MEASUREMENT AND SAMPLING

Field Plot DesignAGRO-324

PopulationThe entire group of people of interest from whom the

researcher needs to obtain information.Element (sampling unit)one unit from a population

SamplingThe selection of a subset of the population

Sampling FrameListing of population from which a sample is chosen

CensusA polling of the entire population

SurveyA polling of the sample

Terminology

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

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

Population Vs. Sample

Population Vs. Sample

Population of Interest

Sample

Population Sample

Parameter Statistic

We measure the sample using statistics in order to drawinferences about the parameters of the population.

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

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

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

Sampling errorError 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 on1. Sample size Decrease in sampling error with increasing sample size A minimum sample size is three2. The sampling frame The means by which the sampled population is identified from the target

population If poor it causes bias towards the sampling3. The sampling procedure Random sampling Random location  Regular intervals and thus have a uniform distribution

Characteristics of Measurement1. 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

QUESTIONS?