Final answer:
The statement provided in the question is presented as data and does not constitute a claim that can be labeled true or false. It indicates a sample mean and standard deviation for a study on mobile device repair costs. Hypothesis testing could be applied to this data for various statistical analyses, such as comparing repair costs or assessing price variability.
Step-by-step explanation:
The statement in the question, "In a random sample of 12 mobile devices, the mean repair cost was $90.42, and the standard deviation was $33.61," does not assert a claim that requires validation and is presented as factual information. Therefore, it cannot be directly classified as either true or false without additional context. In statistical analysis, a sample mean and standard deviation are used to estimate the population parameters and to perform hypothesis tests or construct confidence intervals. To assess the variability in consumer electronics repair costs or to compare different populations (e.g., repair costs across different brands), hypothesis testing could be performed using this sample data.
For example, to analyze whether the standard deviation of the repair costs is greater than a specified value, a chi-squared test for variance could be used. To compare the mean repair costs from different samples, a t-test or ANOVA could be employed, depending on the number of samples and the study design.
Examples of such analyses could include:
- Testing the claim that the standard deviation of calculator prices among various stores is greater than $15.
- Interpreting where a car model stands in terms of repair costs compared to others based on percentile rank.
- Examining the claim of a sales representative about the narrow standard deviation of a computer's price.