Understanding Types of Data and Sampling Methods

Understanding Types of Data and Sampling Methods

Learning Objectives

At the end of the lesson, you will be able to differentiate between primary and secondary data.

What do you already know about primary and secondary data?

Primary Data vs. Secondary Data

Primary data: Your own or group data that is collected firsthand on the day of the fieldwork.

Quantitative Data vs. Qualitative Data

Quantitative data: Data with a numerical value.
Qualitative data: Data as words, views, or feelings.

Reliability in Data Collection

Reliability: Where the data can be trusted to give an accurate representation.

Bias in Sampling

Bias: Where your sampling does not represent the whole data set because you have selected preferred data.

Sampling Techniques

Sampling: A selection of data to represent the information you want to collect, sampled in a planned way to avoid bias.

Systematic Sampling

Systematic sampling: Having a system to collect samples, such as every 2m along a transect or every 5th person.

Random Sampling

Random sampling: Using random numbers to select a sample, ensuring an unbiased selection.

Stratified Sampling

Stratified sampling: Using prior knowledge to decide where you collect samples from a selected area or group.

Definition List

Primary data: Your own or group data that is collected firsthand on the day of the fieldwork.
Secondary data: Data collected from another source, which may be current or historical, and collected by someone else.
Quantitative data: Data with a numerical value.
Qualitative data: Data as words, views, or feelings.
Reliability: Where the data can be trusted to give an accurate representation.
Bias: Where your sampling does not represent the whole data set because you have selected preferred data.
Sampling: A selection of data to represent the information you want to collect, sampled in a planned way to avoid bias.
Systematic sampling: Having a system to collect samples, such as every 2m along a transect or every 5th person.
Random sampling: Using random numbers to select a sample, ensuring an unbiased selection.
Stratified sampling: Using prior knowledge to decide where you collect samples from a selected area or group.

Write down 3 things you learned in this lesson.

Have students enter three things they learned in this lesson. With this they can indicate their own learning efficiency of this lesson.

Write down 2 things you want to know more about.

Here, students enter two things they would like to know more about. This not only increases involvement, but also gives them more ownership.

Ask 1 question about something you haven't quite understood yet.

The students indicate here (in question form) with which part of the material they still have difficulty. For the teacher, this not only provides insight into the extent to which the students understand/master the material, but also a good starting point for the next lesson.