Research Design Business Research Methods

Question: Discuss about the Research Design for Business Research Methods. Answer: Introduction Gym has become an important part for the fitness of the people. Most of the people usually go to gym to stay fit. They have different proportions of height and weight and their Body Mass Index vary from each other (Yu et al., 2014). The customers go to the gym for various purpose like gaining strength or losing weight. Data had been collected on surveying the customers of the gym. In this assignment, these collected data would be analyzed using statistical techniques. Analysis and interpretation of this collected data would provide an idea about the chosen gym. Graphs and charts would be provided in this assignment in order to support the analysis of the data. Review of academic sources As per the survey on 996 adults for the data of gym, it was seen that 452 samples had responded to the survey. As per the viewpoint of Yu et al. (2014), it was seen the samples who have lesser amount of moderate intensity have higher value of BMI and higher value of overall worse health. Thus, it was seen that a relationship exists between the intensity of physical activity and the BMI of the sample. On spending ample amount of time in gym, higher intensity of physical activity is performed which improves the health condition of the respondents. Thus, 20 percent of the variance of BMI is explained by the intensity of the physical activity performed by the respondent. Simple bivariate analysis Two numerical variables, height and weight are selected for the purpose of the analysis. Scatter plot is drawn for these two variables in order to find the relationship between them. The scatter plot of the two numerical variables is given below: The scatter plot shows that the direction of data for height and weight is an increasing trend. It can be interpreted that with the increase in height, there is an increase in the weight of the sample. The mean of the numerical variable height was found to be 170.55 units while the mean of the weight was found to be 76.36 units. The standard deviation of the numerical variable height was found to be 12.81 units while the standard deviation of the numerical variable weight was found to be 15.22 units (Kock, 2013). It is seen that both the numerical variables height and weight are moderately distributed over the data set. It is seen that with the increase in the height, there is an increase in the weight of the person. On considering the file of proposed change data, it was seen that 758 customers had supported the proposed change while 242 customers do not support the proposed change. Managerial advice From the given data, it was found that BMI and Minutes spend on cardio are two important factors as amount of time spent of exercises of cardio influences the BMI of the person. It is seen that the average value of BMI lies in the range of 18.5 to 25 kg/m2. When any people have BMI above 25 kg/m2, it is termed as overweight. It is advised that the people having their BMI above 25 kg/m2, would be advised to spend more time on the cardio machines so that they can reduce their BMI and have a fit physic. Analysis of the data in context of proposed change On analyzing the data, it was seen that the 95% confidence interval of the customers who have their BMI above 25 kg/m2 was found to be (0.54592, 0.73408), where 0.54592 is the lower limit of the interval and 0.73408 is the upper limit of the interval (Vogt Barta, 2013). One sample t-test was performed to test the claim that more than 50 percent of the customers support the change in the given proposal. The z value of this one sample t-test for proportion was found to be 2.916667 and the p value of the test was found to be 0.001769. This p value of the test was found to be less than 0.05 (Candela et al., 2014). The hypothesis of the test can be written as: H0: p = p0 and H1: p p0. At 5 percent level of significance, the p value of the test was found to be significant and this leads to the rejection of null hypothesis. Thus, it can be interpreted that more than 50 percent of the customers support the proposed change in their gym It can be concluded that the average value of height and weight was found to be 170.55 units and 76.36 units respectively. The standard deviation of the two numerical variables height and weight was found to be 12.81 untis and 15.22 units. The proposed change in the gym was advised to segregate the customers who have their BMI above 25 kg/m2. This proposed change was found to be supported by more than 50 percent of the customers. The 95% confidence interval of the customers who have their BMI above 25 kg/m2 was found to be (0.54592, 0.73408). Abuses of statistics The issues with questionnaire are that the samples were selected from America and Germany. Samples from other countries were not considered in this case and thus, it would not provide the overall views of the customers in context of gym. Other measures of statistics like correlation and regression could have been used to find the relationship between the variables. Limitations of quantitative research There are various limitations of quantitative researches. It is seen that quantitative research is time consuming and expensive and it is difficult (Creswell, 2013). On asking close ended questions, the respondents sometimes cannot understand the objective of the questions and they do not provide correct option which leads to the biasness in the data. Structured close ended questions leads to limited outcomes in a generalized form (Field, 2015). Another limitation involves use of extensive statistical analysis on analyzing the quantitative data. References Candela, A., Brigand, G., Aronica, G. T. (2014). Estimation of flood design hydrographs using bivariate analysis (copula) and distributed hydrological modelling.Natural Hazards and Earth System Sciences Discussions,2, 27-79. Creswell, J. W. (2013).Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications. Field, T. (2015). The benefits and limitations of quantitative data collection to the literature review data collection. Kock, N. (2013). Using WarpPLS in E-Collaboration Studies: Descriptive Statistics, Settings.Interdisciplinary Applications of Electronic Collaboration Approaches and Technologies,62. Vogt, A., Barta, J. (2013).The making of tests for index numbers: Mathematical methods of descriptive statistics. Springer Science Business Media. Yu, H. S., Zhang, J. J., Kim, D. H., Chen, K. K., Henderson, C., Min, S. D., Huang, H. (2014). Service quality, perceived value, customer satisfaction, and behavioral intention among fitness center members aged 60 years and over.Social Behavior and Personality: an international journal,42(5), 757-767.