Geography of Eau Claire Thrift Sale Two Hypothesis: 1) Thrift sales will correlate with lower income home owners 2) Thrift sales will correlate with median.

Slides:



Advertisements
Similar presentations
KI 2: Where are people distributed within urban areas?
Advertisements

1 The Inequitable Distribution of Tobacco Outlets in Maryland: Race or Income? David O. Fakunle, BA Doctoral Student Johns Hopkins Bloomberg School of.
Diver Acquisition Project - Phase I Profile of the Most Active Divers in the US; Lifestyle and Demographic Study.
Statistics on Obesity, PA & Diet: England, Jan 08 i Compiled by Sally Cornfield on behalf of PAN-WM Headline Findings.
Urban Models. Percent Urban Population Fig. 13-1: Percent of the population living in urban areas is usually higher in MDCs than in LDCs.
HOG FARMING IN NORTH CAROLINA Meredith Robbins, Bryce Koukopoulos, Emily Madara, Shepard Daniel Abstract There is an increasing market in North Carolina.
Know Your Indicators: Vacancy Measures Erin Browne Economist Economic & Market Analysis Division Office of Economic Affairs.
Amenity Value of Proximity to National Wildlife Refuges Timothy Hamilton North Carolina State University Camp Resources XVIII.
Leadership Camden County October 1, 2008 Camdenton, MO Bill Elder, Director Office of Social & Economic Data Analysis (OSEDA) University of Missouri.
1 The American Community Survey (ACS) 2005 Data Release.
Time Series and Forecasting
1 Home Values: The value of home and property is an important measure of neighborhood quality, housing affordability and wealth.
U.S. Census Overview SOC 101.
Socio-Economic & Demographic Data Tools for Proactive Planning Robin Blakely-Armitage STATE OF NEW YORK CITIES: Creative Responses to Fiscal Stress March.
By Joel Albrecht 6/5/2012. Hypothesis Politically segregated areas of Eau Claire can be reflected by political yard signs and can be determined by 3 variables:
GIS in Prevention, County Profiles, Series 3 (2006) A. Census Definitions The following is an excellent source of definitions and explanations of geography-related.
Chapter 13 Section 5 - Slide 1 Copyright © 2009 Pearson Education, Inc. AND.
Population Mobility in the United States Martha B. Sharma APHG Test Development Committee NCGE, Kansas City October 22, 2004.
Neighborhood Level Public Library Service to Special Populations: a Review of Critical Data Needed for Optimal Service Provision 7 th Northumbria International.
LECTURE UNIT 7 Understanding Relationships Among Variables Scatterplots and correlation Fitting a straight line to bivariate data.
Racial and Spatial Health Disparities in the Delta Arthur G. Cosby Professor & Director Social Science Research Center Mississippi State University Public.
Old Louisville by the Numbers A Statistical Profile by Michael Price Urban Studies Institute University of Louisville Spring 2006.
Why Is It There? Getting Started with Geographic Information Systems Chapter 6.
Chapter 5 – 1 Chapter 5: Measures of Variability The Importance of Measuring Variability IQV (Index of Qualitative Variation) The Range IQR (Inter-Quartile.
THE LEBANESE INDUSTRIAL SECTOR : FACTS AND FINDINGS 2007 Beirut,
Geography 367 Danielle Meyer Interim 2010 Landscaping and Home Values.
McKibben Demographics Student Yield Differentials by Housing Tenure: Examples from Selected U.S. School Districts Jerome McKibben McKibben Demographic.
American Community Survey Getting the Most Out of ACS Jane Traynham Maryland State Data Center.
American Community Survey (ACS) 1 Oregon State Data Center Meeting Portland State University April 14,
Additional analysis of poverty in Scotland 2013/14 Communities Analytical Services July 2015.
