USP/PLSI493: Methods of Planning Data Analysis (4 credits)Urban Studies and Planning Program Professor Ayse PamukSan Francisco State University_____________________________________________________Fall 2017

Tuesdays and Thursdays 11Ό0 - 12:15 (HSS 219 - computer lab)

Professor Pamuk’s office hours: Tuesdays 2-3pm HSS 136; Thursdays 4:45-5:45pm DTC 678A Mailbox: HSS 261, Voicemail: 415-338-7045, Email: namuk@sfsu.edu

Course materials and messages will be posted on iLearn.sfsu.edu

Teaching Assistants: Andrew Humphries ahumnhri@mail.sfsu.eduTA office hours: Tuesdays 4-5pm HSS 272 Isaiah Xavier Gonzalez isaiahg@mail.sfsu.edu TA office hours: TBA

Course Description

USP/PLSI 493 is the second course in the USP 492 (Research Methods)--USP 493 (Data Analysis) course sequence. For pedagogical reasons, it should be taken after completing USP 492 or equivalent (e.g., PLSI 300). Concurrent enrollment is not allowed. For USP majors a passing grade is С or better (No Incomplètes). It is a lecture and computer lab course (with some online hybrid components) designed to introduce Urban Studies and Planning majors (and others interested in professional applied training in social science and public policy analysis) to a range of commonly used quantitative methods of analysis in urban policy and planning. The course emphasizes the use of various practical methods appropriate to analyzing planning and policy problems and building a conceptual framework for reasoning about planning and policy issues. Methods for analyzing primary and secondary data are introduced. Statistical formulas are downplayed. The use of computers as tools for data analysis and spatial analysis is emphasized.

The course is organized into three parts. Part One covers an introduction to spatial analysis of data using ArcGIS 10.4.1. Part Two focuses on the analysis of secondary data including census data on population and housing with Excel. The use of descriptive statistics is introduced with examples of public policy applications of GIS using U.S. and international census data. Part Three focuses on the analysis of primary data with SPSS (e.g. gathered through surveys) including inferential statistics, bivariate measures of association, and multivariate analysis.

Lectures and computer lab exercises will start with introductory material and will gradually add new layers of information. Therefore, it is very important to follow all readings, lectures, and lab exercises to complete the requirements of this course successfully. The course requires a steady and regular level of effort (required attendance and required reading of assigned books and materials) throughout the semester.

Prerequisites

USP 492 (Research Methods) or PLSI 300 or equivalent.

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Student learning objectives

At the end of the semester, students who complete the requirements of this course successfully should be able to:

■ Have a foundation in critical thinking and reasoning skills based on data!■ Understand data retrieval from a wide range of reliable public and private sources

for analysis!■ Gain proficiency in empirical analysis (working with numbers);■ Understand basic statistical concepts (percentage change, mean, median,

percentiles) and use them to discover patterns in data!■ Understand complex urban problems by analyzing data rather than through

anecdotal information;■ Construct and test research hypotheses with data!■ Undertake local census data analysis at the census tract level (compare them to

countydevel data) and prepare community profiles!■ Understand different sampling strategies (probability versus non-probability

samples) and appropriate use of data from each;■ Distinguish descriptive, exploratory, and explanatory research from one another!■ Undertake simple brvariate and multivariate data analysis■ Analyze data using spreadsheets (Excel) and SPSS!■ Analyze data spatially with ArcGIS!■ Analyze data statistically with SPSS!■ Gain proficiency in a range of GIS methods in urban analysis.■ Communicate analysis results visually in a Power Point presentation and written

reports.

Data Files

CIS data files (on a CDROM) for the CIS assignments come with the Mapping Global Cities book. The same date files are also on the shared drive in HSS 219. Other useful links to data in the public domain are listed at online.sfsu.edu/pamuk/data.html. Please bring a USB drive (4G) to class to copy assignment files as instructed. ArcGIS 10.4.1 for desktop student license authorization codes will be provided for you to install it on your personal desktop or laptop PC. Those with Mac computers need to install additional software (available from Apple) on their machines.

Required readings

The following books are available at the University bookstore at SFSU and/or on two-hour reserve at the SFSU library.

Feon-Guerrero, Anna and Chava Frankfort-Nachmi as (2015) Essentials of Social Statistics for a Diverse Society. Fos Angeles: Sage Publications, Inc.

Pamuk, Ayse. Mapping Global Cities'- GIS Methods in Urban Analysis. Redlands, CA: ESRI Press, 2006.

