This document discusses concepts related to measurement and sampling in field research. It defines key terms like population, element, sampling, sampling frame, census, survey, parameter, and statistic. The document explains that sampling involves selecting a subset of a population to study in order to make inferences about the larger population. It notes that samples must be representative of the population and discusses factors like sampling method, sample size, and sampling error that impact representativeness. The document also outlines the steps in the sampling process and lists some advantages of sampling like being faster and cheaper than studying the entire population.

1. MEASUREMENT AND
SAMPLING
Field Plot Design
AGRO-324

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. 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.  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. 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. 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. 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 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. 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?