MEASUREMENT AND SAMPLING TECHNIQUES

MEASUREMENT AND SAMPLING TECHNIQUES

• 1.
  MEASUREMENT AND SAMPLING Field PlotDesign AGRO-324
• 2.
  Population The entire groupof people of interest from whom the researcher needs to obtain information. Element (sampling unit) one unit from a population Sampling The selection of a subset of the population Sampling Frame Listing of population from which a sample is chosen Census A polling of the entire population Survey A polling of the sample Terminology
• 3.
  Parameter  The variableof interest Statistic  The information obtained from the sample about the parameter Goal To be able to make inferences about the population parameter from knowledge of the relevant statistic - to draw general conclusions about the entire body of units Critical Assumption The sample chosen is representative of the population Terminology
• 4.
   The processof obtaining information from a subset (sample) of a larger group (population)  The results for the sample are then used to make estimates of the larger group  Faster and cheaper than asking the entire population  Two keys 1. Selecting the right sampling method  Have to be selected scientifically so that they are representative of the population 2. Selecting the right number of the samples  To minimize sampling errors Sampling
• 5.
  Population Vs. Sample Populationof Interest Sample Population Sample Parameter Statistic We measure the sample using statistics in order to draw inferences about the parameters of the population.
• 6.
  Steps in SamplingProcess 1. Define the population 2. Identify the sampling frame 3. Select a sampling design or procedure 4. Determine the sample size 5. Draw the sample
• 7.
  Purpose of sampling To gain an impression of an area or collection of things  To estimate a population parameter  To test hypotheses: unproven theories or suppositions which are the basis for further investigation
• 8.
  Advantages of sampling The only means of obtaining data about an infinite population (e.g. air temperatures)  Cost and time effective means of obtaining data about a large finite population; better data then hastily collected data for the entire population  Desirable when measurement is destructive or stressful, e.g. plant sampling, some measurements on people
• 9.
  Sampling error Error ina statistical analysis arising from the unrepresentativeness of the sample taken. It depends on measurement error and the representativeness of a sample, which in turn depends on 1. Sample size  Decrease in sampling error with increasing sample size  A minimum sample size is three 2. The sampling frame  The means by which the sampled population is identified from the target population  If poor it causes bias towards the sampling 3. The sampling procedure  Random sampling  Random location  Regular intervals and thus have a uniform distribution
• 10.
  Characteristics of Measurement 1.Validity  A valid measurement is a quantity or dimension that corresponds to the measured variable  There are standard measurements (procedures and expressions) for common variables 2. Accuracy  Closeness of measurements to an expected or true value  Accuracy is inversely proportional to error (i.e. high accuracy corresponds to low error) Types of error:  gross: blunders caused by carelessness of instrument failure  systematic: consistent overestimation or underestimation of the target value; usually caused by poor calibration of an instrument or a poor measurement procedure  random: human error randomly (normally) distributed with respect to the mean observation 3. Precision  The closeness of repeated measurements to one another
• 11.
  QUESTIONS?