My note –

How I do it – First, I was wondering about how statistical data and analysis was being conducted by the economics and business management branches of things where it concerns business –

So, therefore –

I pulled up the statistical data collection and analysis info from the MIT Online CourseWare and opened the notes on Chapter 9

http://ocw.mit.edu/OcwWeb/Sloan-School-of-Management/index.htm

Sloan School of Management

Photo of people in business atire walking on campus.

Photo by Stuart Darsch, Boston

MIT Sloan is a world-class business school long renowned for thought leadership and the ability to successfully partner theory and practice.

MIT Sloan shares a legacy of innovative thinking and collaboration with MIT, and this relationship – unique among business schools – is one that provides tremendous opportunity for students alumni.

At MIT Sloan, customized programs and experiences meet students’ specific needs and help them to reach their personal and professional goals. A commitment to concept-based action learning enables students to gain the experience and skills necessary to enhanced and lead their organizations – and improve the way business is done across the globe.

Sloan School of Management links

Visit the MIT Sloan School of Management home page at:
http://mitsloan.mit.edu/

Find case studies, simulations, deep dives, and industry, business, and country overviews at:
https://mitsloan.mit.edu/mstir/Pages/default.aspx

Review the MIT Sloan School of Management curriculum at:
http://ocw.mit.edu/OcwWeb/web/resources/curriculum/index.htm#15

