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This article in SSSAJ

  1. Vol. 37 No. 4, p. 606-611
    Received: Oct 27, 1972
    Accepted: Feb 12, 1973

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Land Sale Prices in South Dakota and Their Relationship to Some Soil, Climatic, and Productivity Factors1

  1. F. C. Westin,
  2. M. Stout Jr.,
  3. D. L. Bannister and
  4. C. J. Frazee2



About 2,700 land sale figures were used along with individual county soil-association maps to determine average peracre values of South Dakota counties. Annual average precipitation and temperature data were connected to landsale figures using multiple-regression equations. County crop productivity also was related to precipitation and county land sale data. The best prediction formula for explaining average county land values was a fifth-order polynomial-regression with precipitation as the variable. This explained 95% of the variance. Most of the variance (84%) of county cropland productivity was explained with a second-order polynomial-regression having annual-average precipitation as the variable, and 86% of the variance of county land value figures was explained with a second-order polynomial-regression having county cropland productivity as the variable. However, only a little over 54% of the variance of individual farm sales could be explained using regression equations involving climate, slope, and soil-texture as variables.

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