Data Collection
Data collection is any process of preparing and collecting data, for example, as part of a process improvement or similar project. The purpose of data collection is to obtain information to keep on record, to make decisions about important issues, or to pass information on to others. Data are primarily collected to provide information regarding a specific topic.
Data collection usually takes place early on in an improvement project, and is often formalized through a data collection plan which often contains the following activity: 1. Pre collection activity — agree on goals, target data, definitions, methods 2. Collection — data collection 3. Present Findings — usually involves some form of sorting analysis and/or presentation.
There are two broad categories of data collection in research: 1. Probability Sampling 2. Non-probability sampling
Probability
* Probability sampling is a random method of selection in a targeted population. To conduct randomized samples, you need to make sure everyone in the population is given an equal chance to be chosen.
Simple Random Sampling * The simplest sampling technique is the simple random sampling, which is a lottery method of randomly picking from the targeted population. For instance, if a thesis is about malnourished students in a school, your sample size is 50 and there are 200 malnourished students, put all 200 names in a hat and pick out 50.
Stratified Random Sampling * Stratified or proportional sampling aims to find a population for the entire population and for subgroups within the population. Taking the example on the previous technique, in the population of 200, there are 100 fifth-grade students, 50 second-grade students and 50 third-grade students. Since the sample size is 50 -- 25 percent of the population -- you need to take 25 percent from each of the three grade levels. As a result, you would have 25 fifth-graders and 12.5 second-graders and 12.5 third-graders. After
Data collection usually takes place early on in an improvement project, and is often formalized through a data collection plan which often contains the following activity: 1. Pre collection activity — agree on goals, target data, definitions, methods 2. Collection — data collection 3. Present Findings — usually involves some form of sorting analysis and/or presentation.
There are two broad categories of data collection in research: 1. Probability Sampling 2. Non-probability sampling
Probability
* Probability sampling is a random method of selection in a targeted population. To conduct randomized samples, you need to make sure everyone in the population is given an equal chance to be chosen.
Simple Random Sampling * The simplest sampling technique is the simple random sampling, which is a lottery method of randomly picking from the targeted population. For instance, if a thesis is about malnourished students in a school, your sample size is 50 and there are 200 malnourished students, put all 200 names in a hat and pick out 50.
Stratified Random Sampling * Stratified or proportional sampling aims to find a population for the entire population and for subgroups within the population. Taking the example on the previous technique, in the population of 200, there are 100 fifth-grade students, 50 second-grade students and 50 third-grade students. Since the sample size is 50 -- 25 percent of the population -- you need to take 25 percent from each of the three grade levels. As a result, you would have 25 fifth-graders and 12.5 second-graders and 12.5 third-graders. After