Updated within the past 180 days

MIT Course # Course Title Term
15.010 Economic Analysis for Business Decisions Fall 2004
15.011 Economic Analysis for Business Decisions Fall 2004
15.012 Applied Macro- and International Economics Spring 2002
15.014 Applied Macro- and International Economics Spring 2004
15.020 Competition in Telecommunications Fall 2003
15.021J Real Estate Economics Spring 2004
NEW
15.023J Global Climate Change: Economics, Science, and Policy Spring 2008
15.024 Applied Economics for Managers Summer 2004
15.040 Game Theory for Managers Spring 2004
15.057 Systems Optimization Spring 2003
15.060 Data, Models, and Decisions Fall 2007
15.062 Data Mining Spring 2003
15.063 Communicating With Data Summer 2003
15.066J System Optimization and Analysis for Manufacturing Summer 2003
15.067 Competitive Decision-Making and Negotiation Spring 2003
15.070 Advanced Stochastic Processes Fall 2005
15.072J Queues: Theory and Applications Spring 2006
15.073J Logistical and Transportation Planning Methods Fall 2004
15.073J Logistical and Transportation Planning Methods Fall 2006
15.081J Introduction to Mathematical Programming Fall 2002
15.082J Network Optimization Spring 2003
15.083J Integer Programming and Combinatorial Optimization Fall 2004
15.084J Nonlinear Programming Spring 2003
15.084J Nonlinear Programming Spring 2004
15.085J Fundamentals of Probability Fall 2005
15.093 Optimization Methods (SMA 5213) Fall 2004
15.094J Systems Optimization: Models and Computation (SMA 5223) Spring 2004
15.098 Special Seminar in Applied Probability and Stochastic Processes Spring 2006
15.099 Readings in Optimization Fall 2003
15.136J Principles and Practice of Drug Development Fall 2005
15.220 Global Strategy and Organization Spring 2008
15.223 Global Markets, National Policies, and the Competitive Advantages of Firms Fall 2007
15.224 Global Markets, National Politics and the Competitive Advantage of Firms Spring 2003
NEW
15.225 Economy and Business in Modern China and India Spring 2008
15.269 Literature, Ethics and Authority Fall 2005
15.269B Literature, Ethics and Authority Fall 2002
15.280 Communication for Managers Fall 2002
15.281 Advanced Managerial Communication Spring 2004
15.289 Communication Skills for Academics Spring 2002
15.301 Managerial Psychology Laboratory Spring 2003
15.301 Managerial Psychology Laboratory Fall 2004
15.301 Managerial Psychology Fall 2006
15.310 Managerial Psychology Laboratory Spring 2003
15.310 Managerial Psychology Laboratory Fall 2004
15.310 Managerial Psychology Fall 2006
15.311 Organizational Processes Fall 2003
15.316 Building and Leading Effective Teams Summer 2005
15.322 Leading Organizations II Fall 2003
15.328 Team Project Fall 2003
15.341 Individuals, Groups, and Organizations Fall 2006
15.342J Organizations and Environments Fall 2004
15.343 Managing Transformations in Work, Organizations, and Society Spring 2002
15.347 Doctoral Seminar in Research Methods I Fall 2004
15.348 Doctoral Seminar in Research Methods II Spring 2004
15.351 Managing the Innovation Process Fall 2002
NEW
15.351 Managing Innovation and Entrepreneurship Spring 2008
15.352 Managing Innovation: Emerging Trends Spring 2005
15.356 How to Develop “Breakthrough” Products and Services Spring 2004
15.358 The Software Business Fall 2005
NEW
15.369 Corporate Entrepreneurship: Strategies for Technology-Based New Business Development Fall 2007
15.389 G-Lab: Global Entrepreneurship Lab Fall 2007
15.391 Early Stage Capital Fall 2003
15.394 Designing and Leading the Entrepreneurial Organization Spring 2003
15.402 Finance Theory II Spring 2003
15.414 Financial Management Summer 2003
15.426J Real Estate Finance and Investment Fall 2006
15.427J Real Estate Capital Markets Spring 2007
15.428J Advanced Topics in Real Estate Finance Spring 2007
15.431 Entrepreneurial Finance Spring 2002
15.433 Investments Spring 2003
15.501 Introduction to Financial and Managerial Accounting Spring 2004
15.511 Financial Accounting Summer 2004
15.514 Financial and Managerial Accounting Summer 2003
15.515 Financial Accounting Fall 2003
15.516 Introduction to Financial and Managerial Accounting Spring 2004
15.518 Taxes and Business Strategy Fall 2002
15.521 Management Accounting and Control Spring 2003
15.535 Business Analysis Using Financial Statements Spring 2003
15.561 Information Technology Essentials Spring 2005
15.564 Information Technology I Spring 2003
15.565J Integrating eSystems & Global Information Systems Spring 2002
15.566 Information Technology as an Integrating Force in Manufacturing Spring 2003
15.571 Generating Business Value from Information Technology Spring 2007
15.575 Research Seminar in IT and Organizations: Economic Perspectives Spring 2004
15.578J Integrating eSystems & Global Information Systems Spring 2002
15.598 IT and Business Transformation Spring 2003
15.616 Innovative Businesses and Breakthrough Technologies – The Legal Issues Fall 2004
15.617 The Law of Corporate Finance and Financial Markets Spring 2004
15.628 Patents, Copyrights, and the Law of Intellectual Property Spring 2003
15.649 The Law of Mergers and Acquisitions Spring 2003
15.660 Strategic HR Management Spring 2003
15.665B Power and Negotiation Fall 2002
15.667 Negotiation and Conflict Management Spring 2001
NEW
15.676 Work, Employment, and Industrial Relations Theory Spring 2008
15.677J Urban Labor Markets and Employment Policy Spring 2005
15.678J Political Economy I: Theories of the State and the Economy Fall 2005
15.760A Operations Management Spring 2002
15.760B Introduction to Operations Management Spring 2004
15.761 Operations Management Summer 2002
15.762J Supply Chain Planning (SMA 6305) Spring 2005
15.763J Manufacturing System and Supply Chain Design Spring 2005
15.764 The Theory of Operations Management Spring 2004
15.769 Operations Strategy Spring 2003
15.769 Operations Strategy Fall 2005
15.770J Logistics Systems Fall 2006
15.778 Management of Supply Networks for Products and Services Summer 2004
15.783J Product Design and Development Spring 2006
15.792J Proseminar in Manufacturing Fall 2005
15.795 Seminar in Operations Management Fall 2002
15.810 Marketing Management Fall 2004
15.810 Introduction to Marketing Spring 2005
15.812 Marketing Management Fall 2002
15.818 Pricing Spring 2005
15.821 Listening to the Customer Fall 2002
15.822 Strategic Marketing Measurement Fall 2002
15.834 Marketing Strategy Spring 2003
15.835 Entrepreneurial Marketing Spring 2002
15.840 Special Seminar in Marketing: Marketing Management Spring 2004
15.871 System Dynamics for Business Policy Fall 2003
15.874 System Dynamics for Business Policy Fall 2003
15.875 Applications of System Dynamics Spring 2004
15.902 Strategic Management I Fall 2006
15.904 Strategic Management II Fall 2005
15.905 Technology Strategy Spring 2007
15.912 Technology Strategy Spring 2005
15.928 Strategic Management and Consulting Proseminar: Theoretical Foundations Spring 2003
15.963 Organizations as Enacted Systems: Learning, Knowing and Change Fall 2002
15.963 Management Accounting and Control Spring 2007
NEW
15.963 Advanced Strategy Spring 2008
15.965 Ethical Practice: Professionalism, Social Responsibility, and the Purpose of the Corporation Spring 2007
15.967 Managing and Volunteering In the Non-Profit Sector Spring 2005
15.968 The Sociology of Strategy Spring 2005
15.969 Dynamic Leadership: Using Improvisation in Business Fall 2004
15.970 Digital Anthropology Spring 2003
15.971 Developmental Entrepreneurship Fall 2003
15.974 Leadership Lab Spring 2003
15.974 Practical Leadership Fall 2004
15.975 Special Seminar in Management The Nuts and Bolts of Business Plans January (IAP) 2005
15.978 Leadership Tools and Teams: A Product Development Lab Spring 2007
15.980J Organizing for Innovative Product Development Spring 2007
15.988 System Dynamics Self Study Fall 1998
15.990 Architecture and Communication in Organizations Fall 2003
NEW
15.992 S-Lab: Laboratory for Sustainable Business Spring 2008
15.996 Cross-Cultural Leadership Fall 2004
15.997 Advanced Corporate Risk Management Spring 2007

