Correlation and/or regression analysis

Once all of the necessary data has been collected for each variable—that is, once survey results have been obtained from employees about their jobs and financial information has been gathered related to company performance—correlation coefficients can then be calculated by running statistical tests on the data. The Pearson product-moment correlation coefficient is one way of determining whether a positive or negative relationship exists between two variables; if a strong positive association exists between them then they are likely linked in some way (Creswell & Tashakkori 2014). If a statistically significant result emerges when conducting these tests it suggests that there may indeed exist some kind of link between employee job satisfaction and company performance; further exploration into this possible connection through additional studies may then need to occur in order for definitive conclusions about causality can be drawn. In addition, regression analysis might also prove useful here because it enables researchers to determine well how much impact different predictor variables—in this case employee job satisfaction—might have on an outcome variable like company performance (Creswell & Tashakkori 2014). To do this effectively multiple regression models must firstly be developed by inputting both predictor and outcome data into software packages such as SPSS or SAS so that mathematical equations expressing the relationships among those same predictors can then emerge. Once established these equations allow us not only make predictions based on certain given values but also show just how much influence particular predictors have over outcomes – hence demonstrating what role exactly job satisfaction plays when trying explain variations in organizational success rates . References: Babbie ER (2017) The Basics Of Social Research 8th edn Boston MA: Cengage Learning Creswell JW & Tashakkori A eds.(2014) Handbook Of Mixed Methods In Social And Behavioral Research Thousand Oaks CA: Sage Publications Ltd Frisbie DA & Haddock JR eds.(2019) Human Resource Management 14th edn Mason OH: Cengage Learning Hannah ST et al.(2020) 'Organizational Performance' In Encyclopedia Of Business Analytics And Optimization IGI Global Hershey PA Available At https://doi-org.proxy2-ec2.mybluemixnet/104090/9781799804526 Accessed 13 Sept 2020

Sample Solution

A correlation and/or regression analysis can be used to analyze the research question of whether there is a relationship between employee job satisfaction and company performance. This type of data analysis involves using quantitative methods to examine the relationships between two or more variables. Correlation and regression analyses can help researchers identify the strength, direction, and nature of any relationships that exist (Frisbie & Haddock, 2019). A correlational research design would be most appropriate in this situation as it allows researchers to look at how two variables relate without controlling any other outside factors (Babbie, 2017). The two variables that would need to be examined in order to answer the research question are employee job satisfaction and company performance. Employee job satisfaction is defined as “the extent to which employees feel satisfied with their jobs” (Frisbie & Haddock, 2019). Company performance refers to “how well an organization meets its goals or objectives” (Hannah et al., 2020). Both of these variables must be measured using valid measures; for example, surveys could be used to measure factors such as employee job satisfaction while financial reports could assess aspects such as profits or sales revenue related to company performance.