Additional materials are placed on E-reserve, which can be accessed through iFearn.

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USP/PLSI493: Methods of Planning Data Analysis (4 credits)Urban Studies and Planning Program Professor Ayse PamukSan Francisco State University____________________________________________________ Fall 2017

Assignments, Exams, and Grading

There will be 2 short assignments involving computer analysis over the course of the semester, and a final project, including a Power Point presentation. Late paper penalty is .50 points per day (out of a total of 10 points for Assignment #1, for example). Students are expected to complete all readings before each class meeting, and bring required material to computer lab sessions. Attendance and punctuality in all classes and labs are required. Excessive absences in class may result in a failing grade. During class and lab time (in HSS 219) students are expected to shut down all electronic distractions (e.g., cell phone, email, social media) and focus on USP 493 material. Assignments are due no later than midnight on the date when they are due (on iLearn only in one file). See dates below.

1. Assignment L Spatial analysis with ArcGIS (10%) (Sep. 7)2. Assignment 2'· Demographic analysis with US census data (census-tract level analysis)

(15%) (Oct. 5)3. Final project: Combining statistical and spatial analyses

Part A (15%) (Oct. 24)Part В (25%) PowerPoint presentation (Dec. 7 & Dec. 12) - alphabetical order by lastname! No shows will not earn credit) Early presenters on Dec. 5 will earn extra credit.Part С (20%) (Dec. 14)

4. Class participation (15%)

Computer lab policies - message from the CHSS IT Department

There is absolutely no food or drinks allowed in the CHSS Computer Lab spaces - not even during classes (this includes coffee and water bottles). Please leave all food and drinks outside - if you have closed water bottles, those can be kept in the bags/backpacks.

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USP/PLSI 493: Methods of Planning Data Analysis (4 credits)Urban Studies and Planning Program Professor Ayse PamukSan Francisco State University_____________________________________________________Fall 2017

Message from the College of Health & Social Sciences,

Welcome. This section is to inform you of the College and University policies that may affect you. Knowledge of these deadlines (viewed at http ://registrar. sfsu .edu/') and policies will help you to navigate the bureaucracy of the University while helping you succeed and graduate in a timely manner. Policies can be intimidating sometimes, but they ensure an equitable, consistent and reliable process for each student. Please review this information and refer to http://chss.sfsu.edu/content/petitions-information for more detail on these policies. Approval of a petition from the instructor and/or Department Chair does not constitute automatic approval from the Associate Dean so please continue attending class until a decision is made. If you have any questions about how these policies specifically apply to your situation, please contact the Associate Dean's Office at assocdeaiTri,sfsu.edu or in HSS 239.

When is the deadline to drop a class?

The last day to drop a class without a W grade is September 13. 2017 bv 11:59 PM.

What if I wish to withdraw from a course after the drop deadline?

Withdrawal from a course is allowed from September 14. 2017 until November 17. 2017 only if you have serious and compelling reasons with current, relevant supporting documentation. The following are examples of non-serious and non-compelling reasons and would be denied:

• Changing major• Poor academic performance in class• Course no longer needed• Missing pre-requisite(s)• Instructor forgot to drop• More time needed for other classes

Unexpected changes in work schedule or serious accident, protracted illness, or family emergencies may be considered serious and compelling if appropriate supporting documentation is attached. The petition must be submitted within a reasonable timeframe (e.g., within 2 weeks of an illness or change in work hours) and must include your unofficial transcripts. From November 18. 2017 until December 12. 2017. you may not withdraw from a class or the University, except only in the case of a documented serious illness or verified accident.

Withdrawals cannot be initiated electronically and must be submitted using a paper application. A maximum of 18 units can be withdrawn, and a course can only be repeated once with a failing grade.

How do I take a course for Credit or No Credit (CR/NC) Grade?

Please check the course description in the Bulletin to determine if the class can be taken CR/NC. If it is permitted, then you may change your grading option via your SF State Gateway until October 18. 2017 bv 11:59 PM. The Associate Dean will not approve requests for changes if you miss this deadline.

What if I want to add a class after registration closes?

The period to add classes via permission numbers is August 23. 2017 through September 13. 2017 until 11:59 PM. It is your responsibility to obtain a late permission number from your instructor and add the class. Faculty

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cannot add you into a class. Starting September 14. 2017. a Waiver of College Regulations form must be submitted. This will only be approved if there was an administrative error.