^ Back to top

15.075 Applied Statistics

Spring 2003

Image comparing statistics and probability.

Diagram showing the difference between statistics and probability. (Image by MIT OpenCourseWare. Based on Gilbert, Norma. Statistics. W.B. Saunders Co., 1976.)

Course Highlights

Material in 15.075 is presented through its comprehensive set of lecture notes. Students receive hands-on experience with statistical software through the assignments and with examples in the lecture notes.

Course Description

This course is an introduction to applied statistics and data analysis.  Topics include collecting and exploring data, basic inference, simple and multiple linear regression, analysis of variance, nonparametric methods, and statistical computing. It is not a course in mathematical statistics, but provides a balance between statistical theory and application. Prerequisites are calculus, probability, and linear algebra.We would like to acknowledge the contributions that Prof. Roy Welsch (MIT), Prof. Gordon Kaufman (MIT), Prof. Jacqueline Telford (Johns Hopkins University), and Prof. Ramón León (University of Tennessee) have made to the course material.

*Some translations represent previous versions of courses.

Donate Now

Staff

Instructor:
Dr. Elizabeth Newton

Course Meeting Times

Lectures:
Two sessions / week
1.5 hours / sessionRecitations:
One session / week
1 hour / session

Level

Undergraduate

*Translations

Feedback

Send feedback on this course.

Find out how much your company uses OCW.

http://ocw.mit.edu/OcwWeb/Sloan-School-of-Management/15-075Applied-StatisticsSpring2003/CourseHome/index.htm

**

My note –

Then I chose to click over to the lecture notes rather than download the course materials right now because I’m looking for specific comparisons of thought in how data and analysis are approached and handled thereafter, particularly in economics, financial and business orientations.

I also thought that in order to interact, answer questions or initiate a dialogue, I needed a quick access portal for possibilities (Oxford, et al.) – so, I opened the Institute for Study Abroad social blog and applications portals to hold on standby (by putting the word “Scotland” in the Google search and grabbing the appropriate picture.)

****

http://www.ifsa-butler.org/for-students/deadlines/application-deadlines.html

** My Note –

when I have work that I’m doing – a standby through access portals, either for information / data bases or for social networks where answers or access can be found for answers makes sense for me. Its another tab or two or fourteen.

I usually want to know first what resources and source materials were used for the information that I am about to view – not always, but most of the time it helps me to a.) have a better understanding of their viewpoint, and b.) to have those resource materials handy and available quickly in case there is something I don’t understand and need to look up using those reference materials. Normally, I post the list over to a word document as I go along where I can jump up to the list if I need it and resource it online, if available or look for specific published papers and documents by those same authors.

