Predictors of Happiness, Essay Example

Research Design

The research type will be quantitative in nature. A quantitative method consists of statistical techniques in data evaluation (Basias & Pollalis, 2018). The quantitative method assists in establishing the relationship between variables to test the hypothesis (Rashid & Sipahi, 2021). A survey will be utilized to accumulate information.

Sampling

The sample will consist of about 200 participants between 18 and 50 years. Since the age estimate is known, purposive sampling will recruit respondents. In purposive sampling, the researcher selects respondents based on their characteristics (Etikan et al., 2016). Descriptive tests will determine participants’ average age and frequency (Durón-Ramos, & García-Vázquez, 2018). The geographical location of the participants will be established.

Data Collection

The degree of happiness will be evaluated using the subjective or general happiness scale. The scale will contain four to ten items subdivided into subscales (Lyubomirsky & Lepper, 1999). The researcher will also formulate a second scale that evaluates the interrelationships between variables. The contributors will be provided with questionnaires to verify three areas. The main section will have Likert-scale questions that will allow the degree of participants’ responses to be evaluated (Joshi et al., 2015). These questionnaires will take roughly twenty minutes each to be finalized. The information from the questionnaires will be compiled into correct formats for convenience.

Data Analysis

The two scales will be used to evaluate the predictors of happiness. The feasibility of these scales will be determined through internal consistency tests. Statistical tools such as SPSS will be used in data evaluation (Okagbue et al., 2021). The descriptive methodology will evaluate the overall nature of data, such as average (Mishra et al., 2019). Tests such as the ANOVA test will be used to assess the interconnection between variables (Kim, 2017). Multiple regression tests may also be used to test the variables linked to happiness (Garaigordobil, 2015). Predictors of happiness indicators can include health, nature, self-esteem and corporation. The discussion section will highlight the relevance of promoting the predictors of happiness following the research results.

References

Basias, N., & Pollalis, Y. (2018). Quantitative and qualitative research in business & technology: Justifying a suitable research methodology. Review of Integrative Business and Economics Research, 7, 91-105. https://sibresearch.org/uploads/3/4/0/9/34097180/riber_7-s1_sp_h17-083_91-105.pdf

Durón-Ramos, M. F., & García-Vázquez, F. (2018). Orientation to Happiness as Predictor of University Students’ Engagement. International Journal of Evaluation and Research in Education, 7(4), 294-298. http://files.eric.ed.gov/fulltext/EJ1198615.pdf

Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of convenience sampling and purposive sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1-4. https://www.academia.edu/download/55796997/Comparison_Convenience_and_Purposive_Sampling-2016_4p.pdf

Garaigordobil, M. (2015). Predictor variables of happiness and its connection with risk and protective factors for health. Frontiers in Psychology, 6, 1176. https://doi.org/10.3389/fpsyg.2015.01176

Joshi, A., Kale, S., Chandel, S., & Pal, D. K. (2015). Likert scale: Explored and explained. British Journal of Applied Science & Technology, 7(4), 396. https://eclass.aspete.gr/modules/document/file.php/EPPAIK269/5a7cc366dd963113c6923ac4a73c3286ab22.pdf

Kim, T. K. (2017). Understanding one-way ANOVA using conceptual figures. Korean Journal of Anesthesiology, 70(1), 22. https://dx.doi.org/10.4097%2Fkjae.2017.70.1.22

Lyubomirsky, S., & Lepper, H. S. (1999). A measure of subjective happiness: Preliminary reliability and construct validation. Social Indicators Research, 46(2), 137-155. https://doi.org/10.1023/A:1006824100041

Mishra, P., Pandey, C. M., Singh, U., Gupta, A., Sahu, C., & Keshri, A. (2019). Descriptive statistics and normality tests for statistical data. Annals of Cardiac Anaesthesia, 22(1), 67. https://dx.doi.org/10.4103%2Faca.ACA_157_18

Okagbue, H. I., Oguntunde, P. E., Obasi, E. C., & Akhmetshin, E. M. (2021). Trends and usage pattern of SPSS and Minitab Software in Scientific research. Journal of Physics: Conference Series, 1734(1), 1-8. https://iopscience.iop.org/article/10.1088/1742-6596/1734/1/012017/pdf

Rashid, M. H., & Sipahi, E. (2021). The importance of quantitative research in language testing and assessment: in the context of social works. Linguistics and Culture Review, 5(S1), 317-330. https://doi.org/10.21744/lingcure.v5nS1.1413