Core Methods in Educational Data Mining HUDK4050 Fall 2015.

Slides:



Advertisements
Similar presentations
Non-Experimental designs: Developmental designs & Small-N designs
Advertisements

Advanced Methods and Analysis for the Learning and Social Sciences PSY505 Spring term, 2012 March 12, 2012.
Core Methods in Educational Data Mining HUDK4050 Fall 2014.
NATIONAL DEFENSE INTELLIGENCE COLLEGE Measuring Forecaster Performance Lt Col James E. Kajdasz, Ph.D., USAF.
Data Mining Methodology 1. Why have a Methodology  Don’t want to learn things that aren’t true May not represent any underlying reality ○ Spurious correlation.
Relationship Mining Correlation Mining Week 5 Video 1.
10 -1 Lecture 10 Association Rules Mining Topics –Basics –Mining Frequent Patterns –Mining Frequent Sequential Patterns –Applications.
Advanced Methods and Analysis for the Learning and Social Sciences PSY505 Spring term, 2012 April 18, 2012.
Core Methods in Educational Data Mining HUDK4050 Fall 2014.
Discovery with Models Week 8 Video 1. Discovery with Models: The Big Idea  A model of a phenomenon is developed  Via  Prediction  Clustering  Knowledge.
Biostatistics Case Studies 2006 Peter D. Christenson Biostatistician Session 5: Reporting Subgroup Results.
Applied statistics Katrin Jaedicke
Non-Experimental designs: Developmental designs & Small-N designs
ML ALGORITHMS. Algorithm Types Classification (supervised) Given -> A set of classified examples “instances” Produce -> A way of classifying new examples.
Classification of Remotely Sensed Data General Classification Concepts Unsupervised Classifications.
Core Methods in Educational Data Mining HUDK4050 Fall 2014.
Core Methods in Educational Data Mining HUDK4050 Fall 2014.
B.Ramamurthy. Data Analytics (Data Science) EDA Data Intuition/ understand ing Big-data analytics StatsAlgs Discoveries / intelligence Statistical Inference.
Core Methods in Educational Data Mining HUDK4050 Fall 2014.
Case Study – San Pedro Week 1, Video 6. Case Study of Classification  San Pedro, M.O.Z., Baker, R.S.J.d., Bowers, A.J., Heffernan, N.T. (2013) Predicting.
Core Methods in Educational Data Mining HUDK4050 Fall 2014.
PSSA Cohort Analysis by CORE AREAS Classes:
Chapter 11 Business Intelligence Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall 11-1.
Core Methods in Educational Data Mining HUDK4050 Fall 2014.
Special Topics in Educational Data Mining HUDK5199 Spring term, 2013 March 27, 2013.
Core Methods in Educational Data Mining HUDK4050 Fall 2014.
Core Methods in Educational Data Mining HUDK4050 Fall 2014.
Non-Experimental designs
Core Methods in Educational Data Mining HUDK4050 Fall 2014.
Core Methods in Educational Data Mining HUDK4050 Fall 2014.
Special Topics in Educational Data Mining HUDK5199 Spring term, 2013 March 13, 2013.
Core Methods in Educational Data Mining HUDK4050 Fall 2014.
Core Methods in Educational Data Mining HUDK4050 Fall 2015.
Core Methods in Educational Data Mining HUDK4050 Fall 2015.
Core Methods in Educational Data Mining HUDK4050 Fall 2015.
The Call of the Wild Reading Response Journals. DUE: TUESDAY, 9/29/15.
Special Topics in Educational Data Mining HUDK5199 Spring term, 2013 March 6, 2013.
Core Methods in Educational Data Mining HUDK4050 Fall 2015.
Core Methods in Educational Data Mining HUDK4050 Fall 2014.
Core Methods in Educational Data Mining HUDK4050 Fall 2015.
Core Methods in Educational Data Mining HUDK4050 Fall 2015.
Web Analytics Xuejiao Liu INF 385F: WIRED Fall 2004.
Core Methods in Educational Data Mining HUDK4050 Fall 2014.
Special Topics in Educational Data Mining HUDK5199 Spring, 2013 April 3, 2013.
Core Methods in Educational Data Mining HUDK4050 Fall 2014.
Basic Research Terms and Methods Goals of psychological research Measurement and description of behavior Understanding and prediction of behavior Application.
Core Methods in Educational Data Mining HUDK4050 Fall 2015.
Core Methods in Educational Data Mining HUDK4050 Fall 2014.
Core Methods in Educational Data Mining HUDK4050 Fall 2014.
Special Topics in Educational Data Mining HUDK5199 Spring term, 2013 April 15, 2013.
IMPACT EVALUATION PBAF 526 Class 5, October 31, 2011.
HCS 465 Week 4 Individual Evaluating the Research Process To purchase this material click below link
Core Methods in Educational Data Mining
Advanced Methods and Analysis for the Learning and Social Sciences
Core Methods in Educational Data Mining
DATA MINING © Prentice Hall.
Chapter 8 Using secondary data
Core Methods in Educational Data Mining
Introduction to Data Mining
Core Methods in Educational Data Mining
Core Methods in Educational Data Mining
Big Data, Education, and Society
Core Methods in Educational Data Mining
Core Methods in Educational Data Mining
Big Data, Education, and Society
Core Methods in Educational Data Mining
Core Methods in Educational Data Mining
Core Methods in Educational Data Mining
Core Methods in Educational Data Mining
Today we are going back in time to help us predict the future!!!
Presentation transcript:

