Geography 417: California For Educators

Geography Lab: Mapping California   

Geography  Lab: Using and Interpreting Primary Sources

Before you Start: It's always a good idea to print a copy of this exercise out first.  Then you can pencil  in your answers on the paper copy as you go through the assignment.  Should your internet connection fail, then you won't have to start over.  Also, you'll have a 'hard copy' as proof you did the assignment.  When you want to enter your answers, remember to press TAB after you have typed in a response.  You can also use your mouse to move to the next response box.  DO NOT press enter until you are finished.  Once you press Enter or click the Submit button below, you will be redirected to a page that displays your answers.  It's a good idea to keep a copy of this as well.

Background: The ability to make a map is an important component not only of learning how to "do" geography, but becoming cartographically literate.  In other words, in order to effectively read a map, it helps if you've made a map or two.  This exercise is designed to show you how to make a respectable choropleth (KORE-oh-pleth) map using an on-line mapping program called DDViewer.  The data is getting old, but it remains the most efficient, low-hassle interactive mapping program on the web.

You will also get some instruction on how to interpret the maps you've made.  In the process, hopefully you'll learn something about the distribution of ethnic groups in California and some things about causal factors that may in part explain the statewide ethnic patterns.

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CSBE Standard:  This exercise addresses in part several of the California State standards for 4th graders:

4.1 Students demonstrate an understanding of the physical and human geographic features that define places and regions in California.

3.  Identify the state capital and describe the various regions of California, including how their characteristics and physical environments (e.g., water, landforms, vegetation, climate) affect human activity.
4.  Use maps, charts, and pictures to describe how communities in California vary in land use, vegetation, wildlife, climate, population density, architecture, services, and transportation.

CSET Standard: This exercise address in part several CSET Skills and Abilities requirements.  Specifically covered by this lab are the domains below:

Part II-A. Candidates for Multiple Subject Teaching Credentials utilize chronological and spatial thinking.

  1. They construct and interpret timelines, tables, graphs, maps and charts. ** (emphasis-California)

  2. They describe the cultural, historical, economic and political characteristics of world regions, including human features of the regions such as population, land use patterns and settlement patterns. ** (emphasis-California)

Part II-B. Candidates for Multiple Subject Teaching Credentials analyze, interpret and evaluate research evidence in history and the social sciences.

  1. They interpret primary and secondary sources, including written documents, narratives, photographs, art and artifacts revealed through archeology. **

  2. In the interpretation of historical and current events, candidates identify, explain and discuss multiple causes and effects. **

  3. They recognize the differing ramifications of historical and current events for people of varying ethnic, racial, socio-economic, cultural and gender backgrounds. **

Part II-C.  Candidates draw on and apply concepts from history and other social studies including political science and government, geography, economics, anthropology, and sociology.

  1. They draw on and apply basic economic concepts. ** (emphasis-California)

  2. They explain basic concepts of demography including factors associated with human migration. ** (emphasis-California)

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Objectives:  In general, students will be able to make some maps California and discuss the patterns they observe.  Specific objectives include:

  1. Students will create thematic or choropleth maps of California.
  2. Students will identify different classification strategies used by cartographers to display data.
  3. Students will identify several statewide demographic and economic distributions.
  4. Students will offer speculation on the relationship between the demographic and economic data visible on the maps.
  5. Students will explain several basic statistical concepts useful for describing the data and relationships among the data.

* DO NOT start this exercise the night before it is due. You may need help, or a server may go down.
*DO stop by your instructors office if you are having trouble.
*DO remember to put your name in the response box below.

Part I: Cartography and Vocabulary

Maps are an important form of communication.  Some have even argued that cartography, the art & science of mapmaking, is itself a universal language, much like mathematics.  Unfortunately, many people can not effectively read and interpret maps. 

There are a number of types of maps.  Every map is a graphical representations of data.  Some maps are more effective at communicating one type of data than others.  This exercise will focus on choropleth maps, also called thematic maps, because they are most widely used to communicate the type of data used in this exercise.   A variety of data can be mapped with a choropleth map, but it is important to have some familiarity with them because they can hide as much data as they reveal.   In this exercise, you'll make some choropleth maps and also learn about their strengths and weaknesses.

