Statistical Data Collection Methods - Making Sense of the Mine Field

When use correctly, statistical data can be used to improve an array of areas from efficiency, to lead time, and profit. But in order to make improvements you need to know how the data has been collected initially. This article is about Statistical data collection methods.

There are four main Statistical data collection methods:

Census
Sample survey
Experiment
Observational study

Each of these methods has it's own set of advantages and drawbacks, that's why one must be aware of all their characteristics to be able to choose the right method according to the individual situation. Here is a brief definition of each method:

Census - A census is a case study that acquires data from every population member. For the majority of cases, a census is not practical, due to the large amount of time and cost required to conduct it.
Sample Survey - A sample survey is a case study that obtains data only from a subset of the entire population, not every member, as oppose to Census, so it's much more practical and efficient to carry out, but the results might not be that accurate. For best results using this method it may be appropriate sub-categorize your target group and take a sample set from each sub-category. A basic example would be different ethnic groups.

Experiment - The experiment is a controlled study in which researchers try to understand the cause-and-effect relationships, how one thing affects another.

Observational study - Observational studies also try to discover the cause and effect relations, but unlike experiments, they are not able to control how subjects are assigned to groups.

As it was already pointed out, every method has its own pros and cons, so one must be able to know and make a decision regarding which method should be applied in a given situation. There are three factors that should affect this decision and they are - resources, generalizability, causal inference.

If resources are the main factor, then obviously with such a large population, a sample survey has an advantage over census. If the sample survey is well designed, then it can definitely provide results that are really close to the actual figures (high level of accuracy), and it will be done in a quicker and cheaper manner, requiring less man power than a census.

Generalizability stands for applying findings from a sample study to a larger population. Generalizability requires random selection. In case the participants in a study are randomly selected from a larger population, it is appropriate to generalize study results to the larger population, otherwise it might provide accurate results.

Statistical data collection methods are essential for sustainable economics, social and environmental development. We are living in the 'Information Age' where certain data sets are growing in size and complexity, reaching massive proportions, that's why such data collection methods are so important.

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Web Data Extraction Services and Data Collection Form Website Pages

For any business market research and surveys plays crucial role in strategic decision making. Web scrapping and data extraction techniques help you find relevant information and data for your business or personal use. Most of the time professionals manually copy-paste data from web pages or download a whole website resulting in waste of time and efforts.

Instead, consider using web scraping techniques that crawls through thousands of website pages to extract specific information and simultaneously save this information into a database, CSV file, XML file or any other custom format for future reference.

Examples of web data extraction process include:

• Spider a government portal, extracting names of citizens for a survey
• Crawl competitor websites for product pricing and feature data
• Use web scraping to download images from a stock photography site for website design

Automated Data Collection

Web scraping also allows you to monitor website data changes over stipulated period and collect these data on a scheduled basis automatically. Automated data collection helps you discover market trends, determine user behavior and predict how data will change in near future.

Examples of automated data collection include:

• Monitor price information for select stocks on hourly basis
• Collect mortgage rates from various financial firms on daily basis
• Check whether reports on constant basis as and when required

Using web data extraction services you can mine any data related to your business objective, download them into a spreadsheet so that they can be analyzed and compared with ease.

In this way you get accurate and quicker results saving hundreds of man-hours and money!

With web data extraction services you can easily fetch product pricing information, sales leads, mailing database, competitors data, profile data and many more on a consistent basis.

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Data Collection, Just Another Way To Gather Information

Data collection just does not help the companies to launch new products or know about the public reaction to a specific issue, it is a very useful tool for statistical inferences, once the collected data is compiled. The process of data collection is the third step of the six step market research processes. Data collection can be done in two ways involving various technicalities. In this article, we shall give a brief overview of the same.

Data collection can be done in two ways - secondary data and primary data. Secondary data collection involves is the information available in books, journals, previous researches or studies and the Internet. It basically involves making use of the data already present to build or substantiate a concept.

On the other hand, primary data collection is the process of data collection through questionnaire by directly asking respondents of their opinions. Forming the right questionnaire is the most important aspect of data collection. The researcher conducting the data collection just has to be aware of the process. He should have a clear idea about the information sought by the concerned party.

Besides, the data collection officer should be able to construct the questionnaire in such a way so as to elicit the responses needed. Having constructed the questionnaire the researcher should identify the target sample. To illustrate the point clearly, we shall look into the following example.

Suppose, data collection is aimed from an area A, then, if all the residents of the data are given the questionnaire, it is called a census or in other words data collection is done from all the individuals of the specified area. One of the most common examples of data collection done by the government is census. For example the population census conducted by the US Census Bureau every ten years. On the other hand, if only twenty or thirty percent of the population living in area A are given the questionnaire, the mode of data collection would be called sampling.

The data collected from the target sample with a well-defined questionnaire will project the response of the entire population living in the area. Data collected from a sample helps to control the cost and time spent on collecting data from the population. Sample is a part of population.

Data collection just gets easier from the target sample with the help of a pretested questionnaire, which is later analyzed using statistical tests like ANOVA, Chi Square test and so on. These tests help the researcher to infer the result obtained from the data collection.

Market research/data collection is a fast growing and lucrative career option now days. One has to undertake a course in marketing, statistics and research before starting out. It is indeed very important to have a through understanding of various concepts and the theories related. Some basic terminologies related to data collection are: census, incidence, sample, population, parameters, sampling frames and so on.

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