Systematic Sampling of Cities in Riverside County

Introduction to Systematic Sampling

• Systematic sampling is a method of selecting a sample from a larger population.
• In this example, we are focusing on revenues data from Riverside County's cities.

Determining Sampling Parameters

• K = Big N / little n
• Big N = Total population size
• little n = Desired sample size
• Intended sample size: 4 cities
• Identifying Big N
• Population size is indicated by the last city in the spreadsheet.
• The last city is labeled as 29, but we must account for the header row, leaving us with 28 cities.

Calculating the Sampling Interval

• Compute the sampling interval:
• 29 / 4 = 7.25
• Round to the nearest whole number:
• 7.25 rounds down to 7.
• Thus, the sampling interval is set at every 7th city.

Selecting the Starting Point

• The selection starts from one of the first seven cities (rows 2 to 8).
• A random choice is made among rows 2–8; in this case, row 6 is selected.

Sampling Process

• Begin with the city located at row 6: Canyon Lake.
• Use the established sampling interval to select subsequent cities:
• From Canyon Lake (row 6) go to:
  • Row 6 (Canyon Lake)
  • Row 13 (Indian Wells, 6 + 7)
  • Row 20 (Marietta, 13 + 7)
  • Row 27 (San Jacinto, 20 + 7)
• Final Selected Cities:
• 1. Canyon Lake
• 2. Indian Wells
• 3. Marietta
• 4. San Jacinto
• Total of 4 cities successfully selected for the sample.

Conclusion

• Systematic sampling allows for an organized approach to sample selection within a population.
• Understanding the method ensures accurate sampling while minimizing bias in data collection.