Fri Mar 14 13:10:19 2014
Approvals Received: 



Approvals Pending:  College/Dean > Provost > Catalog  
Effective Status:  Active  
Effective Term:  1153  Spring 2015  
Course:  AST 4031  
Institution: Campus: 
UMNTC  Twin Cities UMNTC  Twin Cities 

Career:  UGRD  
College:  TIOT  College of Science and Engineering  
Department:  11092  Astrophysics, MN Inst for  
General  
Course Title Short:  Statistical Astrophysics  
Course Title Long:  Statistical Astrophysics  
MaxMin Credits for Course: 
4.0 to 4.0 credit(s)  
Catalog Description: 
Introduction to statistics with applications to modern astrophysics statistical methods to interpret and analyze the large data sets from experiments. Principles and methods of statistical analysis, with applications to current research. For senior undergraduate and graduate students in Physics and Astronomy. 

Print in Catalog?:  Yes  
CCE Catalog Description: 
<no text provided>  
Grading Basis:  AF only  
Topics Course:  No  
Honors Course:  No  
Online Course:  No  
Instructor Contact Hours: 
4.0 hours per week  
Years most frequently offered: 
Other frequency  
Term(s) most frequently offered: 
Spring  
Component 1: 
LEC (no final exam) 

AutoEnroll Course: 
No  
Graded Component: 
LEC  
Academic Progress Units: 
Not allowed to bypass limits. 4.0 credit(s) 

Financial Aid Progress Units: 
Not allowed to bypass limits. 4.0 credit(s) 

Repetition of Course: 
Repetition not allowed.  
Course Prerequisites for Catalog: 
<no text provided>  
Course Equivalency: 
No course equivalencies  
Consent Requirement: 
No required consent  
Enforced Prerequisites: (coursebased or noncoursebased) 
No prerequisites  
Editor Comments:  <no text provided>  
Proposal Changes:  Adding a new course  
History Information:  <no text provided>  
Faculty Sponsor Name: 
Maria Scarlata  
Faculty Sponsor Email Address: 
scarlata@astro.umn.edu  
Student Learning Outcomes  
Student Learning Outcomes: 
* Student in the course:
 Can identify, define, and solve problems
Please explain briefly how this outcome will be addressed in the course. Give brief examples of class work related to the outcome. The students will be able to describe and analyse quantitatively processes, relationships and techniques relevant to the topics included in the course outline, and applying these ideas and techniques to analyze critically and solve advanced or complex problem. In order to address this outcome, I will devote part of the lectures to the analysis of welldefined problems routinely encountered in real astrophysical research. As an example, we will discuss various techniques to compute galaxy luminosity function. How will you assess the students' learning related to this outcome? Give brief examples of how class work related to the outcome will be evaluated. Students capability of identifying and solving complex problems will be assessed via project homework focussed on the application of the statistical tools discussed during the course.  Have mastered a body of knowledge and a mode of inquiry Please explain briefly how this outcome will be addressed in the course. Give brief examples of class work related to the outcome. By the end of the course, students will be able to demonstrate a knowledge and broad understanding of Statistical Astronomy, and show a critical awareness of the significance and importance of the topics, methods and techniques discussed in the lectures and their relationship to concepts presented in other courses. During the lectures the students will actively participate by presenting papers and projects prepared as part of the homework. How will you assess the students' learning related to this outcome? Give brief examples of how class work related to the outcome will be evaluated. Student learning will be assessed via project homework focussed on the application of the statistical tools discussed during the course, and during the final exam.  Can communicate effectively Please explain briefly how this outcome will be addressed in the course. Give brief examples of class work related to the outcome. The students should be able to write down and, where appropriate, either prove or explain the underlying basis of astrophysical laws relevant to the course topics, and discuss their applications. Part of the lectures will be devoted to student presentations and discussion of the project homework. How will you assess the students' learning related to this outcome? Give brief examples of how class work related to the outcome will be evaluated. Students capability of communicating effectively will be evaluated via the written presentations of their homework, and the presentations given in class.  
Liberal Education  
Requirement this course fulfills: 
None  
Other requirement this course fulfills: 
None  
Criteria for Core Courses: 
Describe how the course meets the specific bullet points for the proposed core
requirement. Give concrete and detailed examples for the course syllabus, detailed
outline, laboratory material, student projects, or other instructional materials or method.
Core courses must meet the following requirements:
<no text provided> 

Criteria for Theme Courses: 
Describe how the course meets the specific bullet points for the proposed theme
requirement. Give concrete and detailed examples for the course syllabus, detailed outline,
laboratory material, student projects, or other instructional materials or methods. Theme courses have the common goal of cultivating in students a number of habits of mind:
<no text provided> 

LE RecertificationReflection Statement: (for LE courses being recertified only) 
<no text provided>  
Statement of Certification: 
This course is certified for a Core, effective as of
This course is certified for a Theme, effective as of 

Writing Intensive  
Propose this course as Writing Intensive curriculum: 
No  
Question 1 (see CWB Requirement 1): 
How do writing assignments and writing instruction further the learning objectives
of this course and how is writing integrated into the course? Note that the syllabus must
reflect the critical role that writing plays in the course. <no text provided> 

Question 2 (see CWB Requirement 2): 
What types of writing (e.g., research papers, problem sets, presentations,
technical documents, lab reports, essays, journaling etc.) will be assigned? Explain how these
assignments meet the requirement that writing be a significant part of the course work, including
details about multiauthored assignments, if any. Include the required length for each writing
assignment and demonstrate how the minimum word count (or its equivalent) for finished writing will
be met. <no text provided> 

