Due to financial hardship, the Nyke Shoe Company feels they only need to make one size of shoes, regardless of gender or height. Because they want to reduce production cost to get survive from the financial crises. This analysis of shoe size would help them to resolving the problem
Nyke Shoe Company are undergoing financial difficulties and are looking into making a single size of shoe regardless of gender or height. This decision is intended to reduce the costs associated with production when manufacturing different sizes of shoes. If the company is able to find a single size that works for a larger group, then this can help them recover from their financial crises and they can minimize the costs associated with production without a loss in sales as well as profits increasing. This solution will help in the overall financial problem being eliminated. There is need for statistical analysis to be done on the data to determine the shoe size they can focus on to help in solving their current problem.
The dataset given from the company has 3 variables and 35 data points for carrying out the analysis. The variables are the ‘Shoe Size’, ‘Height’ and ‘Gender’ of the customers. The dependent variables in this case is the shoe size while the independent variables are the gender and height. The target of the statistical processes is to discover the shoe size which meets the interests of the company and then get solution from the analysis.
Analyze the Data and Interpret the Results
First, from the dataset, I find the mean, mode and median for the different variables. The variability of the values gives insights that it is more present in the ‘Shoe Size’ variable as compared to the ‘Height’ variable.
The mean, mode and median for the ‘Shoe Size’ are 9.1429, 7 and 9.
The mean, mode and median for the ‘Height’ are 68.9429, 70 and 70.
From the analysis, we can see the size 7 that is repeated more often than any other size of shoes, it means more people would choose shoes for size 7. Thus, it indicates the size 7 maybe the best size for Nyke Shoe Company to make more profits and reduce cost of production. Then, the data shows that there are 18 females which is 51.43% of shoes production and 48.57% for males. In order to better interpret and understand the data, there is need for the analysis on the scatter plot of Height and Shoe Size, and the scatter plot for the Gender and Shoe Size. The ‘Shoe Size’ was used as the dependent variable. The graph shows that the shoe size is variant across genders and heights. The graphs show the variations in height and sex of the customers and conclusions are that generally, people who are larger need a larger shoe size and also that males are in need of larger shoe sizes. From these statistics, there are relationships exist between the independent variables.
The regression analysis may interpret the relationships such as the shoe size being affected by variables of gender and height. A standardized shoe size which would fit all is impossible. However, the company seeking a way to reduce cost since they cannot be able to satisfy for production costs of all sizes, therefore, there is need for them to find a central point to work on for maximum sales and profits. The best solution would be applying a point estimate alongside a confidence interval. The confidence interval is 95%. The confidence interval is (8.256, 10.030). This value, however, fails in giving proper results since the size 7 is excluded in this interval, size 7 should be the usable size for the best outcome.
The initial outcome shows that both gender and height impact the size of the shoe significantly, therefore, there is no standard single shoe size which can be accepted by all genders and heights. However, the best recommendation after the analysis is size 7 since this offers maximum efficiency in comparison to any other size for all participants. Therefore, size 7 shoes are recommended for production.