MEASUREMENT AND SAMPLING TECHNIQUES

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MEASUREMENT AND SAMPLING TECHNIQUES

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MEASUREMENT AND SAMPLING TECHNIQUES

  1. 1. MEASUREMENT AND SAMPLING Field Plot Design AGRO-324
  2. 2. Population The entire group of 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. 3. Parameter  The variable of 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. 4.  The process of 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. 5. Population Vs. Sample Population of Interest Sample Population Sample Parameter Statistic We measure the sample using statistics in order to draw inferences about the parameters of the population.
  6. 6. Steps in Sampling Process 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. 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. 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. 9. Sampling error Error in a 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. 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. 11. QUESTIONS?

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