Sampling and Data Collection Plan
Sampling and Data collecting Plan
October 9, 2014
University of Phoenix
QNT/561
Team D has chosen to look into whether or not should Pear Inc. should start putting their resources into either Laptops or tablet electronic devices. Putting resources into a venture that may or not pan out could be detrimental to that same company. As an example; Kodak and their choice not to expand into digital, something they created, and stay the course with their polyurethane film (Mui, 2012).In the end the choice the public made was to go to digital and have the image saved for ever instead of the inevitable fading of pictures and the breakdown of the film making Kodak play catchup.
Population, Size, and Target When considering of finding the population we have chosen social media for all sexes, ages, financial, and country demographics. The reasoning behind the choice is Pear’s product utilizes this source of media in particular. In addition social media is heavily used by the same people who frequent these sites. The sampling would reflect on Pear’s target audiences assisting in the choice of which direction to go with Pear’s resources. It determining size team D would like to obtain a min of 10% of the population of random sampling. Due to the time limit restraint of the weeks leading up to week 4 team D would like to see a 300 individual response to the choices of our chosen sampling element.
Sample Element Team D had talked about data mining, survey source, and observation. Data mining would need to look at the sales of both the Pear Book and the Pear Pad in a given business cycle of the most current year (Stat Soft, 2014). This is due the fact technology is growing so fast looking at data, even one year ago, may provide incorrect data in which put Pear on a different direction then it should be taken. Also data mining would only answer the direction the company is being taken too by the market and not determining or understanding the cause
October 9, 2014
University of Phoenix
QNT/561
Team D has chosen to look into whether or not should Pear Inc. should start putting their resources into either Laptops or tablet electronic devices. Putting resources into a venture that may or not pan out could be detrimental to that same company. As an example; Kodak and their choice not to expand into digital, something they created, and stay the course with their polyurethane film (Mui, 2012).In the end the choice the public made was to go to digital and have the image saved for ever instead of the inevitable fading of pictures and the breakdown of the film making Kodak play catchup.
Population, Size, and Target When considering of finding the population we have chosen social media for all sexes, ages, financial, and country demographics. The reasoning behind the choice is Pear’s product utilizes this source of media in particular. In addition social media is heavily used by the same people who frequent these sites. The sampling would reflect on Pear’s target audiences assisting in the choice of which direction to go with Pear’s resources. It determining size team D would like to obtain a min of 10% of the population of random sampling. Due to the time limit restraint of the weeks leading up to week 4 team D would like to see a 300 individual response to the choices of our chosen sampling element.
Sample Element Team D had talked about data mining, survey source, and observation. Data mining would need to look at the sales of both the Pear Book and the Pear Pad in a given business cycle of the most current year (Stat Soft, 2014). This is due the fact technology is growing so fast looking at data, even one year ago, may provide incorrect data in which put Pear on a different direction then it should be taken. Also data mining would only answer the direction the company is being taken too by the market and not determining or understanding the cause
References: Mui, C. (2012). How Kodak Failed. Retrieved on October 9, 2014 from http://www.fo rbes.com/sites/chunkamui/2012/01/18/how-kodak-failed/ SHMA (2012). 4 Types of Consumer Buying Behavior. Retrieved on October 9, 2014 from http://managementation.com/4-types-of-consumer-buying-behavior/ Stat Soft (2014). What is Data Mining (Predictive, Analytics, Big Data). Retrieved on October 9, 2014 from http://www.statsoft.com/Textbook/Data-Mining-Techniques