Georgia Institute of Technology
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All courses for Georgia Institute of Technology
- ID 2242 ID 2242 2
- ISYE 6501 ISYE6501 53
- ISYE 6501 Final Quiz - Summer 2018 - Verified Learners ISYE6501 4
- ISYE 6501 Final Quiz Summer 2018 1
- ISYE 6501 Midterm Quiz 1 with all the Correct Answers ISYE 6501 Midterm Quiz 1 with all the Correct Answers 4
- ISYE 6501 MIDTERM QUIZ 2 2
- ISYE 6501 WEEK 1 HOMEWORK – SAMPLE SOLUTIONS ISYE 6501 WEEK 1 HOMEWORK – SAMPLE SOLUTIONS 6
- ISYE 6501/ISYE6501 ISYE6501 2
- ISYE 6501X ISYE6501X 29
- ISYE 6501x Midterm Quiz 1 - Audit Learners 2
- ISYE 6501X Verified Learners Final Quiz 2
- ISYE 6644 ISYE 6644 14
- ISYE 6644 Week 12 Homework Simulation 2019 ISYE6644 1
- MGT 2210 1
- MGT 2210 Information Systems and Digital Transformations MGT 2210 1
- MGT 6203 13
- MGT 6203 /MGT 6203 FINAL EXAM 2
- Midterm Quiz 1 - Audit Learners | Midterm Quiz 1 - Audit Learners | ISYE6501x Courseware | edX 1
- Midterm Quiz 2 - GT Students and Verified MM Learners _ Midterm Quiz 2 _ ISYE6501x Courseware _ edX ISYE6501 2
Latest notes & summaries Georgia Institute of Technology
Quiz #1 
Due Jan 29 at 10:59pm Points 5 Questions 5 
Available Jan 13 at 7am - Jan 29 at 10:59pm Time Limit 40 Minutes 
Instructions 
This quiz was locked Jan 29 at 10:59pm. 
Attempt History 
Attempt Time Score 
LATEST Attempt 1 30 minutes 5 out of 5 
Score for this quiz: 5 out of 5 
Submitted Jan 29 at 10:39pm 
This attempt took 30 minutes. 
Warning: this is the real quiz that counts 5% of your final course grade. You can take this quiz once 
and only once! In particular, once you start the qui...
ISyE7406 – HOMEWORK 4 
Spring 2023 
1. Introduction 
In this homework, we will examine how various local smoothing methods estimate the 
“Mexican hat function” at various points in the interval [-2π, 2π]. Using these methods, 
we will be able to better understand how bias, variance, and mean square error of these 
estimators perform given different spans, bandwidths, and local smoothing parameters. 
2. Exploratory Data Analysis 
The Mexican hat function is defined in the range [-2π, 2π...
ISYE 7404 
2 
Introduction 
The objective of this assignment is to study how well three distinct local smoothing techniques (LOESS, 
Nadaraya-Watson (NW) kernel smoothing, and Spline Smoothing) perform on a simulated additive noise model. 
�� = �(�) + ��, 
Consuming the Mexican Hat function 
�(�) = (1 − �2 
) exp(−0.5�2 
), where � � [-2�, 2�]. 
In the additive noise model, the error terms follow a normal distribution with mean 0 and standard deviation 0.2, and ar...
HW2 
Introduction 
Work with “fat” data set and apply 7 linear regression models to the data set. For each model, find out 
the testing error. Since the data set is small, apply Monte Carlo Cross Validation to all the models and 
find out the average Testing error for each model after 100 loops. 
Exploratory Data Analysis 
The “fat” data set has 252 observations and 18 variables. The first column “brozek” is the dependent 
variable representing the percentage of body fat. The rest 17...
Phys2211 Class Notes | These Are Phys2211 Classnotes for year 2023-24
Phys2211 Class Notes | These Are Phys2211 Classnotes for year 2023-24
Phys2211 Class Notes | These Are Phys2211 Classnotes for year 2023-24
Phys2211 Class Notes | These Are Phys2211 Classnotes for year 2023-24
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These are classnotes of Phys2211, year 2023-24