Difference between revisions of "AY1516 T2 Group 18 Data"
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==<div style="background:#ff4fa7; padding: 10px; font-size: 14px; font-weight: bold; line-height: 1em; text-indent: 15px; border-left: #D3D3D3 solid 25px;"><font color="white">Data</font></div>== | ==<div style="background:#ff4fa7; padding: 10px; font-size: 14px; font-weight: bold; line-height: 1em; text-indent: 15px; border-left: #D3D3D3 solid 25px;"><font color="white">Data</font></div>== | ||
| − | + | <b>Data Provided</b><br> | |
| − | + | The Singapore and Malaysia data provided to us by TNS was collected via online panels and weighed afterwards in proportion of population representative for both countries. The data was presented to us in an SPSS format and is cleaned. This is because the online questionnaires in the online panels were programmed in a way where logic checks and routing were done during the data collection process. In addition, the data collected was also automatically coded in the background based on the specifications in the survey questionnaire, which was also given to us.<br><br> | |
| − | The data was presented to us in an SPSS format and is cleaned. This is because the | ||
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| + | <b>Data Preparation</b><br> | ||
| + | Even though the data presented to us has been preliminarily cleaned by the online panels, there is still a need to go through a second stage of cleaning to ensure that the data is relevant for the purpose of this project. There is also a need to filter out outliers and anomalies. As we are only focusing on one particular sector, we also need to filter out all the questions catered specifically for other irrelevant market sectors. This allows us to focus on the key objectives better and provide more meaningful visualization.<br><br> | ||
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| + | In order to provide more in-depth analysis and insights, we will need to explore the data to understand various aspects of the data further. After which, we will also need to manipulate certain variables to create multi-dimensional views of the data. E.g. creation of a derivative variable.<br><br> | ||
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| + | <i>Note:</i><br> | ||
| + | We have identified variables from the dataset to be useful for the purpose of our analysis. However. due to NDA with the company, more information will be only be made available in the project proposal.<br> | ||
| + | Sample dataset will be in the project proposal as well. | ||
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Revision as of 06:58, 12 January 2016
Data
Data Provided
The Singapore and Malaysia data provided to us by TNS was collected via online panels and weighed afterwards in proportion of population representative for both countries. The data was presented to us in an SPSS format and is cleaned. This is because the online questionnaires in the online panels were programmed in a way where logic checks and routing were done during the data collection process. In addition, the data collected was also automatically coded in the background based on the specifications in the survey questionnaire, which was also given to us.
Data Preparation
Even though the data presented to us has been preliminarily cleaned by the online panels, there is still a need to go through a second stage of cleaning to ensure that the data is relevant for the purpose of this project. There is also a need to filter out outliers and anomalies. As we are only focusing on one particular sector, we also need to filter out all the questions catered specifically for other irrelevant market sectors. This allows us to focus on the key objectives better and provide more meaningful visualization.
In order to provide more in-depth analysis and insights, we will need to explore the data to understand various aspects of the data further. After which, we will also need to manipulate certain variables to create multi-dimensional views of the data. E.g. creation of a derivative variable.
Note:
We have identified variables from the dataset to be useful for the purpose of our analysis. However. due to NDA with the company, more information will be only be made available in the project proposal.
Sample dataset will be in the project proposal as well.
