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ITECH5500 | Professional Research and Communication

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Federation University of Australia

   

ITECH5500 Professional Research and Communication (ITECH5500)

   

Added on  2020-03-07

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ITECH5500, we will discuss some solutions based on PROFESSIONAL RESEARCH AND COMMUNICATION, suggest valid ways for representing the data, talk about the reflection of the perceptions we collected that are true, and take hypothesis test in some given situations.

ITECH5500 | Professional Research and Communication

   

Federation University of Australia

   

ITECH5500 Professional Research and Communication (ITECH5500)

   Added on 2020-03-07

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Running Head: PROFESSIONAL RESEARCH AND COMMUNICATIONProfessional Research and CommunicationName of the StudentName of the University
ITECH5500 | Professional Research and Communication_1
1PROFESSIONAL RESEARCH AND COMMUNICATIONAnswer to Question 1The value that has been gathered from the survey is not a valid summary of data becauseof several reasons. First of all, the value generated is merely a mean rating from the valueschosen by the customers during the survey. However, it is not known whether the customershave given biased opinions or not. Secondly, the survey does not reflect the views of the entirecustomer base as many have not participated in the survey. It is possible that most of customerswho participated in the survey have only positive or negative reviews against the company(Krebs & Duncan, 2015). Finally, the main problem is that in this survey scale, it has beenassumed that the scale is evenly spaced i.e. the data generated is ordinal data but it has beentreated as interval data in the survey outcome.A more valid way of representing the same data is to change the answers that are selectedby the customers. Instead of predefining the scale of the data (1 to 5), the customers taking partin the survey should be given the chance to give a number in a scale of 1 to 5 or 10 based ontheir views on each question. This will generate actual interval data that can be then used foranalysis. Moreover, there will be less biasing in the values as the customers as they will entertheir own values instead of previously fixed values. Hence, this manual scaling method isrecommended for representing the collected data from the survey.Answer to Question 2If the general case is considered, then true reflection is not received from the datacollected from the online survey. This is mainly because many customers do not participate inthe survey due to lack of sufficient technical support or no interest in conducting surveys.
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2PROFESSIONAL RESEARCH AND COMMUNICATIONMoreover, some other genuine customers may also have no information regarding such a survey.As a result, there are insufficient amounts of opinion reflected in the survey (Aikens et al., 2014).Again, there is the problem of biasing. There may be some old customers of the company thatare biased towards it and hence, will give biased views on the company, reflecting only thepositive reviews instead of actual condition of the company. This type of biasing is common inthe movie ratings where, no matter how good or bad a movie is, the viewers will always rate thatmovie based on biased personal preferences and experiences. Similarly, the customers will havebiased personal preferences regarding the company. Again, in order to reach a particularconclusion regarding the services of the company, a large sample size necessary instead of asmall one in order to remove biasing as well as more variation in the ratings given by thecustomers (Denscombe, 2014). However, nowadays, almost everyone has a smartphone thesedays and more and more people can participate in the survey process. As a result, the abovediscussed limitations are getting more and more irrelevant as more customers are becomingactive participants in rating the company’s services. Answer to Question 3Data a – In this particular survey, the two responses are male or female. This is anexample of Nominal Data. Nominal data is the data that is not based on numerical values and issimply based on some word choices or as commonly called – labels (Gravetter & Wallnau,2016). The main significance and the key identification point is that the nominal data has nonumeric values and also do not overlap with each other if considered as distinct data sets. Hence,this data is nominal data.
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