How do I know if any changes in my registration went through?

Always check your registration on your SF State Gateway after making any changes and before deadlines to ensure you are registered properly for your classes. It is always your responsibility to ensure your schedule is correct, even if the instructor indicates they will drop you. All deadlines will be strictly adhered to by the instructor, the Department Chair, and the CHSS Associate Dean.

When are finals?

According to Academic Senate policy F76-12 a time period is set aside at the end of each semester for a formal examination period. All classes are expected to meet during the final examination period whether an examination is given or not. The final examination schedule is: http : //www. sfsu. edu/~acadre s/final exams/finalf 17 .htm

What resources are available to me on campus?

Disability Programs and Resource Center: Students with disabilities who need reasonable accommodations are encouraged to contact the instructor. The Disability Programs and Resource Center (DPRC) is available to facilitate the reasonable accommodations process. The DPRC, located in SSB 110, can be reached by telephone at 415-338-2472 (voice/TTY) or by e-mail at dprc@sfsu.edu.

Student Disclosures of Sexual Violence: SF State fosters a campus free of sexual violence including sexual harassment, domestic violence, dating violence, stalking, and/or any form of sex or gender discrimination. If you disclose a personal experience as an SF State student, the course instructor is required to notify the Dean of Students. To disclose any such violence confidentially, contact:

The SAFE Place - (415) 338-2208; http://www.sfsu.edu/~safe_plc/

Counseling and Psychological Services Center - (415) 338-2208; http://psyservs.sfsu.edu/For more information on your rights and available resources: http://titleix.sfsu.edu

CHSS Student Resource Center (HSS 254): Provides academic advising and support to all students with a CHSS major. For more information and to book advising appointment: http://chss.sfsu.edu/src or call (415) 405-3740.

Undergraduate Advising Center (ADM 212): Provides academic advising and support to all students. For more information: https://advising.sfsu.edu/.

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A note about academic integrity, plagiarism, and student conduct

What is plagiarism?

“Plagiarism is generally defined as "presentting] the ideas or words of another as one's own." (MerrianrWebster Dictionary, 378) While people often focus on unattributed direct quotation of material, plagiarism also includes making minor changes in wording or sentence structure that repeats essentially the same concept as the original statement. Words, charts, drawings, computer programs or any other creative work can be plagiarized. Undisputed common knowledge can be cited without attribution.”

“Plagiarism is defined as the act of using the ideas or work of another person or persons as if they were one's own without giving proper credit to the source. Such an act is not plagiarism if it is ascertained that the ideas were arrived through independent reasoning or logic or where the thought or idea is common knowledge. Acknowledgement of an original author or source must be made through appropriate references! i.e., quotation marks, footnotes, or commentary. Examples of plagiarism include, but are not limited to the following: the submission of a work, either in part or in whole completed by another! failure to give credit for ideas, statements, facts or conclusions which rightfully belong to another! failure to use quotation marks when quoting directly from another, whether it be a paragraph, a sentence, or even a part thereof! close and lengthy paraphrasing of another's writing without credit or originality! use of another's project or programs or part thereof without giving credit.”

Source: http://conduct.sfsu.edu/Olagiarism

Please familiarize yourself with the likely consequences of plagiarism by reading the SFSU Standards for Student Conduct http://conduct.sfsu.edu/standards

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USP/PLSI493: Methods of Planning Data Analysis (4 credits)Urban Studies and Planning Program Professor Ayse PannikSan Francisco State University____________________________________________________ Fall 2017

Course Outline

Introduction to course and requirements (week 1)

Part Г Exploring global metropolitan regions with GIS (weeks 2 and 3)

Part II: Descriptive statistics with secondary data (weeks 4-9)

• Accessing and analyzing U.S. census data• Statistics in social science research• Census data analysis• Urban planning and policy applications of GIS using census data• Analyzing spatial patterns in metropolitan areas with GIS• Understanding demographics• Introduction to survey research methods• Working with Excel

Part IIP Inferential statistics using survey data (weeks 10-15)

• Working with SPSS• The Normal curve, distribution, sampling, and sampling distribution• Estimation procedures and confidence intervals• Hypothesis testing (one sample)• Hypothesis testing (two samples)• Identification of differences and similarities between groups of observations• Correlation among variables• Introduction to regression• Working with SPSS & ArcGIS together

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USP/PLSI493: Methods of Planning Data Analysis (4 credits)Urban Studies and Planning Program Professor Ayse PamukSan Francisco State University_____________________________________________________Fall 2017