Core Methods in Educational Data Mining HUDK4050 Fall 2015

Assignment

Q1-Q3 Within data set 1, how many correlations are statistically significant (according to the customary p<0.05 definition) – If you do not apply any sort of post-hoc control? – If you use Bonferroni – If you use Benjamini&Hochberg

Q4 What is the correlation with the lowest p- value that comes up significant for B&H but not for Bonferroni?

Q5-Q7 Within data set 2, how many correlations are statistically significant (according to the customary p<0.05 definition) – If you do not apply any sort of post-hoc control? – If you use Bonferroni – If you use Benjamini&Hochberg

Q8 What is the lowest correlation that is still statistically significant, according to Bonferroni’s test?

Why were the “lowest significant correlations” so different between data sets?

Q9 Question 9: Now do you see why Professor Baker says that statistical significance doesn’t matter much for really big data sets? (and this is NOT a big data set by reckoning in other fields) Yes – Bonferroni is ridiculously conservative with 1,112 tests, and yet correlations that are absurdly small still come up statistically significant. No. I think the answer to Question 9 is a fine correlation, perfectly likely to represent a large effect size. No. Big data is a FAD. No one should ever expect to work with a data set over 150 data points, especially after the societal collapse predicted by James Howard Kunstler occurs.

Today… We’ll discuss discovery with models

Discovery with Models What is discovery with models?

Discovery with Models How is it used in prediction? How is it used in relationship mining?

Discovery with Models Why do we need a special term for it? (Do we need a special term for it?)

Advantages & Disadvantages What are some of the advantages and disadvantages of discovery with models?

Questions or comments?

Questions or comments about Dawson et al. case study?

Questions or comments about Hershkovitz et al. paper?

Questions or comments about Fancsali paper?

Any other questions about discovery with models?

Assignment B7 Clustering Any questions?

Next Class Tuesday, November 17 Baker, R.S. (2015) Big Data and Education. Ch. 7, V1, V2, V3, V4, V5. Amershi, S. Conati, C. (2009) Combining Unsupervised and Supervised Classification to Build User Models for Exploratory Learning Environments. Journal of Educational Data Mining, 1 (1), Bowers, A.J. (2010) Analyzing the Longitudinal K-12 Grading Histories of Entire Cohorts of Students: Grades, Data Driven Decision Making, Dropping Out and Hierarchical Cluster Analysis. Practical Assessment, Research & Evaluation (PARE), 15(7), 1-18.

The End