Data imputation - Samenvattingen, Aantekeningen en Examens

What is inferential statistics? sample > measure values > make inference about whole population What is causal inference? prediction of intervention, missing data imputation In causality, what are all paths that start with an arrow pointing to the independent variable and end with an arrow pointing to the dependent variable (to be controlled) called? back-door paths How can I block back-door paths? include 3rd variables in regression models, matching based on confoundi...

ement is a more accessible alternative to drag & drop reordering. Pres INSTRUCTIONS FOR QUESTIONS 1-5 For each of the following five questions, select the probability distribution that could best be used to model the described scenario. Each distribution might be used, zero, one, or more than one time in the five questions. These scenarios are meant to be simple and straightforward; if you're an expert in the field the question asks about, please do not rely on your expertise to fill in a...

What do descriptive questions ask? What happened? (e.g., which customers are most alike) What do predictive questions ask? What will happen? (e.g., what will Google's stock price be?) What do prescriptive questions ask? What action(s) would be best? (e.g., where to put traffic lights) What is a model? Real-life situation expressed as math. What do classifiers help you do? differentiate What is a soft classifier and when is it used? In some cases, ther...

What do descriptive questions ask? What happened? (e.g., which customers are most alike) What do predictive questions ask? What will happen? (e.g., what will Google's stock price be?) Brainpower Read More 0:05 / 0:15 What do prescriptive questions ask? What action(s) would be best? (e.g., where to put traffic lights) What is a model? Real-life situation expressed as math. What do classifiers help you do? differentiate What is a soft classifier and when is it...

Georgia Tech Est ISYE 6501 Lecture Transcripts, Comprehensive masterpiece. Document Content and Description Below Est ISYE 6501 Lecture Transcripts About This Document This document was originally created in the summer of 2017 and is maintained collaboratively through the efforts of the students of edX GTx ISY E 6501 using transcripts and screenshots from the video lectures. You are strongly encouraged to improve the formatting, layout, add or adjust images, bold key words, and even condense c...

Week 1 Why Analytics? 6 Data Vocabulary 7 Classification 8 Support Vector Machines 11 Scaling and Standardization 13 k-Nearest Neighbor (KNN) 13 Week 2 Model Validation 16 Validation and Test Sets 17 Splitting the Data 18 Cross-Validation 20 Clustering 21 Supervised vs. Unsupervised Learning 22 Week 3 Data Preparation 25 Introduction to Outliers 25 Change Detection 27 Week 4 Time Series Data 31 AutoRegressive Integrated Moving Average (ARIMA) 34 Generalized Autoregressive...

Midterm Quiz 2 - Verified MM Learners Midterm Quiz 2 due Apr 12, 2021 1500 HKT Completed 90 Minute Time Limit Instructions Work alone. Do not collaborate with or copy from anyone else. Work the problems in any order you wish, but submit each answer before ending the exam. You may use any of the following resources: One sheet (both sides) of handwritten (not photocopied or scanned) notes If any question seems ambiguous, use the most reasonable interpretation (i.e. don't be like Calvin)...

Bivariate Statistics - Use of Contingency Table correct answersUsed to detect incompatibilities between variables, links between the dependent ('target') variable and the independent variables and their interactions, in order to eliminate the variables having no effect on the dependent variable; links between the independent variables, which must be avoided in some methods, such as linear and logistic regression. Detection of Rare Variables correct answersRare values can create bias in fac...

Questions 2a, 2b 5.0/10.0 points (graded) Five classi�cation models were built for predicting whether a neighborhood will soon see a large rise in home prices, based on public elementary school ratings and other factors. The training data set was missing the school rating variable for every new school (3% of the data points). Because ratings are unavailable for newly-opened schools, it is believed that locations that have recently experienced high population growth are more likely to have...

Questions 2a, 2b 5.0/10.0 points (graded) Five classification models were built for predicting whether a neighborhood will soon see a large rise in home prices, based on public elementary school ratings and other factors. The training data set was missing the school rating variable for every new school (3% of the data points). Because ratings are unavailable for newly-opened schools, it is believed that locations that have recently experienced high population growth are more likely to have ...