Business Decision Making Process

Research Work

Student’s Name

Institution

Graphical Techniques

This paper is a continuation of Week 2. Week 4 is a continuation of Week 3. All weeks are written on the same recycled document for maximum weekly points. The topic last week was Fizzy. That should be the topic this week.  

Writing style. When writing this type of paper, keep focused on the project. If the research variables are quantitative, qualitative variables are unimportant. 

You may resubmit this paper once you decide on a common topic. Combine the Week 2 and Week 3 papers using the Word template. 

RESEARCH WORK 1

Research variables

For my research work, I will focus on determining the relationship between employee job satisfaction and employee performance. Hence, the two variables would be employee job satisfaction and employee performance. Creswell (2014) refers to research variables as people, phenomenon, or place that a researcher is trying to measure in one way or another. Research variables are classified into dependent and independent variable. Independent variables cause changes in dependent variables and it is impossible for dependent variable to cause changes in dependent variables.

The variables were not discussed.

Collection of Data Sample

A random sampling technique will be used for the study. To do so, I will first of all define the study population. The study population will include the total number of workers in a given organization. I will target an organization with 500 employees. After determining the study population, I will choose a sample size because of budget and time limitations. I will use Raosoft (2004) to determine a sample size for the study. With a population size of 500, Raosoft (2004) recommends a sample size of 218 employees. To select a sample of 218 employees, I will have to identify all 500 workers at the organization. After listing the population, I will assign consecutive numbers, starting from 1 to 500, next to each employee. The next step will involve determination of random number, which would be determined by using a random number table. Finally, I will select which of the 500 employees to invite for the study. In essence, I will select 218 random numbers listed in the random table.

The above paragraph is quite good.

Validation of Data Collection Process

Data validity and reliability is very important in any research work. Cresswell (2014) refers to validity as the essential truthfulness of data. A researcher asserts validity by indicating that the data collected actually measures or reflects a claimed phenomenon. Reliability, on the other hand, relates to a researcher’s assertion regarding data accuracy. Hence, it is important to determine the purpose of a study before collecting data. It is possible to determine the type of data to collect by having a problem statement. Having a research question can also help in determining the type of data worth collecting, whether quantitative or qualitative data.

Wang (2015) indicates that quantitative data is normally expressed in numbers and/or graphs and analyzed with the help of statistical methods. Qualitative data is usually expressed in words and analyzed based on interpretations and categorizations. Quantitative data is suitable for hypothesis testing while idea exploration requires qualitative data. It is also important to determine data collection method for data reliability and validity. For instance, experimental research requires quantitative method, interviews and ethnography require qualitative methods, and surveys require either quantitative or qualitative methods. To ensure data validation, it is important to record relevant information whenever they are obtained and to double check data entry for any errors. It is also important to ensure that data measurements are done using calibrated instruments.

The above section is too general. It needs to be specific to the data being collected.

References

Cresswell, J. W. (2014). Research design: Qualitative, quantitative and mixed methods approaches (4th ed.). Thousand Oaks: Sage publications.

Raosoft. (2004). Raosoft: Sample size calculator. Retrieved from http://www.raosoft.com/samplesize.html

Wang, K. T. (2015). Research design in counseling (4th ed.). Boston, MA: Cengage Learning