Step 1. Click the link below to open a second browser window.  When this window opens, click on the link labeled Java Edition v3.0.    Hopefully your computer will have Java installed.  It's a fairly common program and comes pre-installed on most machines now.

Open the CIESIEN's DDViewer welcome page...click on the Java 3.0 link.

Step 2.  Once the program has loaded, you should see a window depicting a base map of the United States (see screen capture).  This is an outline map awaiting data to give it life. 

Step 3.  Click on the "Select Vars" button and another dialog window will open.  This window allows you to begin selecting up to 220 variables in a variety of categories.  Population variables are selected by default, but you will be selecting income and employment variables during this lab, so make a note of the buttons at the top of the window.  From the list of variables, simply click on the variable names "totpop" and "popsqmi" to begin making a pair of maps (see screen capture).  The first is of total population and the second will be of population density. 

Step 4:  Return to the mapping window and click on the "Submit Job" button.  Wait a moment and a new map will appear in the window and you will have made a map depicting total population by state, in 1990.  Make sure the label button is checked on, and move your cursor over the outline of California.  Note the number that appears after the word California (see screen capture).  This number represents the 1990 population of California in scientific notation.  You may recall from a math class, that scientific notation is a means of expressing very large numbers.  In this instance, the population of California is expressed as 2.9760016E7.  You should read this as 2.97600016 x 10 to the 7th power.  Translated into integers, this is roughly 29,760,016, which seems like an ineffective use of scientific notation to me, but you should still be able to read numbers expressed as such.  See if you can do it.  Move your cursor over Florida and answer question 1. 

Question 1: Fill in the blank- The population of Florida, expressed as an integer, expressed with place holding commas, is: .

Step 5.  Notice that states are divided into four groups based on population, with the states with the greatest population appearing in the darkest read color.  The least populous fourth (1/4) of states appear in Yellow.    What if you want to divide the data into fifths, thirds or eighths rather than fourths?  You can change the map in the DDViewer so that more divisions in the data appear.  Click on the Customize Maps button and another dialog window will appear.   In the lower right window, you can select the number of groups you want the data to be divided into.  Select from the list "5 equal groups" (see screen capture).  This means the map is now in quintiles, rather than quartiles...though it remains in quantiles.  The map will change to reflect your selection.  Observe your new map and answer the next question.

Question 2: How many states should be in the top (darkest red) category now that 50 states have been divided into 5 equal groups?

Step 6.  Check to see if indeed the top 1/5th of the states are shaded differently than the others.  Because the eye has trouble picking out the slight variation in color between the dark orange and red colors that separate the top 2 /5th of the state, it is advisable to change color denoting the highest category of data to something other than red.  In the customize output dialog box, click in the box to the right of the number 5.  This opens yet another window that has a color palette.  From the available colors, chose a color like green or blue that will allow you  to distinguish the top states more easily (see screen capture).  Your map should now appear as it does in this screen capture

A SIDE NOTE: Using a color, like green, which is not part of the color ramp (yellow-orange-red) helps us see the distinction better, but it ALSO suggests, that there is something QUALITATIVELY different about those states.  In reality, the difference in population you are mapping is QUANTITATIVELY different, so using green would not be appropriate to communicate this fact.  You should use a QUALITATIVE color scheme to map qualitatively different (nominal) data.  For example, if the people of states had to vote for their favorite soft drink and they could chose between Coke, Pepsi and 7-UP, it would be appropriate to make a map using Red, Blue and Green (qualitative scheme) to denote the statewide preference in soft drinks. 

Question 3: Fill in the blank: This map of US governors by party affiliation (click to see) is an example of a color scheme.

Step 7.  The next step is to decide whether equal intervals (quantiles) data classification system is most appropriate for mapping the state populations of the US.  The main question you want to ask yourself is: "Does this ranging method best communicate the dispersion of the data?"    Take a look at this scatterplot graph of the US State populations.  The vertical lines divide the data into five quantiles or equal groups.  The point in the upper right represents the population of California (about 30 million in 1990) , the point on the vertical line extending upward from 40 is North Carolina, with roughly 6.6 million people in 1990.   Now, take a look at a second strategy for dividing the same data, using equal intervals.  Here the data itself is divided into equal data ranges of roughly 8 million.  Note the horizontal lines.  So states with less than about 8 million are in the first category, those with 8 to 16 million are classified into the next, 16 to 24 million in the next, and so on.  Note the categories into which California and North Carolina now fall (2000 data).

