FROM
http://www.mste.uiuc.edu/malcz/data/WEATHER/Temperatures.html

US Temperatures


Data was taken from The Data and Story Library. For further information about the data, see The Data and Story Library http://lib.stat.cmu.edu/DASL/
Web Page.

Return to the MSTE Data Archive 

Reference: Peixoto, J.L. (1990) A property of well-formulated polynomial regression models. American Statistician, 44,
26-30. Also found in: Hand, D.J., et al. (1994) A Handbook of Small Data Sets, London: Chapman & Hall, 208-210. 

Description: The data gives the normal average January minimum temperature in degrees Fahrenheit with the latitude and
longitude of 56 U.S. cities. (For each year from 1931 to 1960, the daily minimum temperatures in January were added
together and divided by 31. Then, the averages for each year were averaged over the 30 years.) 

Number of cases: 39 

Variable Names: 

  A.City: City, State postal abbreviation 
   B.JanTemp: Average January minimum temperature in degrees F. from 1931-1960 
  C.Lat: Latitude in degrees north of the equator 
  D.Long: Longitude in degrees west of the prime meridian 

To download this data into an Excel spreadsheet, click on US Temperatures. 

       City
                  Temperature
                              Latitude
                                     Longitude
 "Mobile, AL"
                  44
                              31.2
                                     88.5
 "Phoenix, AZ"
                  35
                              33.6
                                     112.5
 "Los Angeles, CA"
                  47
                              34.3
                                     118.7
 "San Francisco, CA "
                  42
                              38.4
                                     123
 "Denver, CO"
                  15
                              40.7
                                     105.3
 "Washington, DC"
                  30
                              39.7
                                     77.5
 "Miami, FL"
                  58
                              26.3
                                     80.7
 "Atlanta, GA"
                  37
                              33.9
                                     85
 "Boise, ID"
                  22
                              43.7
                                     117.1
 "Chicago, IL"
                  19
                              42.3
                                     88
 "Indianapolis, IN"
                  21
                              39.8
                                     86.9
 "Louisville, KY"
                  27
                              39
                                     86.5
 "New Orleans, LA"
                  45
                              30.8
                                     90.2
 "Portland, ME"
                  12
                              44.2
                                     70.5
 "Baltimore, MD"
                  25
                              39.7
                                     77.3
 "Boston, MA "
                  23
                              42.7
                                     71.4
 "Detroit, MI "
                  21
                              43.1
                                     83.9
 "Minneapolis, MN"
                  2
                              45.9
                                     93.9
 "St. Louis, MO"
                  24
                              39.3
                                     90.5
 "Helena, MT"
                  8
                              47.1
                                     112.4
 "Omaha, NE"
                  13
                              41.9
                                     96.1
 "Albuquerque, NM"
                  24
                              35.1
                                     106.7
 "New York, NY"
                  27
                              40.8
                                     74.6
 "Charlotte, NC "
                  34
                              35.9
                                     81.5
 "Bismarck, ND"
                  0
                              47.1
                                     101
 "Cincinnati, OH"
                  26
                              39.2
                                     85
 "Cleveland, OH "
                  21
                              42.3
                                     82.5
 "Seattle, WA"
                  33
                              48.1
                                     122.5
 "Milwaukee, WI"
                  13
                              43.3
                                     88.1
 "Cheyenne, WY"
                  14
                              41.2
                                     104.9


-----------------------------  

http://ww2.sofweb.vic.edu.au/cgi-win/search.exe/BROWSEITEM?LVL=2&ID=1243

Correlation between average temperature and
      latitude for cities in USA


      Abstract: 
                           Students download real data from the Internet in the form of an excel spreadsheet and
                           find a line of good fit.
      Prerequisites:
      (Requirements prior to
      activity) 
                           Students should have some knowledge of lines of good fit, and some experience using
                           a spreadsheet.
      Resources Needed:
                           Computer lab with access to internet and excel spreadsheets
      URL1: 
                           http://www.mste.uiuc.edu/malcz/data/WEATHER/Temperatures.html
      Activity: 
                           Students go to web site URL1 and download the excel file from page to disk (very
                           fast download time). They then start Excel, open the downloaded file and highlight the
                           average temperature and latitude columns (columns B and C, this is not clear from
                           downloaded file but can be verified using the data read from the web page). 
                           Students use the data to create a scatter graph and determine the line of good fit.
                           Students could print out the scatter graph and find their own line of good fit as well as
                           using the spreadsheet line of best fit feature. They should determine the equation of
                           their hand drawn line of good fit.
                           Students should also interpret their graph and discuss it's features, for example, which
                           city produces an outlier.

                           Students can also use the spreadsheet to convert the temperature data from
                           Fahrenheit to Celsius using the formula "F = 1.8C + 32" and then use the Celsius data
                           to create their scatter plot. This makes the data more familiar.
      Learning Outcomes: 
                           Mathematics:Chance and Data:6
                           MACD565 - Makes statements about the association between bivariate variables
                           MACD564 - Reports on his or her displays and summaries
                           MACD563 - Interprets data from prepared databases
                           MACD4612 - Uses appropriate computer software to produce a scatter plot
                           MACD4610 - Draws a line of good fit to a scatter plot by eye
                           MACD4609 - Represents bivariate data in a scatter plot
                           MACD4605 - Identifies outliers in data sets
                           MACD3606 - Collects bivariate data
      Comments: 
                           This real data produces a good linear trend with one outlier. The data gives the normal
                           average January minimum temperature in degrees Fahrenheit with the latitude and
                           longitude of 56 U.S. cities. (For each year from 1931 to 1960, the daily minimum
                           temperatures in January were added together
                           and divided by 31. Then, the averages for each year were averaged over the 30
                           years.) 
      Acknowledgements: 
                           Nil
      Other benefits 
      for students: 
                           Students use real data to test for a relationship between two variables.