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Formulation of goals and hypotheses
A hypothesis is a prediction or statement that you make before you collect data. Normally this is based on theory, z. 'A CBD has the highest concentration of comparison shops.' During your investigation, you try to prove or refute your hypothesis. You do this by gathering relevant data, analyzing it and analyze the conclusion.
A hypothesis should always be smart. If your hypotheses are not smart, it may not be possible to prove or refute them.
The main objective of collecting data should be as objective as possible, ie their results are not biased or influenced by personal opinion.
Goal: This is if the data collection is not influenced by the personal opinion of people. This is very difficult to achieve because even the design of data collection forms is influenced by people's opinion. However, it is possible to try to be as objective as possible by resulting in scanning technique, collect data in groups and follow the methodology.
Subjective: This is if your personal opinion has an influence on the result of data collection. Everyone has personal preload, so this is not necessarily bad, but they should recognize this in their methodology and evaluation.
You can use a variety of primary and secondary data. A combination of the two is often preferred because this means that they have data they have raised first-hand, as well as data collected on a large scale.
Primary data: All data you have collected (this does not mean to pick up the Internet). Primary data can contain traffic counts, pedestrian counts, environmental indexes, questionnaires or land use surveys.
Secondary data: All data collected by another person. The secondary data collection can be found in books, the Internet, academic magazines, etc., probably the most useful secondary data are census. A census is a survey that is carried out every 10 years in the majority of the countries. It is a detailed survey that is compulsory for all to fill out.
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