– cricketdiane, 04-03-09

****

Related Resources

Here is a list of books that Dr. Newton placed on reserve for the course. For weekly readings in the course textbook, see the readings page.

Albright, S. C., W. L. Winston, and C. J. Zappe. Managerial Statistics. Duxbury, 2000.

Delwiche, L. D. and S. J. Slaughter. The Little SAS® Book: A Primer. 2nd ed. SAS® Publishing, 1998.

Draper, N. and H. Smith. Applied Regression Analysis. 3rd ed. Wiley, 1998.

Getting Started With the SAS® System: Version 8. SAS® Publishing, 1999.

Hand, D., H. Mannila, and P. Smyth. Principles of Data Mining. MIT Press, 2001.

Hastie, T., R. Tibshirani, and J. Friedman. The Elements of Statistical Learning: Data Mining, Inference and Prediction. Springer, 2001.

Hildebrand D., and R. L. Ott. Statistical Thinking for Managers. 4th ed. Duxbury, 1998.

Hosmer, D. W., and S. Lemeshow. Applied Logistic Regression. 2nd ed. Wiley, 2000.

Johnson, R. A., and D. W. Wichern. Applied Multivariate Statistical Analysis. 4th ed. Prentice-Hall, 1998.

Montgomery, D. C., E. A. Peck, and G. G. Vining. Introduction to Linear Regression Analysis. 3rd ed. Wiley, 2001.

Myers, R. H. Classical and Modern Regression with Applications. 2nd ed. Duxbury, 1990.

Neter, J., M. Kutner, C. Nachtsheim, and W. Wasserman. Applied Linear Statistical Models. 4th ed. Irwin, 1996.

Ott, L., M. Longnecker, R. Lyman Ott. An Introduction to Statistical Methods and Data Analysis. 5th ed. Duxbury, 2000.

Rawlings, J. O. Applied Regression Analysis: A Research Tool. 2nd ed. Springer, 1998.

Rice, J. A. Mathematical Statistics and Data Analysis. 2nd ed. Duxbury, 1995.

Tamhane, A. and D. Dunlop. Statistics and Data Analysis. Prentice Hall, 2000.

SAS® and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries. ® indicates USA registration.

**

Lecture Notes

The lecture notes reference the 15.075 course textbook: Statistics and Data Analysis from Elementary to Intermediate by Ajit C. Tamhane and Dorothy D. Dunlop, Prentice Hall, 2000. They also occasionally refer to: Casella, George, and Roger L. Berger. Statistical Inference. Belmont, CA: Duxbury Press, 1990.

Some slides were prepared by or based on slides by: Prof. Roy Welsch (MIT), Prof. Gordon Kaufman (MIT), Prof. Jacqueline Telford (Johns Hopkins University), and Prof. Ramón León (University of Tennessee). These contributions have been acknowledged on the first slide of each lecture.

LEC # TOPICS
1 Introduction and Collecting Data (PDF)
2 Summarizing and Exploring Data (PDF – 1.4 MB)
3 Summarizing and Exploring Data (See PDF file in Lecture 2)
4 Review of Probability (PDF)
5 Sampling Distributions (PDF)
6 Basic Concepts of Inference (PDF)
7 Inference for Single Samples (PDF)
8 Inference for Two Samples (PDF)
9 Inference for Proportion and Count Data (PDF)
10 Review and Examples (PDF)

Inference in a Nutshell (PDF)

11 Midterm Exam
12 Simple Linear Regression and Correlation (PDF)
13 Simple Linear Regression and Correlation (See PDF file for Lecture 12)
14 Multiple Linear Regression (PDF)
15 Multiple Linear Regression (See PDF file for Lecture 14)

Logistic Regression (PDF)

Regression Review and Robust Regression (PDF)

16 ANOVA – single factor (PDF)
17 ANOVA – single factor (See PDF file for Lecture 16)
18 ANOVA – multifactor (PDF)
19 ANOVA – multifactor (See PDF file for Lecture 18)
20 Nonparametric Methods (PDF)
21 Nonparametric Methods (See PDF file for Lecture 20)
22 Special Topics
23 Special Topics
24 Review and Examples (PDF)
25 Final Exam

