this problem, using the C or Java Standard Library functions. One brute-force algorithm to solve this problem is as follows: Compare each point pi ∈ S against all the other points in S to determine if pi is dominated by any of those points; if pi is not dominated by any of them, add it to the output set maxima(S). This algorithm takes Θ(n) time for each point pi , for a total of Θ(n 2 ) time. You will implement an efficient algorithm that is expected to run in Θ(n log n) time. The program must be in C or Java only. This handout discusses the implementation in C , using the Standard Template Library (STL). The algorithm consists of three steps. I. Input: The point set S is in an input file. The first line contains the value of n (the number of points). Following that, there will be n lines, each line containing the x, y and z coordinates of one point. The points must be read and stored in an array P OINT S[0..(n − 1)] of POINT objects. The P OINT S[i] object corresponds to point pi , and has four fields: the x, y and z-coordinates (all double); the boolean field maximal indicating whether or not the point is maximal. II. Sorting: Sort the points (i.e., the array P OINT S) according to their z-coordinates, and reindex them such that z(p0) ≤ z(p1) ≤ . . . ≤ z(pn−1). The sorting must be done using the sort library function: sort(POINTS, POINTS n); this requires that you implement the operator x(q). If x(pi) > x(q), add pi to maxima(S); also, we need to update the BST so that it represents maxima2[i..n]. The update of the BST is done as follows: First, consider the nodes in the BST whose y-coordinates are less than y(pi), in decreasing order of their y-coordinates; delete them one-by-one, until you come across a point p with x(p) > x(pi). Finally, insert pi into the BST. Each insertion or deletion in a BST takes time Θ(height of the tree). To achieve the Θ(n log n) runtime, the above BST must be a height-balanced binary search tree: At any istant, the height of the tree is Θ(log of number nodes in the tree). One example of such a tree is Red-Black Tree (see Chapter 13 in the text book). You will use the STL data structure map. It is implemented as a Red-Black Tree. In the class, I will explain how to use map. Variable M axNum has the number of elements in M axima(S). Print out M axNum and M axima(S). For each point in M axima(S), also print out its array index (i.e., the index of the point in P OINT S array). Your program should be modular, and contain appropriate procedures/functions. No comments or other documentation is needed. Use meaningful names for all variables. You will run your program on 10 different sets of points; your program should have a loop for this. All the point sets are in the input file infile.txt. The name of your program file must be maxima.[cpp or java] (corresponding to C or Java programs, respectively); the name of your output file must be outfile.txt.