Publications by Yonathan Anggraiwan
CS-Lab4-Hypothesis Testing
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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Optim-Lab4-Solving-Nonlinear-Equations
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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Lab3: Linear Programming Modeling
Case Study 1 Suppose a farmer has 75 acres on which to plant two crops: wheat and barley. To produce these crops, it costs the farmer (for seed, fertilizer, etc.) $120 per acre for the wheat and $210 per acre for the barley. The farmer has $15000 available for expenses. But after the harvest, the farmer must store the crops while awaiting avourab...
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Document
1 Binomial Distribution 1.1 Question What is a binomial distribution in Statistics? What is binomial distribution used for? Please argue 4 requirements needed to be a binomial distribution? Is a binomial distribution a normal distribution? Suppose there are twenty multiple choice questions in an Statistics class quiz. Each question has five pos...
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CS-Lab3-Confidential-Interval
1 Brief Introduction Please watching this video, to get some ideas about Confidence Intervals (CI) 2 CI in Business This video guide you, how can you apply Confidence Intervals in Business. 3 Your Exercise In this section, your expected to get familiar with confidential intervals exercise: 3.1 Exercise 1 Find a point estimate of average univer...
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Optim-Lab5-General Optimization
1 General Optimization In mathematics, nonlinear programming (NLP) is the process of solving an optimization problem where some of the constraints or the objective function are nonlinear. An optimization problem is one of calculation of the extrema (maxima, minima or stationary points) of an objective function over a set of unknown real variables...
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CS-Lab6-Goodness-of-Fit
##7 EXERCISE #7.1 Please work out in R by doing a chi-squared test on the treatment (X) and improvement (Y) columns in treatment.csv. dataEX1 <- read.csv("treatment.csv") table(dataEX1$treatment, dataEX1$improvement) ## ## improved not-improved ## not-treated 26 29 ## treated 35 ...
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Optimization : EM Algorithm
1 Latihan 12 Exepektasi Maksimal Di kelas ini kita akan menerapkan algoritma Expectation Maximization untuk memperkirakan parameter Campuran Gaussian. Metode ini menyediakan pengklasifikasi tanpa pengawasan yang sangat berguna ketika distribusi Gaussian diasumsikan. Misalkan kita ingin memodelkan parameter populasi yang diasumsikan sebagai salah ...
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CS-Lab8-Inference-in-Linear-Regression
1 Inferensial di Regresi Linear Setelah membaca seksi ini, kamu akan bisa: ~Mengerti mengenai distribusi dari suatu estimasi regresi. ~Membuat interval estimasi untuk regresi parameter, respon rata-rata, dan prediksi. ~Menguji signifikan regresinya. Di seksi terakhir, kita memecahkan model regresi linear sederhana, yaitu \[Y_i = β_0 + β_1x_i + ...
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Ujian Akhir Semester
Email: email-anda@gmail.com RPubs: https://rpubs.com/akun-rpubs-anda/ Packages library(dplyr) #data manipulation library(ggplot2) #data visualization library(DT) #beautify the data table library(plotly) #make a pie chart library(Metrics) #find error value library(tidyverse) library(yardstick) library(data.table) l...
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