**
My note – and then I chose to take a quick review and try to understand this one from the list above –

http://ocw.mit.edu/NR/rdonlyres/Sloan-School-of-Management/15-075Applied-StatisticsSpring2003/91C6DAF6-E101-480D-BF39-6C67CD6C664B/0/lec9_chap9.pdf

Which was:

INFERENCE FOR PROPORTION AND COUNT DATA – from Chapter 9 (Lecture Notes)

http://ocw.mit.edu/NR/rdonlyres/Sloan-School-of-Management/15-075Applied-StatisticsSpring2003/EEF9C9C0-1AF7-4DD0-A6DE-C7566709CA2C/0/lec12_chap10.pdf

Page 10 Fitted Regression and thereafter –

from: Simple Linear Regression and Correlation – Lecture Notes

pp. 24  Statistical Inference (ETC> all info on this page)

***

My Note –

Then, I wanted to compare this information with what I’ve found in Materials Science Engineering and some other applications of data array management and analysis – so:

***

http://ocw.mit.edu/NR/rdonlyres/Sloan-School-of-Management/15-075Applied-StatisticsSpring2003/91C6DAF6-E101-480D-BF39-6C67CD6C664B/0/lec9_chap9.pdf

A Better Confidence Interval for Proportion
Use this probability statement

pp. 4

Inference for Count Data

pp. 18

pp. 15 Test for Equality of Proportional Relationship
Test for Equality of Proportions (Large n) Independent Sample Design – pooled estimate of p

Comparing Two Proportions: Independent Sample Design – pp, 14

Inferences for Two-Way Count Data

pp. 20 – 21

Remarks About Chi-Square Test
• The distribution of the chi-square statistics under the null hypothesis is approximately chi-square only when the sample sizes are large
– The rule of thumb is that all expected cell counts should be greater
than 1 and –No more than 1/5th of the expected cell counts should be less than
5.

• Combine sparse cell (having small expected cell counts) with adjacent cells. Unfortunately, this has the drawback of losing some information.
• Never stop with the chi-square test. Look at cells with large values of (O-E), as in job satisfaction example.

Pp.27

Inference for Small Samples
Fisher’s Exact Test

Calculates the probability of obtaining observed 2×2 table or any more extreme with margins fixed.

Uses hypergeometric distribution

pp. 17

*****

http://ocw.mit.edu/OcwWeb/Materials-Science-and-Engineering/index.htm

Materials Science and Engineering

Combustion synthesis of fullerenes and fullerenic nanostructures.

Combustion synthesis of fullerenes and fullerenic nanostructures. Courtesy Vander Sande Lab

Students, professors, and researchers in the Department of Materials Science and Engineering explore the relationships between structure and properties in all classes of materials including metals, ceramics, electronic materials, and biomaterials.

Our research leads to the synthesis of improved materials in response to challenges in the areas of energy, the environment, medicine, and manufacturing.

Collaborating with industry, government, and other institutions, our research contributes to a broad range of fields. In a recent U.S. Army-funded study, we used nanotechnological methods to study the structure of scales of the fish Polypterus senegalus, leading to more effective ways of designing human body armor. In the MIT and Dow Materials Engineering Contest (MADMEC), student teams design and prototype devices to harness, store, and exploit alternative energy sources. With support from the Lord Foundation, the purchase of advanced equipment will allow us to build custom experimental equipment, develop and test prototypes, and even make a new part for an unmanned air vehicle.

Our educational programs interweave concepts of materials engineering and materials science throughout the curriculum. Core subjects offered at both undergraduate and graduate levels cover topics necessary for all DMSE students:

  • Thermodynamics
  • Kinetics
  • Materials structure
  • Electronic and mechanical properties of materials
  • Bio- and polymeric materials
  • Materials processing

This core foundation and appropriate electives lead to a variety of opportunities in engineering, science, or a combination of the two.

