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Class prep

Class prep. Go to S:classesUEP_ENV Copy whole folder “American Community Survey Error Exploration” to your Desktop Make writable: right-click on folder => properties => uncheck read-only. Class prep.

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Class prep

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  1. Class prep • Go to S:\classes\UEP_ENV • Copy whole folder “American Community Survey Error Exploration” to your Desktop • Make writable: right-click on folder => properties => uncheck read-only

  2. Class prep • Using Windows Explorer, go to the following folder:American Community Survey Error Exploration \AFF_data_tables\ Median_HH_Income_tract • Open: • ACS_10_SF4_B19013_metadata.csv – this is the metadata file for the ACS data • ACS_10_SF4_B19013_Med_HH_Income.xlsx – this is the data table (median household income)

  3. Today • Census mapping basics review and questions • Understanding American Community Survey margin of errors • Calculating a reliability index (coefficient of variation or CV) • Visualizing the CV on a map

  4. Questions about joining tables to geography? Federal Information Processing Standards (FIPS) Codes Area Name FIPS State Massachusetts 25 County Suffolk 25025 Tract 000601 25025000601

  5. We JOIN the data table to the geography table using the common ID column

  6. Mapping Numbers

  7. Graduated color

  8. Graduated Colors…number of renters

  9. Graduated Symbols…number of renters

  10. Normalization (“divide by”) Number of population in rental units normalized by total population in occupied housing units

  11. Fraction of renters living in each tract out of total population in occupied housing units

  12. Using “Normalization” • Normalize by means “divide by” • Percentage – e.g., number of renters over total population in occupied housing • Result is a fraction, e.g., .45 • Fractions are translated into percentages by multiplying by 100 • .45 = 45% • Density – population normalized by area (e.g., sq mi, acre)

  13. Classes and Classification Methods

  14. Classes and Classification Methods

  15. Classification methods • Details from ArcGIS 10.1 Help – standard classification methods • Natural breaks – good for skewed data • Equal interval, defined interval, and standard deviation – good for evenly distributed data to show differences • Quantiles - good for evenly distributed data to show relative difference (e.g., top and bottom 20 percentile • Geometric interval – compromise that attempts to have similar number of features in each class with intervals being roughly the same

  16. Classification methods • Details from ArcGIS 10.1 Help – standard classification methods • Equal interval • Defined interval • Natural breaks • Quantiles • Standard deviation • Geometric interval Try them out!

  17. Which classification methods is best?

  18. Formatting numeric labels

  19. But make it better! Clutter and data speak! Clearer and cleaner

  20. Review • Categories versus numbers • Proportional versus graduated symbols • Understanding classification methods • No “right” method – explore • Different methods => very different results • Number of classes – hard to distinguish over 6 • Understanding normalization (“divide by”)

  21. Mapping a particular area – two selection options: • Select the town first, then perform select by location to get all tracts that intersect that town (or have their centroid in that town) • Zoom into an area slightly larger than the region you want to map, then interactively select all the tracts from in that area (e.g., use the select tool to make a box around them) • Then Create Layer from Selected Features

  22. Copying and pasting the same layer in your table of contents • If you want to map several variables that are within the same joined table(s), you can simply copy and paste the layer so that you have another copy • Then create maps from a different variable in each layer • Make sure to change title, legend

  23. American Community Survey What users need to know

  24. Test: why do we need to use ACS data in policy / environmental analysis?

  25. Because it has important information about our communities…

  26. Because it has important information about our communities…

  27. So we need to learn to use the information reliably… And especially to understand the margin of error for ACS estimates

  28. Review – What is the ACS? • American Community Survey • A continuous monthly survey of households • Long set of questions covering many topics • Data is released once a year • 1 Year averages – areas with a population 65,000+ • 3 Year averages – areas with a population 20,000+ • 5 Year averages - all other areas (including census tracts and blockgroups) • E.g., averagenumber of people commuting by bicycle for 2007-2011

  29. Use Census 2010 data where possible because it is 100% survey, thus has smaller sampling error • Population Counts • Age • Race / Hispanic Ethnicity • Housing Unit Counts and Tenure (rented, owner-occupied) • Household and Family Relationships

  30. ACS: Use the highest aggregation you can in terms of tables (can be hard to find)

  31. ACS and Margin of Error Workers 16 and Over Means of transportation for commute – Tract Level - ACS 2005-2009 5 year estimates Universe is workers 16 and over

  32. Open the Excel files… • ACS_10_SF4_B19013_Med_HH_Income.xlsx – this is the data table (median household income) • ACS_10_SF4_B19013_metadata.csv– this is the metadata file for the ACS data

  33. Metadata file and data table…

  34. So let’s understand the margin of error…

  35. What is Sampling Error? Definition The uncertainty associated with an estimate that is based on data gathered from a sample of the population rather than the full population

  36. Illustration of Sampling Error Estimate average number of children per household for a population with 3 households living in a block: Household A has1 child Household B has2 children Household C has3 children The block average based on the full population is two children per household: (1+2+3)/3

  37. Conceptualizing Sampling Error Three different samples of 2 households: • Households A and B (1 child, 2 children) • Households B and C (2 children, 3 children) • Households A and C (1 child, 3 children) Three different averages based on which sample is used: • (1 + 2) / 2 = 1.5 children • (2 + 3) / 2 = 2.5 children • (1 + 3) / 2 = 2 children

  38. Sampling Error • Census 2010 is a 100% survey so has smaller error • ACS data is based on samples – error is larger • The smaller the geography, the larger the error (because the sample is smaller) • Especially true for variables that sample a small number of people, e.g., bike commuters

  39. ACS and Margin of Error Workers 16 and Over Means of transportation for commute – Tract Level - ACS 2005-2009 5 year estimates Universe is workers 16 and over

  40. American Community Survey and sampling error The margin of error is calculated and included with each estimate Calculated at 90% confidence level What does that mean?

  41. ACS and Margin of Error Workers 16 and Over Means of transportation for commute – Tract Level - ACS 2005-2009 5 year estimates Universe is workers 16 and over

  42. Confidence level of 90% • We don’t know for sure how many people in Tract 3.02 take public transit to work • Based on the ACS sample, our estimate over 5 years is that an average of 747 people take transit, +/- 226 at 90% confidence level • If we did many, many samples of that same tract, 90% of the time the resulting range (521-973 people) would contain the real number of commuters taking transit. • 10% of the time it would not

  43. Confidence level of 90% • The confidence level of a margin of error indicates the likelihood that the true population value (real number) falls within the margin of error • We can be 90% confident that somewhere between 571 and 973 people take transit to work in tract 3.02

  44. Also we know that Tract 3.02 has somewhere between 1958 and 2684 workers) So maybe half the workers take transit, or maybe just a fifth of them do. Ugh!!!

  45. If using ACS data, pay attention to margin of error!

  46. ACS table from American Factfinder….

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