Math m2

• Data collection - is a systematic approach to get a relevant information from a variety of sources depending on the problem statement.
• Primary data - have been collected from first-hand-experience. Those data can be obtained by doing interview, observation, or experimentation.
• Secondary data - are data collected from a source that has already been published in any form. Those data can be obtained from books, newspapers, magazines, journals, biographies or thesis of other researchers.
• Interview - This method is also known as direct method of gathering data, it is a person-to-person inquiry.
• The person gathering the data is called the - interviewer
• Questionnaire - It is known as indirect method ofgathering data because it includes set of written questions to be answered by the respondents. The questions should be specific and clear to obtain accurate information.
• observation - This method makes use of senses in gathering information that involves behavior or attitudes of individuals or a group of individuals.
• Census - It is also known as registration. Data are collected for each and every element/unit of the population.
• Experimentation - This is the process of performing scientific to determine something.
• Sampling - a process of choosing a representative of a population. The chosen representative is referred to as the sample.
• 1. Probability Sampling - In this sampling procedure, every element of a population is given an equal chance of being included in the sample.
• Simple random sampling - can be done by picking up written names placed in a bowl or picking out names from a computer-generated system.
• Systematic sampling - is the process of selecting every nth element in the population until the desired number of samples are obtained. From a list of population, we can pick a sample systematically using a set of intervals like every 4th, 10th, 15th, etc.
• Stratified sampling - is done by dividing the population into strata or classes. Each stratum may be formed based on members' shared attributes or characteristics.
• Cluster sampling - is done in randomly selecting groups or cluster of elements from a population and then from each cluster, the researcher selects the sample randomly. The researcher can even opt to include the entire elements in the chosen cluster.
• Non-probability Sampling - In this sampling procedure, not every element of a population is given an equal chance of being included in the sample.
• Convenience sampling - is a method in which people are chosen because they are convenient sources of data for researchers.
• Quota sampling - is similar to stratified sampling but the drawing of samples in quota sampling is not done randomly. If the desired quota is reached, the drawing of samples is terminated.
• Purposive sampling - is done when the criteria of the study satisfy a particular sample.
• what sampling - systematic

  
• what sampling - stratified

  
• what sampling - cluster

  
• what sampling - convenience

  
• what sampling - quota

  
• what sampling - purposive