Department of Materials Science and Engineering links

Visit the MIT Department of Materials Science and Engineering home page at:
http://dmse.mit.edu/

Review the MIT Department of Materials Science and Engineering curriculum at:
http://ocw.mit.edu/OcwWeb/web/resources/curriculum/index.htm#3

Atomic Control Software allows users to create crystal structures, manipulate them in three dimensional space on their desktop, and simulate x-ray diffraction patterns of the crystals.
http://pruffle.mit.edu/atomiccontrol/

Learn more about MIT Engineering:
http://engineering.mit.edu/

Updated within the past 180 days

MIT Course # Course Title Term
3.00 Thermodynamics of Materials Fall 2002
3.012 Fundamentals of Materials Science Fall 2005
3.014 Materials Laboratory Fall 2006
3.016 Mathematics for Materials Scientists and Engineers Fall 2005
3.021J Introduction to Modeling and Simulation Spring 2006
3.032 Mechanical Behavior of Materials Fall 2007
3.034 Organic & Biomaterials Chemistry Fall 2005
NEW
3.042 Materials Project Laboratory Spring 2008
3.044 Materials Processing Spring 2005
3.051J Materials for Biomedical Applications Spring 2006
3.052 Nanomechanics of Materials and Biomaterials Spring 2007
3.053J Molecular, Cellular, and Tissue Biomechanics Fall 2006
3.063 Polymer Physics Spring 2007
3.064 Polymer Engineering Fall 2003
3.080 Economic & Environmental Issues in Materials Selection Fall 2005
3.091 Introduction to Solid State Chemistry Fall 2004
3.093 Information Exploration: Becoming a Savvy Scholar Fall 2006
3.094 Materials in Human Experience Spring 2004
3.14 Physical Metallurgy Fall 2003
3.15 Electrical, Optical & Magnetic Materials and Devices Fall 2006
3.155J Micro/Nano Processing Technology Fall 2005
3.172 Inventions and Patents Fall 2005
3.185 Transport Phenomena in Materials Engineering Fall 2003
3.986 The Human Past: Introduction to Archaeology Fall 2006
3.987 Human Origins and Evolution Spring 2006
3.A08 Attraction and Repulsion: The Magic of Magnets Fall 2005
3.A26 Freshman Seminar: The Nature of Engineering Fall 2005
3.A27 Case Studies in Forensic Metallurgy Fall 2007

^ Back to top

***

Coefficient of Determination (R-squared) – pp. 27

Geometry of the Sums of Squares) – pp. 26

Regression DiagnosticsResidual vs. observation number – pp. 29

Inference for Small Samples
Fisher’s Exact Test pp. 17

http://ocw.mit.edu/NR/rdonlyres/Sloan-School-of-Management/15-075Applied-StatisticsSpring2003/91C6DAF6-E101-480D-BF39-6C67CD6C664B/0/lec9_chap9.pdf

http://ocw.mit.edu/NR/rdonlyres/Sloan-School-of-Management/15-075Applied-StatisticsSpring2003/EEF9C9C0-1AF7-4DD0-A6DE-C7566709CA2C/0/lec12_chap10.pdf

****

Then –

3.60 Symmetry, Structure, and Tensor Properties of Materials

Fall 2005

Schematic of molecular crystal structure.

Crystal structure of the cuprate compound Bi2Sr2CaCu2O8+δ or Bi2212, showing the copper (purple)–oxygen (black) layer responsible for superconductivity. (Image courtesy of Lawrence Berkeley Laboratory.)

Course Highlights

This course features a complete set of video lectures, plus many readings and assignments.

Course Description

This course covers the derivation of symmetry theory; lattices, point groups, space groups, and their properties; use of symmetry in tensor representation of crystal properties, including anisotropy and representation surfaces; and applications to piezoelectricity and elasticity.

Special Features

Technical Requirements

Special software is required to use some of the files in this course: .rm, .mp3.

**

Readings

Amazon logo Help support MIT OpenCourseWare by shopping at Amazon.com! MIT OpenCourseWare offers direct links to Amazon.com to purchase the books cited in this course. Click on the Amazon logo to the left of any citation and purchase the book from Amazon.com, and MIT OpenCourseWare will receive up to 10% of all purchases you make. Your support will enable MIT to continue offering open access to MIT courses.

This section contains documents created from scanned original files, which are inaccessible to screen reader software. A “#” symbol is used to denote such documents.

Readings are mix of Professor Wuensch’s original handouts and other published materials, presented here in the order used in class. The individual original handouts are also published here as compiled notes.