Detailed Course Schedule

Introduction to course and requirements

WEEK 1 (Aug. 24)

■ What is data and data analysis?■ Importance of up-to-date and accurate data for informed public- and

private-sector decision making■ Data Sources on the Internet: an overview

Lab Activity #P Introduction to Data Sources for Urban Planners and Policy Analysts (international, national, regional, 9-county Bay Area, and San Francisco)

http://online.sfsu.edu/~pamuk/data.html

Assignment #L Spatial analysis with ArcGIS handed out (due: Sep. 7)

PART I: Exploring global metropolitan regions with GIS. Spatial analysis with ArcGIS and an introduction to U.S. and international census data

WEEK 2 (Aug. 29 and Aug. 31)

Combining Data Analysis with Spatial Analysis

■ What is GIS?■ Asking geographic questions■ 2000 and 2010 decennial census data■ American Community Survey data■ CIS in public policy■ Using CIS in analyzing cities in a global world■ Using CIS to solve public policy problems—identifying the need for Head

Start services in San Francisco■ Spatial data

Required Readings

Pamuk, Ayse 2006. Introduction and Chapter L Using GIS to analyze cities in a globalworld In Mapping Global Cities, pp. 1-45.

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Lab Activity # 2'· Pamuk, Ayse (2006) GIS Exercise #L “Create a thematic map using Brazil census data” Data on Mapping Global Cities CD

WEEK 3 (Sep. 5 and Sep. 7) Working with spatial data

Required Reading

Pamuk, Ayse. 2006. Chapter % Spatial Data. In Mapping Global Cities, pp. 47-66.

Lab Activity # 3: Exercise #2: “Spatializing non-spatial data” Data on Mapping Global Cities CD.____________________________________________________________________

IĮ ^Assignment # 1 due (Sen. 7) on iLearn

PART II: Descriptive statistics with secondary data

Week 4 (Sep. 12 and Sep. 14)

Accessing and analyzing U.S. census data

■ Local area analysis with census data■ Bottom up orientation■ Census sampling frame: all known addresses in the U.S.■ What is census data good for?

• Measuring changes over time• Comparing places

■ ( Ammon/typical questions answered by census data• Overall growth• Composition or make-up of local population

■ Census geography• Hierarchical structure• Definitions

■ Population vs sample■ Structure of datasets\linkages\questionnaire (short and long form)■ Universe\base\population concepts■ Comparability of boundaries over time■ STF3A (Summary Tape Files for 1990) vs printed tables■ SF1, SF3 (Census 2000)■ Census 2010■ American Community Survey data

Assignment # 2 handed out: Demographic analysis of a SF census tract, 2000-2010 (due: Oct. 5).

Required Reading

Myers, Chapter L “Introduction” (pages 1-9) Chapter 2'· “Using census data for localportraits” (pages 13-31), Chapter 3: “Concepts, definitions, and linkages” (pages 33-

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61), and part of Chapter 4- “Data available for local area analysis” (pages 63-82 only) (on e-reserve)

Lab Activity # 4- Exercise 2a: Working with 2010 census data and GIS.

WEEK 5 (Sep. 19 and Sep. 21)

Statistics in Social Science Research

■ Theory, Research (exploratory, descriptive, explanatory), and Data Analysis■ Levels of measurement: ordinal, categorical, continuous■ Types of variables: dependent and independent■ Measurement scales■ Distributions■ Basic descriptive statistics■ Indices■ Univariate analysis of data■ Percentages, proportions, frequencies, ratios, rates■ Measures of central tendency to summarize/describe the distribution of a

single variable: Mode, median, mean■ Percentiles■ Standardizing data

Required Readings

Leon-Guerrero, Anna and Chava Frankfort-Nachmias (2015), Chapter L “The what and the why of statistics” Chapter 2- “The organization and graphic presentation of data! Chapter 3: “Measures of central tendency”

Lab Activity # 5: Creating Excel tables showing change in demographics in a SF census tract (absolute change, percent change, percentage point change).

WEEK 6 (Sep. 26 and Sep. 28)

Census data analysis. Urban Planning & Policy Applications of GIS using census data■ Analysis of local housing conditions at the census tract level■ Population age structure (age pyramids)■ Household relationships■ Population pyramids at the census tract level■ International comparisons■ Age group versus cohort■ Cohort retention

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Required Readings

Pamuk, Ayse. 2006. Chapter 3: “Urban planning applications of GIS in local government” pp. 69-92. Chapter 4- “GIS Analysis in Planning Social Delivery, pp. 93-105 in Mapping Global Cities.

