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You should make sure that your test has enough power to detect a difference that is practically significant. You do not have enough evidence to conclude that the difference between the population mean and the hypothesized mean is statistically significant. P-value > α: The difference between the means is not statistically significant (Fail to reject H 0) If the p-value is greater than the significance level, the decision is to fail to reject the null hypothesis. For more information, go to Statistical and practical significance. Use your specialized knowledge to determine whether the difference is practically significant. The red reference lines represent the interval, so we can be 95 confident the population mean of Barkley’s yards per carry is between approximately 3.4 and 7.8. You can conclude that the difference between the population mean and the hypothesized mean is statistically significant. The middle 95 of values from the bootstrapping distribution provide a 95 confidence interval for the population mean. P-value ≤ α: The difference between the means is statistically significant (Reject H 0) If the p-value is less than or equal to the significance level, the decision is to reject the null hypothesis. A significance level of 0.05 indicates a 5% risk of concluding that a difference exists when there is no actual difference. Usually, a significance level (denoted as α or alpha) of 0.05 works well. To determine whether the difference between the population mean and the hypothesized mean is statistically significant, compare the p-value to the significance level. For more information, go to Ways to get a more precise confidence interval. If the interval is too wide to be useful, consider increasing your sample size. Use your specialized knowledge to determine whether the confidence interval includes values that have practical significance for your situation. The confidence interval helps you assess the practical significance of your results. For example, a 95% confidence level indicates that if you take 100 random samples from the population, you could expect approximately 95 of the samples to produce intervals that contain the population mean. The confidence interval provides a range of likely values for the population mean. Find a 90 confidence interval for the population mean of all IQ scores (which we already. To better estimate the population mean, use the confidence interval. Minitab computes confidence intervals based on the sample data. Because the mean is based on sample data and not on the entire population, it is unlikely that the sample mean equals the population mean. The mean of the sample data is an estimate of the population mean. First, consider the sample mean, and then examine the confidence interval.