Several readings are from the books:
[TABLES_52] Norman, F. M., and Kathleen Lonsdale, eds. International Tables for X-Ray Crystallography. Vol. 1. Birmingham, UK: The Kynoch Press, 1952.

Amazon logo [TABLES_83] Hahn, Theo, ed. International Tables for Crystallography. Vol. A. New York, NY: Springer-Verlag, 1983. ISBN: 9789027715326.

Crystallography Readings

Amazon logo Buerger, Martin J. Elementary Crystallography: An Introduction to the Fundamental Geometrical Features of Crystals. Cambridge, MA: MIT Press, 1978, chapters 1-9. ISBN: 9780262520485.

Principles of Plane Group Derivation (PDF)#

“The 17 Two-Dimensional Space Groups: Equivalent Positions, Symmetry and Possible Reflections.” Section 4.2 in [TABLES_52].

Distribution of Lattice Types, Point Groups and Plane Groups Among the Two-Dimensional Crystal Systems (PDF)#

Spherical Trigonometry (PDF)#

Derivation of the 32 Crystallographic Point Groups, or Crystal Classes (PDF)#

“The 32 Three Dimensional Point Groups.” Table 3.3 in [TABLES_52].

Demonstration of 2-fold and 3-fold Axes (PDF)#

Tables d, f, and g in Nowacki, W. “Crystal Data – Systematic Tables.” Monograph 6, 2nd Edition. Buffulo, NY: American Crystallographic Association, 1967.

Summary of 2-Dimensional Plane Groups in Preparation for Addition of a Stacking Vector to Produce a Space Lattice (PDF)#

Derivation of the Space Lattices (PDF)#

Lattice Transformations (PDF)#

Distribution of Lattice Types and Point Groups Among the Crystal Systems (PDF)#

Symbols for the Locus of a Glide Plane (PDF)#

Single Page Summary of Logic and Combination Theorems Used to Derive Space Groups (PDF)#

The Monoclinic Space Groups. pp. 76-101 In [TABLES_52].
This reading illustrates how the three-dimensional space groups are systematically derived by adding each of the point groups in a particular crystal system — and with pure rotation replaced by a screw axis and/or a mirror plane by a glide plane — to each of the space lattices that are able to accomodate them.

“A short explanation of the space-group data (cf. Section 2.2).” In [TABLES_83].

Excerpts from “The 230 Space Groups.” pp. 420-422, 473, 590-591, 648-649, 662-663, 670-703. In [TABLES_83].

Symbols for All Possible Orientations of the 230 Space Groups. Table 6.2.1, pp. 545-553. In [TABLES_52].

Summary Notes on the Crystalline State (PDF)#

“Packing Considerations.” In Wuensch, B. J. “Determination, Relationships and Classification of Sulfide Mineral Structures.” Chapter 1 in Sulfide Mineralogy: Reviews in Minerology. Vol. 1. Chantilly, VA: Mineralogical Society of America, 1974.

Derivative Structures (PDF)#

Tensor Properties Readings

Propagation of Waves Along One-Dimensional Crystal with Two Kinds of Atoms (PDF)#

Wave Propagation in a Continuous One-Dimensional Medium (PDF)#

Propagation of Elastic Waves in Crystals (PDF)#

Stiffness vs. Temperature (PDF)#

Conventions for Relabeling Stress, Strain, Stiffness and Compliance in Matrix Notation (PDF)#

Symmetry Restrictions for 4th Rank Property Tensors (PDF)#

Some Basic Relations in Electromagnetism (PDF)#

Stress and Strain Tensors (PDF)#

Some Solutions to 3rd Order Equations (PDF)#

2nd Rank Tensors and the Representation Quadric (PDF)#

Tensor Properties of Crystals and Anisotropy (PDF)#

Professor Wuensch’s Compiled Notes

These two files are compilations of the above individual readings files.

Crystallography Notes (PDF – 2.1 MB)#

Tensor Properties Notes (PDF – 2.3 MB)#

****
My note –
I select these two from the list – because I believe the comparative information will be easily found and quickly available –

Propagation of Waves Along One-Dimensional Crystal with Two Kinds of Atoms (PDF)#

Wave Propagation in a Continuous One-Dimensional Medium (PDF)#

****

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