Sampling
1. Introduction
In analytical chemistry, accurate results depend not only on sophisticated
instruments but primarily on proper sampling and sample preparation. No
matter how advanced the analytical technique is, incorrect sampling or poor
sample preparation will lead to unreliable results. Therefore, sampling and
preparation form the foundation of the entire analytical process.
2. Sampling
Definition
Sampling is the process of selecting a small, representative portion from a large
bulk material so that the analysis reflects the true composition of the whole.
Importance of Sampling
Ensures representativeness of the sample
Minimizes analytical errors
Improves accuracy and precision
Preserves the original composition of the analyte
3. Types of Sampling
1. Random Sampling
In random sampling, each unit of the population has an equal probability of being
selected. This method is best suited for homogeneous materials and helps
eliminate selection bias.
Example: Randomly collecting water samples from different locations in a storage
tank.
, 2. Systematic Sampling
Samples are collected at fixed time intervals or spatial intervals. This method is
commonly used in process monitoring.
Example: Sampling industrial effluent every hour.
3. Stratified Sampling
The bulk material is divided into subgroups (strata) based on known variations,
and samples are taken from each group. This method is effective for
heterogeneous materials.
Example: Soil sampling at different depths.
4. Grab Sampling
A single sample collected at one time and one location. Although simple, it may
not represent variations over time.
Example: Taking a single river water sample.
5. Composite Sampling
Multiple samples collected at different times or locations are combined to obtain
an average composition.
Example: Mixing wastewater samples collected throughout the day.
4. Sampling Techniques
A. Solid Sampling
Crushing and grinding
Coning and quartering
1. Introduction
In analytical chemistry, accurate results depend not only on sophisticated
instruments but primarily on proper sampling and sample preparation. No
matter how advanced the analytical technique is, incorrect sampling or poor
sample preparation will lead to unreliable results. Therefore, sampling and
preparation form the foundation of the entire analytical process.
2. Sampling
Definition
Sampling is the process of selecting a small, representative portion from a large
bulk material so that the analysis reflects the true composition of the whole.
Importance of Sampling
Ensures representativeness of the sample
Minimizes analytical errors
Improves accuracy and precision
Preserves the original composition of the analyte
3. Types of Sampling
1. Random Sampling
In random sampling, each unit of the population has an equal probability of being
selected. This method is best suited for homogeneous materials and helps
eliminate selection bias.
Example: Randomly collecting water samples from different locations in a storage
tank.
, 2. Systematic Sampling
Samples are collected at fixed time intervals or spatial intervals. This method is
commonly used in process monitoring.
Example: Sampling industrial effluent every hour.
3. Stratified Sampling
The bulk material is divided into subgroups (strata) based on known variations,
and samples are taken from each group. This method is effective for
heterogeneous materials.
Example: Soil sampling at different depths.
4. Grab Sampling
A single sample collected at one time and one location. Although simple, it may
not represent variations over time.
Example: Taking a single river water sample.
5. Composite Sampling
Multiple samples collected at different times or locations are combined to obtain
an average composition.
Example: Mixing wastewater samples collected throughout the day.
4. Sampling Techniques
A. Solid Sampling
Crushing and grinding
Coning and quartering