There are many other classification systems, but these two are popular.

Step 8.  Change the ranging method on map to classify the data into equal intervals.  Click on the Customize Map button (or switch to that dialog window if it is already open).  In the Customize Output dialog box, click on the radio button to the left of Eq. Intervals (for equal range) and select 5 equal intervals from the list of options.  Examine your redrawn map of US populations by state.

You may want to experiment a bit with the equal interval and quantile options. 

Question 4:  Fill in the blank:  The best way to demonstrate California's uniquely large population among the states is to map state population using the ranging method or data classification scheme.
  (quantile?  equal interval?)

Question 5: On the other hand, if you wanted to make California appear as if it were not unusually large, then then the ranging method would be better. 

Step 9.  In the Customize Output window, return the data classification scheme to quantiles.  If you leave it in equal intervals the next question will be harder to answer.

Step 10. Back in the main map viewing window, click on the popsqmi in the little mapped variable window.  A new map will appear in the window, showing the population densities of states. 

Question 6:  If you didn't like crowds, what part of the United States would you most avoid...The South, The Northeast,
The Midwest or the West? 

Step 11.  Click on the Statistical Info button to bring the a new window that displays some basic statistical data about the mapped variables. 

Question 7: The average or mean population of the states including  Washington D.C. is :

Question 8:  The maximum population density for this data set is 9884.3 people per square mile.  This is for   and the inclusion of this place really skews this data, pushing the mean (average) for the states much higher.

Part II: Mapping California

Step 1. Move your cursor over California, and make a note of California's population density (popsqmi).  Next, Click on Sel New Region button and the map will return to its default 'base map' state.  Click once on the outline of California to highlight it (see screen capture).   Now click on the Get Counties button to produce a base map of California's counties.  Click Submit Job to produce a map of population.  Click on "popsqumi" in the mapping variable window to change the map to population density (see screen capture). 

Step 2.  Click on the Statistical Info button and examine the information that appears. 

Question 9: The lowest population density for any county is  persons per square mile.

Question 10: The highest population density of any county in California is persons per square mile.

Step 3.  Compare the answers you got for questions 9 and 10 with the average population density for all of California.  You should recognize that the "average" is not a very useful statistic in this instance.  This is problem reveals itself in the US- States map as well.  Because a choropleth map generally prohibits you from seeing the variation with the borders of a state, it suggests  to the unwary that everything within those boundaries are essentially equal, when as you can see they are not.  Choropleth maps mask internal variations.  ***Poorly considered deductive logic also suffers from the same problem.  It is dangerous to suppose much about any individual based on the actions or characteristics of any group to which that individual may belong. 

Check out this website, which examines some of the problems with typical election night choropleth maps.

Step 4: Click on the Select Vars button to return to the window that allows you to select variables to map.  Click on the "Clear All Selections" button to get rid of the population statistics.  Scroll down through the population variables until you find "pct white % white population".  Select all the ethnic percent variables (pct white, pct black, pct asian, pct amind and pct hisp- screen capture).  Click submit job.  Look at all the maps and think about the reasons behind these patterns.  Answer the following questions.  You are welcome to open the statistical information window and in there you can select tabular info to see a table.  You may also want to switch the map between equal intervals and quantiles to make the answers more obvious.

Question 11.  Which county has the highest percentage of Hispanic population? 

Question 12.  Which county has the highest percentage of Asian and Pacific Islander population?

Question 13:  Which county has the highest percentage of Blacks?

One of the reasons for the ethnic patterns visible in these maps lie in the reasons people migrate to a specific county.  You could hypothesize that the ethnic pattern is partly a result of the type of jobs that attract migrants from other countries or from other parts of the US.  Frequently if a person gets a job somewhere new, and they like it (or the money they make) they will invite friends and relatives to join them in the new location.  A chain of migrants from one location to another can form, radically altering the ethnic composition of the destination region.   We can do a preliminary test of this hypothesis with the data on the DDViewer.

