Data gathering is useful to everyone. The data gathered can be use to predict trends and to develop responses to address the trend. It can also be used to understand how a lot of things work. So whether you’re gathering data for a class requirement, or for other purposes like business and research, it’s very important to be knowledgeable about how data should be collected.

Any type of data collection relies a lot in selecting a good sample especially if the population is too big for you to cover. The sample should be able to represent the whole target population. There are two types of sampling method, Probability Sampling and Non-Probability Sampling.

Probability sampling includes: Random sampling, Cluster sampling, Systematic sampling and Stratified sampling. Non probability sampling method includes Convenience sampling, and Voluntary sampling. Some researchers who uses convenience sample, which would entail conducting a survey

Apart from the sampling methods, we will also be learning the Influencing Factors in Data Collection such as bias, time constraints, cultural sensitivity, ethics and costs. We will have several examples to illustrate those in 11.1. There are real life examples of influencing factors in Data Collection such as those biased results that favor the interests of the sponsors of a particular research and those that discloses deficient data.

In the next part of the chapter, we will be tested as to what kind of sampling method is best to use for certain kinds of scenario that are given and in 11.3, we will use the data we have been able to gather and use that to look at their probabilities.

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This lesson answers the question: What are the differences between mean, median and mode in statistics? Also, we will learn how to calculate the probabilities out of a two-way frequency table, and figure out the trends.


  • 2.
    Six hundred people were randomly selected in downtown. They were asked if they choose their clothes based on its comfort or style. The following is the results:
















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