Qnt/275 Business Decision Making Project Part 3
Business Decision Making Project, Part 3
QNT/275
12/22/2014
Business Decision Making Project, Part 3
At the beginning of our week four team collaboration, members of Team A reflected on the outcomes of the study that we administered in the city of Pittsburgh, Pennsylvania. Our research utilized descriptive statistics to analyze the data that we collected. We were able to describe and summarize the data in a significant manner, by using charts and tables. Our descriptive statistics results involved measures of central tendency and measures of dispersion. As we continued with our discussion, we deliberated on which of the inferential statistics methods would be appropriate based on the data we achieved.
Inferential statistics enables us to use a hypothesis testing to draw a conclusion about a population parameter. In this case, the …show more content…
With the result we got, we were not able to make a well-reasoned inference based the Customer Service Representative sample we got from Pittsburgh. In addition, the scatterplots did not showcase a strong correlation. Therefore, we concluded that gathering a random sample and a proper sample size of Customer Service Representatives from various states would be a reliable choice.
Our new sample consists of a random selection of representatives, from ten randomly chosen states. We think that selecting individual at random will ensure that every representative in the customer service population will have an equal opportunity of being selected for the sample. Overall, acquiring a genuine random sample will eliminate any possibilities of bias conclusions.
After gathering the data from the sample, we used the data to determine the mean salary of male and female representatives’ respectively and combined. Next, we created scatterplots for each population, which is highlighted in the following
QNT/275
12/22/2014
Business Decision Making Project, Part 3
At the beginning of our week four team collaboration, members of Team A reflected on the outcomes of the study that we administered in the city of Pittsburgh, Pennsylvania. Our research utilized descriptive statistics to analyze the data that we collected. We were able to describe and summarize the data in a significant manner, by using charts and tables. Our descriptive statistics results involved measures of central tendency and measures of dispersion. As we continued with our discussion, we deliberated on which of the inferential statistics methods would be appropriate based on the data we achieved.
Inferential statistics enables us to use a hypothesis testing to draw a conclusion about a population parameter. In this case, the …show more content…
With the result we got, we were not able to make a well-reasoned inference based the Customer Service Representative sample we got from Pittsburgh. In addition, the scatterplots did not showcase a strong correlation. Therefore, we concluded that gathering a random sample and a proper sample size of Customer Service Representatives from various states would be a reliable choice.
Our new sample consists of a random selection of representatives, from ten randomly chosen states. We think that selecting individual at random will ensure that every representative in the customer service population will have an equal opportunity of being selected for the sample. Overall, acquiring a genuine random sample will eliminate any possibilities of bias conclusions.
After gathering the data from the sample, we used the data to determine the mean salary of male and female representatives’ respectively and combined. Next, we created scatterplots for each population, which is highlighted in the following