Step 5.  Now go back to the Select Variables dialog box and clear the selections again.  Click on the button at the top of the variables dialog box labeled "Employment".  Scroll to the bottom of the list where you will find a set of variables that refer the percent of people employed in several broad employment categories.  Select them all and click on the Submit Job button in the mapping window.  Examine your new maps.   Do you see any spatial correlation between the map of occupational categories and the maps of ethnicities?  If you have a good eye, you might notice that some of these maps look like each other, but generally this is hard to do, so the last step is to test this correlation.  You can copy and paste all this data into a spreadsheet or a statistics software program, but to save time, I've done it for you.  

If you want to see a cool on-line interactive mapping program that does this statistic for you, check out The ARDA.com

Step 6:  Click on this link to a table that has the data that you just mapped.  Look it over for a moment.  Next look at the multicolored table below.

This table was created in M.S. Excel when the software was prompted to calculate the statistical relationship between the each ethnic variable and each employment variable.  The table below contains the answers in a cross tabulation table. The correlation coefficient between Percent White (pink column) and Percent Employed in agriculture, forestry or fishing (bold green font row) is actually negative or inverse (-0.12).  Roughly translated, this statistic says that about 12% of the time, when the percent of white people goes up in a county, the number of farm/forestry/fishing jobs goes down...and vice verse.  On the other hand, about 40% of the time when the percent of the change in Percent White is accompanied by a corresponding increase in the percent of service jobs.   This is a pretty good correlation for social science.  As the correlation gets stronger, the correlation coefficient gets closer to (-/+)0.99.  A perfect correlation is 1.00 and can be positive or negative.

  Pct White Pct Hispanic Pct Asian Pct Black
PCT Farm -0.12 0.45 -0.28 -0.27
PCT Service 0.40 -0.38 -0.39 -0.24
Pct Technical -0.33 -0.01 0.60 0.53

***IT IS VERY IMPORTANT that you don't assume that correlation implies CAUSATION.  There may be a strong positive correlation between the sale of swimsuits and the sale of ice cream over the course of a year, but you can not claim that eating ice cream makes you want to buy a bathing suits (or vice verse).  Many variables may have a spurious relationship, or co-vary yet are without a causal linked.  In the case of ice cream and bathing suits, temperature may be the causal variable for both. 

Step 7.  With that information answer the following questions.

Question 14: According to the table above, about 45% of the change in the percent of county populations of this ethnic group is accompanied by an increase in farming, forestry or fishing jobs:   (see this page for a hint)

Question 15: An even stronger correlation exists between the percent of Asian in California's counties and the percent of people engaged in jobs.

Question 16:  There is a .53 correlation between the percent of Blacks and the percentage of jobs in the field.

While this table may suggest that certain ethnic groups are attracted to certain jobs (or that certain jobs follow specific ethnic groups).  There is other factors certainly worth considering that a responsible social scientist would investigate. 

Common sense and other social science data would strongly suggest that black folks are more likely to be employed in service sector jobs.  So why is the correlation between these two categories negative?   The answer lies in the resolution of the data.  Since this data is at the county level, you can't tell what kind of jobs people are doing within the counties.  Perhaps in counties with few service jobs and few Blacks, the black folks still are engaged in those jobs.  The same holds true for Asians and technical jobs.  It might be that Asians aren't employed in technical fields, they just happen to like living in counties where there happen to be lots of technical jobs. 

Question 17: What do you suppose might be a causal variable that seems to place both Blacks and Asians in counties with technical jobs?  In fact there is 0.65 correlation at the between Percent Black and Percent Asian.  They are in the same places.  Where are they that also has technical jobs?
Answer 17: Fill in the blank. Blacks and Asians both tend to live in counties, which also have a higher percentage of technical jobs.

Bonus:  It appears that whites are more common in those counties where service sector jobs dominate.  In what part of the states do you have many counties with both large percentage of whites and an above average percent of jobs in the service sector?   (North, South, Coastal, Desert, ??)
Answer:

 

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If you have questions or comments, please contact me at steve.graves@csun.edu