Myers, Chapter 6: “Local housing conditions” (pages 129-150); Chapter 8: “Population age structure” (pages 151-188) “Chapter 10: “Racial composition and change” (pages 207-233) (on e-reserve)

Lab Activity #6: Pamuk (2006) GIS Exercise #3: Analyze vector data using US census date (Data on Mapping Global Cities CD).

WEEK 7 (Oct. 3 and Oct. 5)

Open lab sessions working on Assignment #2

G Assignment #2 due (Oct. 5) on iLearn

WEEK 8 (Oct. 10 and Oct. 12)

Analyzing Spatial Patterns in Metropolitan Areas with GIS

Lab Activity #7: GIS exercise #5- “Create new information.” Data on Mapping Global Cities CD.

Required Readings

Pamuk, Ayse. 2006. Chapter 5: “Locating immigrant clusters with census data.” pp. 109- 127. Chapter 6: “Comparing immigrant clustering patterns across metropolitanareas”

Final proiect handed out (Part A due: Oct. 24; Part B: due: Dec. 7 and Dec. 12; Part С due: Dec. 14) Early presenters (Dec. 5) will earn extra credit.

WEEK 9 (Oct. 17 and Oct. 19)

Open lab session: Working on Part A of the final project.

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PART IIP Inferential statistics using survey data

WEEK 10 (Oct. 24 and Oct. 26)

The Normal Curve. Distribution, Sampling, and Sampling Distribution, Confidence intervals

■ Measures of dispersion (range, percentile ranks, standard deviation)■ Shape of the distribution (e.g., normal)■ Central limit theorem■ The normal curve (standardized theoretical curve)■ Z'scores■ Concept of probability■ Sampling distribution - theoretical basis for inferential statistics■ Standard deviation of the sampling distribution■ Strategies to reduce nonsampling error■ Confidence intervals

Required Readings

Leon-Guerrero, Anna and Chava Frankfort-Nachmias (2015), Chapter 4- “Measures of variability” Chapter 5: “The normal distribution” Chapter 6: “Sampling and sampling distributions” Chapter 7- “Estimation”

How to Use a Statistical Package (on iLearn, titled SPSS Basics)

II ^ Final project Part A due Oct. 24 on iLearn

WEEK 11 (Oct. 31 and Nov. 2)

Hypothesis (significance) testing (one sample)

■ Hypothesis testing■ One- and two-tailed tests■ Student’s t (small samples)

Required Readings

Pamuk, Ayse. 2006. “Comparing immigrant clustering patterns across metropolitan areas.” In Mapping Global Cities, pp. 129-152.

Leon-Guerrero, Anna and Chava Frankfort-Nachmias (2015), Chapter 8: “Testing hypotheses”

И ) Lab Activity #8'· Recoding Variables in SPSS and descriptive statistics for the new variables (creating an income level variable)

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WEEK 12 (Nov. 7 and Nov. 9)

Hypothesis (significance) testing (two samples),

■ Measures of association■ Bivariate tables■ Chi square test for independence

Required Readings

Leon-Guerrero, Anna and Chava Frankfort-Nachmias (2015), Chapter 9: “Bivariate tables”

Lab Activity #9- Crosstabs and measures of association with SPSS

WEEK 13 (Nov. 14 and Nov. 16)

Open lab sessions working on the final project

November 21 and Nov. 23 - FALL RECESS

WEEK 14 (Nov. 28 and Nov. 30)

Introduction to regression (bi-variate and multivariate)

■ Correlation■ Causality■ Scatterplots■ Bi-variate and multiple regression

Required Readings

Leon-Guerrero, Anna and Chava Frankfort'Nachmias (2015), Chapter 10: “Analysis of Variance” Chapter 11 “Regression and correlation”

Lab Activity #10: Regression analysis with SPSS

Lab Activity #11: Pamuk (2006) GIS Exercise #6: Self-directed project: Planning in the new global metropolis. Data on Mapping Global Cities CD.

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WEEK 15 (Dec. 5 and Dec. 7)

О Final proiect Part В (Power Point presentations) due: Dec. 7 on iLearn Early presentations (Dec. 5) for extra credit)

ОWeek 16 — Dec. 12 — Part В presentations continued.

Final project part С due no later than midnight on Dec. 14 on iLearn.

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