Question 3 (see CWB Requirement 3): 
How will students' final course grade depend on their writing performance?
What percentage of the course grade will depend on the quality and level of the student's writing
compared to the percentage of the grade that depends on the course content? Note that this information
must also be on the syllabus. <no text provided> 

Question 4 (see CWB Requirement 4): 
Indicate which assignment(s) students will be required to revise and resubmit after
feedback from the instructor. Indicate who will be providing the feedback. Include an example of the
assignment instructions you are likely to use for this assignment or assignments. <no text provided> 

Question 5 (see CWB Requirement 5): 
What types of writing instruction will be experienced by students? How much class
time will be devoted to explicit writing instruction and at what points in the semester? What types of
writing support and resources will be provided to students? <no text provided> 

Question 6 (see CWB Requirement 6): 
If teaching assistants will participate in writing assessment and writing instruction,
explain how will they be trained (e.g. in how to review, grade and respond to student writing) and how will
they be supervised. If the course is taught in multiple sections with multiple faculty (e.g. a capstone
directed studies course), explain how every faculty mentor will ensure that their students will receive
a writing intensive experience. <no text provided> 

Statement of Certification:  This course is certified as Writing Internsive effective as of  
Readme link.
Course Syllabus requirement section begins below


Course Syllabus  
Course Syllabus: 
For new courses and courses in which changes in content and/or description and/or credits
are proposed, please provide a syllabus that includes the following information: course goals
and description; format;structure of the course (proposed number of instructor contact
hours per week, student workload effort per week, etc.); topics to be covered; scope and
nature of assigned readings (text, authors, frequency, amount per week); required course
assignments; nature of any student projects; and how students will be
evaluated. The University "Syllabi Policy" can be
found here
The University policy on credits is found under Section 4A of "Standards for Semester Conversion" found here. Course syllabus information will be retained in this system until new syllabus information is entered with the next major course modification. This course syllabus information may not correspond to the course as offered in a particular semester. (Please limit text to about 12 pages. Text copied and pasted from other sources will not retain formatting and special characters might not copy properly.) AST 4031: Statistical Astrophysics Spring 2015 Instructor: Prof. Claudia Scarlata Tate 355 Phone: 6126261811 email: mscarlat@umn.edu. Text Eric D. Feigelson G Jogesh Babu 2012: Modern Statistical Methods for Astronomy, Cambridge University press (copy are available in the astroreading room) This course is meant for senior undergraduate and graduate students in physics and astronomy. Familiarity with calculus and other basic mathematical techniques is assumed, but no extensive prior knowledge in statistic is required. Modern astrophysics research relies on sophisticated statistical methods to interpret and analyze the large amount of data characteristic of new experiments. In this course, students will learn the key principles and methods of statistical analysis, with applications to current research in astrophysics. Course Content: 1) Part one The first part of the course will cover probability theory and the foundation of statistical inference: overview of probability and random variables discrete and continuous distributions limit theorems Concepts of statistical inference: classical vs. Bayesian statistical inference Maximum likelihood estimation least square method confidence intervals (the Bootstrap and the Jackknife) hypothesis testing techniques probability distribution functions (Binomial, Poissonian, Normal and Lognormal, powerlaw, Gamma) nonparametric statistics: concept of nonparametric inference, univariate problems (KolmogorocSmirnov test). 2) Part two The second part of the course will deal with applied statistical techniques that are based on the foundations presented in part one. These applied techniques include: data smoothing and density estimation: histograms, kernel density estimators, adaptive smoothing regression: leastsquare linear regression, weighted leastsquares, non linear models, model validation, selection and misspecification multivariate analysis: multivariate distances and normal distribution, hypothesis tests, multiple linear regression, principal component analysis, outliers, nonlinear methods; multivariate visualization clustering, classification and data mining: definition and scope of clustering, supervised classification time series analysis: timedomain analysis of evenly and unevenly spaced data; spectral analysis of evenly and unevenly spaced data spatial point processes: tests of uniformity, spatial autocorrelation, modelbased spatial analysis, tessellation. For each applied statistical technique, the astronomical context will be emphasized with examples based on specialized literature. The statistical methods learned during the course will be put into practice using realworld data sets and pythonbased codes. Course Format: Most of the course will be in the form of lectures; a week of the course will be devoted to studentled seminars presenting group projects completed by the students. Grading: Homework 25% Presentations (1 presentations per student) 25% Inclass participation 15% Final exam 35% Any changes in the grading policy or in the syllabus will be communicated to the students. Suggested Book: Zeljko Ivezic, Andrew J. Connolly, Jacob VanderPlas & Alexander Gray Statistics, data mining and Machine learning in Astronomy 2013 Princeton series in modern observational astronomy although this is not required. 

Readme link.
Strategic Objectives & Consultation section begins below


Strategic Objectives & Consultation  
Name of Department Chair Approver: 
Robert Gehrz  
Strategic Objectives  Curricular Objectives: 
How does adding this course improve the overall curricular objectives ofthe unit? A good foundation in astronomical and astrophysical statistics is necessary in contemporary astrophysical research. This material has previously been dispersed in an uncoordinated way amongst other courses and we are now bringing this material together in a more coherent package. 

Strategic Objectives  Core Curriculum: 
Does the unit consider this course to be part of its core curriculum? Yes 

Strategic Objectives  Consultation with Other Units: 
In order to prevent course overlap and to inform other departments of new
curriculum, circulate proposal to chairs in relevant units and followup with direct
consultation. Please summarize response from units consulted and include correspondence. By
consultation with other units, the information about a new course is more widely disseminated
and can have a positive impact on enrollments. The consultation can be as simple as an
email to the department chair informing them of the course and asking for any feedback
from the faculty. <no text provided> 
