# Usability of Certain Symbols Indicating Automobile Safety Status Based on Youth Assessment
## 4 Discussion  
It is important to underscore the selection process of \(p_{0}\) values during the examination of statistical hypotheses through Z-tests for one population proportion. As mentioned earlier, for this purpose, the inferential statistics technique was used. Inferential statistics is a type of statistical analysis that is used to make predictions or inferences about a population based on a sample. It involves using data from a sample to draw conclusions about the population as a whole. This technique is used to make decisions and predictions about a population based on a smaller sample size. This means that the stated values for the proportion \(p_{0}\) (0.82, 0.75, 0.78, 0.57, 0.09, 0.55, 0.65, 0.9, 0.88, 0.43, 0.49, 0.17, 0.71, 0.68, 0.8, and 0.61) were obtained for each symbol individually based on the calculation. To achieve this, the Z-test for one population proportion was applied iteratively until a p\({}_{0}\) limitvalue was reached for each symbol, where the set null hypothesis could not be rejected. In other words, it means that in the population, the percentage of correct understanding for the symbol \"Airbag\" cannot be expected to be higher than 82%, as well as that the percentage of correct understanding in the population for the symbol \"Engine stop\" cannot be expected to be greater than 75%, etc. It should be mentioned that in all computations pertaining to the Z-test application for a single population proportion, the conditions for sample size have been met, with np > 5 and n (1 - p) \(\geq\) 5 (n \(\geq\) 30). This indicates that the population-level predictions can be deemed statistically valid. In connection with the foregoing, based on the conducted analysis of all tested symbols, it can be deduced that there is not enough evidence to conclude that the percent of the youth population \(p\) who can, at a significance level of 5%, correctly recognize the following symbols is greater than:  
- 82% for the Airbag symbol;  
- 75% for the Engine stop symbol;  
- 78% for the Check gauges symbol;  
- 57% for the Immobilizer system symbol;  
- 9% for the Auto door lock malfunction symbol;  
- 55% for the Transmission failure symbol;  
- 65% for the Transmission oil temperature symbol;  
- 90% for the Steering failure symbol;  
- 88% for the Loose wheel warning symbol;  
- 43% for the Electric park brake trouble symbol;  
- 49% for the Brake fluid level symbol;  
- 17% for the Antilock braking system trouble symbol;  
- 71% for the Lambda sensor warning symbol;  
- 68% for the Message symbol;  
- 80% for the Engine coolant level symbol;  
- 61% for the Electronic throttle control symbol. This kind of analysis can be found in recent analyses of car dashboard symbols [16; 19; 20], but it was not previously performed in other research on symbols. However, much research on car dashboard symbols does not include the application of statistical tests for making conclusions. For example, Ref. [2] does not explicitly mention any hypothesis testing that was conducted by using statistical tests. The results were analyzed by the application of descriptive statistics. Similarly, Ref. [6] also does not mention any statistical tests being used to check hypotheses about symbols used in cars. Instead, the study used a qualitative approach to investigate the effectiveness of using icons to convey information about automation systems to users. The research in [14] also does not mention the use of any specific statistical tests to analyze the results regarding the testing of car display panel symbols. A primary focus of the study was to assess comprehension via direct interpretation of the responses given by the participants. Correct responses were quantified and percentages were associated with each icon to determine the level of comprehension. There is also research on car dashboard symbols that use certain statistical tests in order to analyze the data. A statistical test was used in [17], in order to analyze the influence of demographic variables on the understandability and recognizability of each symbol.