Publications by Jerrel
Week 6
library(ggplot2) library(dplyr) ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:base': ## ## intersect, setdiff, setequal, union library(tidyr) library(ggthemes) 1 Exercise 1.1 Exercise 1 Please work out in R by doing...
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Week 3
# Case Study 2 A manufacturing manager is in charge of minimizing the total costs (raw materials, labor and storage costs) of the following four months. In Table 3.1 can be found the cost of raw materials of one unit of final product, the demand of final product and the working hours available for each month. Labor costs are of 12 e per hour, an...
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Week 2
1 Binomial Distribution 1.1 Question What is a binomial distribution in Statistics? What is binomial distribution used for? Please argue 4 requirements needed to be a binomial distribution? Is a binomial distribution a normal distribution? Suppose there are twenty multiple choice questions in an Statistics class quiz. Each question has five pos...
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Week 3
library(MASS) 1 Brief Introduction Please watching this video, to get some ideas about Confidence Intervals (CI) 2 CI in Business This video guide you, how can you apply Confidence Intervals in Business. 3 Your Exercise In this section, your expected to get familiar with confidential intervals exercise: 3.1 Exercise 1 Find a point estimate of...
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Week 4
1 Bisection Method The bisection method is another approach to finding the root of a continuous function \(f(x)\) on an interval \([a,b]\). The method takes advantage of a corollary of the intermediate value theorem called Bolzano’s theorem which states that if the values of \(f(a)\) and \(f(b)\) have opposite signs, the interval must contain a...
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Week 4
1 Introduction As a data scientist you probably retain or reject hypothesis based on measurements of observed samples. The decision is often based on a statistical mechanism called hypothesis testing. Let’s watching the following video: There are three conditions of having hypothesis testing included: Left Tailed Test: When the \(\bar{x}\) is...
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Week 5
1 General Optimization In mathematics, nonlinear programming (NLP) is the process of solving an optimization problem where some of the constraints or the objective function are nonlinear. An optimization problem is one of calculation of the extrema (maxima, minima or stationary points) of an objective function over a set of unknown real variables...
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Week 6
1 Praktek 12: Ekspektasi Maksimalisasi Dalam kelas ini kita akan menggunakan algoritma Ekspektasi Maksimalisasi untuk mengestimasi parameter Campuran Gaussian. Metode ini menyediakan pengklasifikasi yang tidak terjaga dan sangat berguna ketika distribusi Gaussian diasumsukan. Misalkan kita ingin memodelkan parameter populasi yang diasumsikan menj...
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Week 8
1 Find the maximum solution to \[Z=4x+3y\] Suppose that the objective function is subject to the following constraints: \[\begin{equation*} x \ge 0\\ y \ge 2\\ 2y \le 25-x\\ 4y \le 2x-8\\ y \le 2x-5\\ \end{equation*}\] Solve this problems using mathematical model and R packages (please explain it step-by-step). library(lpSolve) # Set t...
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Week 8
1 Interferensi dalam Regresi Linier Setelah membaca bab ini, anda akan dapat: Memahami distribusi estimasi regresi. Membuat interval untuk parameter regresi, responden rata-rata, dan prediksi. Menguji taraf signifikansi suatu regresi. Dalam bab sebelumnya, anda sudah menegaskan model dari regresi linear sederhana, \[Y_i = \beta_0 + \beta_1 x_i ...
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