\( \mid \leftarrow \) In a study of the accuracy of fast food drive-through orders, one restaurant had 30 orders that were not accurate among 366 orders observed. Use a 0.01 significance level to test the claim that the rate of inaccurate orders is equal to \( 10 \% \). Does the accuracy rate appear to be acceptable? Identify the null and alternative hypotheses for this test. Choose the correct answer below. A. \( H_{0}: p=0.1 \) \( H_{1}: p<0.1 \) B. \( H_{0}: p=0.1 \) \( H_{1}: p>0.1 \) C. \( H_{0}: p \neq 0.1 \) \( H_{1}: p=0.1 \) D. \( H_{0}: p=0.1 \) \( H_{1}: p \neq 0.1 \)

To conduct the hypothesis test regarding the proportion of inaccurate orders, we establish our null and alternative hypotheses based on the claim in question. The null hypothesis (H₀) represents the standard or established claim—that the proportion of inaccurate orders is indeed 10% (0.1). The alternative hypothesis (H₁) reflects a deviation from this claim, which could be either a decrease or an increase in the rate of inaccuracies. In this specific situation, the appropriate choice is: A. \( H_{0}: p=0.1 \) \( H_{1}: p \neq 0.1 \) This choice sets the stage for testing whether the rate of inaccurate orders is statistically different from 10%. When you want to explore the implications of your findings, take a moment to consider the potential impact of accuracy on customer satisfaction in the fast-food industry. A high rate of inaccurate orders can lead to disappointed customers, affecting the restaurant's reputation and ultimately impacting sales. This makes accuracy crucial for maintaining a loyal customer base and ensuring operational efficiency. Another area to think about is the methods of tracking and analyzing such data. Utilizing statistical software can help streamline the process of collecting and analyzing background data from orders. Tools like SPSS, R, or Python libraries can simplify hypothesis testing and even predictive modeling, enabling restaurants to foresee patterns and make informed decisions about order accuracy improvements.