Chapter 13: Correlation An Introduction to Statistical Problem Solving in Geography As Reviewed by: Michelle Guzdek GEOG 3000 Prof. Sutton 2/27/2010.
U.S. Hispanic Population: 1999 Helping You Make Informed Decisions.
Probabilistic & Statistical Techniques Eng. Tamer Eshtawi First Semester Eng. Tamer Eshtawi First Semester
Environmental Factors and Risk of Childhood Obesity Sharon Kandris, MA 1 & Gilbert Liu, MD,MS 2 1 The Polis Center at Indiana University-Purdue University.
Every student. every classroom. every day. Healthy Kids Healthy Oakland Opportunity Mapping Update Susan Lindell Radke OUSD GIS Analyst/Contract Demographer.
6.8Compare Statistics from Samples Example 1 Compare statistics from different samples Production The data set below give the number of computers assembled.
Section 6.8 Compare Statistics from Samples. Vocabulary Quartile: The median of an ordered data set Upper Quartile: The median of the upper half of an.
Sample Box-and-Whisker Plot lower extreme, or minimum value 1st quartile, the median of the lower half of the data set 2nd quartile, the median of the.
Chapter 3: Averages and Variation Section 2: Measures of Dispersion.
Slide Slide 1 Section 6-4 Sampling Distributions and Estimators.
Statistics Division Beijing, China 25 October, 2007 EC-FAO Food Security Information for Action Programme Side Event Food Security Statistics and Information.
Achievements of the Diaspora Mohammad Hafezi Harvard University Iranian Studies
Rensselaer County Community Health Needs Assessment Sociodemographic Indicators.
An Analysis of the Geographic Incidence of Social Welfare Factors as they Relate to School Performance of Early Elementary School Children Purpose This.
The Geography of Income Variations by states; Variations within metropolitan areas.
Point Estimates. Remember….. Population  It is the set of all objects being studied Sample  It is a subset of the population.
 What is the difference between wealth & Income?  How do you measure wealth?  What are assets & debts?  What does it mean to be wealthy but little.
MR. MARK ANTHONY GARCIA, M.S. MATHEMATICS DEPARTMENT DE LA SALLE UNIVERSITY.
©The McGraw-Hill Companies, Inc. 2008McGraw-Hill/Irwin Time Series and Forecasting Chapter 16.
Why Is It There? Chapter 6. Review: Dueker’s (1979) Definition “a geographic information system is a special case of information systems where the database.
NURS 306, Nursing Research Lisa Broughton, MSN, RN, CCRN RESEARCH STATISTICS.
Income, Education, & Ethnicity Erin Dawson Ball State University Geography 265.
Finding and Mapping Census Data Kathleen Fear, Data Librarian Blair Tinker, GIS Research Specialist.
Copyright © 2009 Pearson Education, Inc. Chapter 13 Section 5 - Slide 1 Section 5 Measures of Central Tendency.
AND.
Figure 11. Box plot showing the patterns of quantitative data of elastic fibre density in skin of different regions of the body in male and female cattle.
Housing, Infrastructure, and Land Use Data
Unit 8 Statistics Quiz Review
Quantifying Scale and Pattern Lecture 7 February 15, 2005
Directions for Constructing Population Pyramids in Microsoft Excel go to: Population Pyramids in Excel 1.
Housing, Infrastructure, and Land Use Data
Statistics Collecting and analyzing large amounts of numerical data
Unit Seven: Cities and Urban Land Use Advanced Placement Human Geography Session 5.
Hypothesis Tests for Two Population Proportions
Laura Wolf-Powers Josh Warner Shiva Kooragayala
MEASURES OF CENTRAL TENDENCY
Hypothesis Tests for Proportions
Current conditions.
Section 13.4 Measures of Central Tendency
Measures of Position Section 3.3.
Presentation transcript:

