Publications by Rajwant Mishra, Priya Shaji, Debabrata Kabiraj, Isabel Ramesar, Sin Ying Wong and Fan Xu

DATA 605 02[46835] : Week 13 Discussion

26.04.2020

QUESTION Using R, build a multiple regression model for data that interests you. Include in this model at least one quadratic term, one dichotomous term, and one dichotomous vs. quantitative interaction term. Interpret all coefficients. Conduct residual analysis. Was the linear model appropriate? Why or why not? ANSWER Dataset Using sample car...

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DATA 605 02[46835] : HomeWork Assignment 12

25.04.2020

ASSIGNMENT 12 Problem The attached who.csv dataset contains real-world data from 2008. The variables included follow. Country: name of the country LifeExp: average life expectancy for the country in years InfantSurvival: proportion of those surviving to one year or more Under5Survival: proportion of those surviving to five years or more TBFree:...

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DATA 608 01 [46846] : Module 6 - Assignment 6

22.04.2020

Module 6 GitHub Pages Stream Graph Shiny Server Assignment 6: D3 lab D3.js is a powerful data visualization library. Rather than being based around existing plot types, d3 allows you to bind any html element. This power is a double edged sword. It allows you to build completely custom data visualizations, but because you're dealing with indiv...

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DATA 605 02[46835] : HomeWork Assignment 11

13.04.2020

ASSIGNMENT 11 Problem 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.) Answer Data Exploration help(cars) # Summary of the data summary(cars) ## speed ...

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DATA 605 02[46835] : Week 10 Discussion

04.04.2020

P-Introduction to Probability Chapter 11. Markov Chains 11.2 Absorbing Markov Chains Exercise 15 Page 424 Consider the game of tennis when deuce is reached. If a player wins the next point, he has advantage. On the following point, he either wins the game or the game returns to deuce. Assume that for any point, player A has probability .6 of w...

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DATA 605 02[46835] : HomeWork Assignment 10

04.04.2020

ASSIGNMENT 10 Problem Smith is in jail and has 1 dollar; he can get out on bail if he has 8 dollars. A guard agrees to make a series of bets with him. If Smith bets A dollars, he wins A dollars with probability .4 and loses A dollars with probability .6. Find the probability that he wins 8 dollars before losing all of his money if Answer The Mar...

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DATA 608 01 [46846] : Module 5 - Assignment 5

29.03.2020

Module 5 Beginner: This is one of two homework assignments you can complete for this week (you must do two, you may do all three for extra credit). This is geared towards those of you who have never worked with javascript before. Your assignment should be in the form of an HTML page, which I will be able to run locally. Refer to the file ‘js_i...

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DATA 605 02[46835] : Week 9 Discussion

28.03.2020

P-Introduction to Probability Chapter 9. Central Limit Theorem 9.3 Central Limit Theorem for Continuous Independent Trials Exercise 9 Page 363 How large must \(n\) be before \(S_n = X_1+X_2+...+X_n\) is approximately normal? This number is often surprisingly small. Let us explore this question with a computer simulation. Choose \(n\) numbers f...

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DATA 605 02[46835] : HomeWork Assignment 9

28.03.2020

ASSIGNMENT 9 Chapter 7.2 Exercise #11 page 363 of Probability Text The price of one share of stock in the Pilsdorff Beer Company is given by \(Y_n\) on the \(n\)th day of the year. Finn observes that the differences \(X_n = Y_{n+1} - Y_n\) appear to be independent random variables with a common distribution having mean \(\mu = 0\) and variance \...

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DATA 621 01[46893] : HomeWork3

27.03.2020

Code Show All Hide All DATA 621 Homework #3 Overview Deliverables Data Exploration Missing Values & Data Type Check Data Statistics Summary Consolidated Data Dictionary Data Preparation Re-scale Data Build Models Model 1: Full Model Model 2: Removing predictors seemed Unnecessary Model 3: Removing Highest VIF Values Model 4: Removing Poor P...

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