Answer: It seems like there might be some typos or missing information in your question. Let's break down what you've mentioned and try to make sense of it.
You have a local retailer claiming that the mean waiting time is 10 minutes. You've taken a random sample of waiting times, and you have some calculated values. It's implied that the waiting times are normally distributed.
- Let's decode the provided values:
"A random sample of so waiting times as a mean of 10": It seems like you've taken a random sample of waiting times and calculated their mean, which is 10.
"Use the value method, Exact value of the standard devi notrown": I'm not entirely sure what you mean by "the value method" and "Exact value of the standard devi notrown." It seems like you might be trying to perform a hypothesis test using the sample mean and standard deviation.
"O P-0.053 Support claim": It's unclear what "O P-0.053" represents. If this is a p-value, it could be associated with a statistical test to either support or reject the retailer's claim.
"O P=0,097 Support claim": Similarly, this seems to be another p-value with a different value.
"O P 0.003 Reject claim": This also appears to be a p-value, but with a value that might lead to rejecting the retailer's claim.
"O P-0.007 Reject claim": Another p-value that might lead to rejecting the claim.
- Based on the general principles of hypothesis testing:
If the p-value is small (typically below a significance level like 0.05), you might reject the null hypothesis (in this case, the retailer's claim).
If the p-value is not small, you might fail to reject the null hypothesis and not have sufficient evidence to dispute the claim.
However, without a clear understanding of what "O P" represents and the context of the calculations, I cannot definitively guide you on which claim to support or reject. If you can provide clearer information or context about the calculations and values, I'd be happy to assist further.