The types of probability sampling include simple random, systematic, stratified, cluster, resampling and convenience. Explain two of the methods in your own words and provide an example of each. Your explanation should contain 200-250 words. Also, respond to two of your peer's postings. Your response to your peers should expand on their definition or examples. Reply to these two. 1) Going through the PowerPoints I have understood more information than other information. The two terms that stood out to me was simple random sampling. To me the easiest way to look at this term is as an unbiased method. It’s a random picking as such, it can be an act of being chosen from a group of people and each individual is chosen randomly, they all have the same chance of being picked no matter of their skin tone, career, eye color, etc, it doesn’t really matter. For example, a teacher in a classroom wants to play a game, but the game requires 5 people at a time So, she decides to use the hat trick where she rights down names on a piece of paper and draw from the hat breaking the name of kids into her selected choice, but first she must count the total amount of students to determine who might participate in the game at the moment. The other term I find quite easy to understand was convenience sampling. To my understanding it is the most quick and easiest way to collect data. For example, I go to fast food restaurants all the time and after I have ordered my food, I receive a receipt. At the end of that receipt, it asks me to survey my experience at that particular restaurant. For me, and my mama we like Whataburger surveys because most of the time we experienced something nice, and additionally we want the coupon for the next time we eat at Whataburger. Fill out the survey or calling a specific number, we have experienced a convenience sample. This method was so easy for the whataburger to acquire information from. 2) A simple random sample is a subset of a population chosen at random. Each member of the population has an exact equal chance of being chosen in this sampling process. Since it only requires a single random selection and no prior knowledge of the population, this approach is the easiest of all the probability sampling methods. Since it employs randomization, any reversal is impossible. An example of a simple random sample could be: Each employee on an assembly line is given a random number by computer software. The same program is used on a regular basis to select a variety of workers to be observed in order to ensure that they are following best practices. Systematic sampling is a probability sampling method where researchers select members of the population at a regular interval. Researchers use systematic sampling as a statistical tool to narrow down the population they want to study. The sampling interval is calculated by dividing the total population size by the desired sample size. Systematic sampling is an extension of probability sampling in which each member of the group is selected to form a sample at regular intervals. An example of systematic sampling would be an employee of a movie theatre can give a survey to every fourth customer that comes in to the movie theater. The types of probability sampling include simple random, systematic, stratified, cluster, resampling and convenience. Explain two of the methods in your own words and provide an example of each. Your explanation should contain 200-250 words. Also, respond to two of your peer's postings. Your response to your peers should expand on their definition or examples. Reply to these two. 1) Going through the PowerPoints I have understood more information than other information. The two terms that stood out to me was simple random sampling. To me the easiest way to look at this term is as an unbiased method. It’s a random picking as such, it can be an act of being chosen from a group of people and each individual is chosen randomly, they all have the same chance of being picked no matter of their skin tone, career, eye color, etc, it doesn’t really matter. For example, a teacher in a classroom wants to play a game, but the game requires 5 people at a time So, she decides to use the hat trick where she rights down names on a piece of paper and draw from the hat breaking the name of kids into her selected choice, but first she must count the total amount of students to determine who might participate in the game at the moment. The other term I find quite easy to understand was convenience sampling. To my understanding it is the most quick and easiest way to collect data. For example, I go to fast food restaurants all the time and after I have ordered my food, I receive a receipt. At the end of that receipt, it asks me to survey my experience at that particular restaurant. For me, and my mama we like Whataburger surveys because most of the time we experienced something nice, and additionally we want the coupon for the next time we eat at Whataburger. Fill out the survey or calling a specific number, we have experienced a convenience sample. This method was so easy for the whataburger to acquire information from. 2) A simple random sample is a subset of a population chosen at random. Each member of the population has an exact equal chance of being chosen in this sampling process. Since it only requires a single random selection and no prior knowledge of the population, this approach is the easiest of all the probability sampling methods. Since it employs randomization, any reversal is impossible. An example of a simple random sample could be: Each employee on an assembly line is given a random number by computer software. The same program is used on a regular basis to select a variety of workers to be observed in order to ensure that they are following best practices. Systematic sampling is a probability sampling method where researchers select members of the population at a regular interval. Researchers use systematic sampling as a statistical tool to narrow down the population they want to study. The sampling interval is calculated by dividing the total population size by the desired sample size. Systematic sampling is an extension of probability sampling in which each member of the group is selected to form a sample at regular intervals. An example of systematic sampling would be an employee of a movie theatre can give a survey to every fourth customer that comes in to the movie theater.
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