Geography of Eau Claire Thrift Sale Two Hypothesis: 1) Thrift sales will correlate with lower income home owners 2) Thrift sales will correlate with median household income and owner occupied homes

Thrift Sales: A National Phenomenon Nationally, nearly 20 million thrift sales annually. That is a ratio of 1 sale for every 11 people. (Combs, H., et al. 1980) Reasons for holding sales range from housecleaning to desiring a profit, but 8 out of 10 hosts interviewed in Eau Claire stated, “getting rid of junk” as a main driver. Since the 1960s, thrift sales developed as a way of compensating for the material consumption pervasive in American lifestyles. (Soiffer, S., & Herrmann, G. 1987)

Idioms of “Thrift” Sales Sale TermRegion Used TagNortheast Yard Northeast/ Midwest ThriftMidwest PorchSouth GimmeSouth RummageWest SummerWest GarageNational Terminology varies by geographic region Term/Region associations found through brief reference of large periodical classified sections Debate exists for term implications

Source: J Combs, J Bauer, P Burger. Journal of Cultural Geography. Vol. 25, No. 3, October 2008 Data Collection Thrift sale locations collected from the Leader-Telegram using August listings of sale advertisements from August listings were highest in number, corresponding with others research in Jonesboro, Arkansas August coincides with peak of the national moving season

Mapping the Data Addresses were mapped using Google Earth Pro 587 data points collected with 507 points plotted 80 points were unused due to incomplete or inaccurate address, or the addresses listed were in surrounding towns Data points were then superimposed onto US Census data maps US Census block groups were used as they are the lowest level for which geographic area decennial data is calculated

Thrift Sales and Median Household Income Comparison of thrift sales to median household income show a correlation Lower density of thrift sales in lower median income block groups Thrift sales cluster in middle median income - upper median income block groups

Jonesboro, Arkansas research supports findings (Combs, H., et al. 1980) Sale locations were positively correlated to income The block group with the second highest income per household held the highest amount of sales. Nearly 31% of the households in that block group held a sale. The lowest income block group did not hold a sale over the course of time sampled Sales per 1000 HouseholdsMedian Household Income

Thrift Sales and Low Median Household Income A near absence of sales in lower median income neighborhoods such as North, Downtown, and West Median Household Income

Thrift Sales and Median Household Income Thrift sales held largely in middle median income to upper median income block groups

Thrift Sales and Owner-Occupied Homes Thrift sale density is lower in block groups with lower proportion of owner occupied homes

Thrift Sales and Median Income/Owner-Occupancy The variance of median household income values within these block groups does not establish a pattern Median Household IncomeOwner Occupancy When compared to owner occupancy, the pattern becomes apparent

Interpretation and Implication for Future Research Original hypothesis was disproven, however literature was supported Higher income families are the impetus for the trickle down of goods in a population. o People attend thrift sales in higher or equal class neighborhoods (Herrmann, G. 2004) Home owners tend to accumulate more items over time and purge these items to make space for more/newer goods Geocoding and statistical analysis of addresses using GIS could yield greater insight into correlations

References 1. Combs, H., Bauer, J., & Burger, P. (2008). A geographical analysis of garage sales in Jonesboro, Arkansas. Journal of Cultural Geography, 25(3), doi: / Herrmann, G. (2004). Haggling Spoken Here: Gender, Class, and Style in US Garage Sale Bargaining. Journal of Popular Culture, 38(1), Retrieved from SPORTDiscus with Full Text database. 3.Soiffer, S., & Herrmann, G. (1987). Visions of power: ideology and practice in the American garage sale. Sociological Review, 35(1), doi: / X.ep Indowebsites. (n.d) Facts and Definitions. Retrieved from on 2010, August Bogwood Films, Inc. (n.d) Bogwood A-Z. Retrieved from on 2010, August 2. 6.Classifieds. (2009, May). Thrift sales: Section Leader-Telegram pp. 3C 7.Classifieds. (2009, August). Thrift sales: Section Leader-Telegram pp. 3C 8.Classifieds. (2008, August). Thrift sales: Section Leader-Telegram pp. 3C 9.Classifieds. (2007, August). Thrift sales: Section Leader-Telegram pp. 3C 10.Pamplin Media Group. Classifieds. (2001, 09 August). Garage/Rummage sales. Retrieved from on 2010, August The Providence Journal Co. (2001, 09 August). Yard sales. Retrieved from o on 2010, August 09.