Want this question answered?
Assuming that other measures remain the same, as the sample estimate increases both ends of the confidence interval will increase. In effect, the confidence interval will be translated to a higher value without any change in its size.Assuming that other measures remain the same, as the sample estimate increases both ends of the confidence interval will increase. In effect, the confidence interval will be translated to a higher value without any change in its size.Assuming that other measures remain the same, as the sample estimate increases both ends of the confidence interval will increase. In effect, the confidence interval will be translated to a higher value without any change in its size.Assuming that other measures remain the same, as the sample estimate increases both ends of the confidence interval will increase. In effect, the confidence interval will be translated to a higher value without any change in its size.
Statistical estimates cannot be exact: there is a degree of uncertainty associated with any statistical estimate. A confidence interval is a range such that the estimated value belongs to the confidence interval with the stated probability.
It means that 95% of the values in the data set falls within 2 standard deviations of the mean value.
Why confidence interval is useful
What percentage of times will the mean (population proportion) not be found within the confidence interval?
Point Estimate of the Mean: The point estimate of the mean is 16, since this is the sample mean. 95% Confidence Interval Estimate for the Mean: The 95% confidence interval estimate for the mean can be calculated using the following formula: Mean +/- Margin of Error = (16 +/- 1.96*(9/sqrt(50))) = 16 +/- 1.51 = 14.49 to 17.51 99% Confidence Interval Estimate for the Mean: The 99% confidence interval estimate for the mean can be calculated using the following formula: Mean +/- Margin of Error = (16 +/- 2.58*(9/sqrt(50))) = 16 +/- 2.13 = 13.87 to 18.13
An open interval centered about the point estimate, .
confidence level
The confidence interval is not directly related to the mean.
Assuming that other measures remain the same, as the sample estimate increases both ends of the confidence interval will increase. In effect, the confidence interval will be translated to a higher value without any change in its size.Assuming that other measures remain the same, as the sample estimate increases both ends of the confidence interval will increase. In effect, the confidence interval will be translated to a higher value without any change in its size.Assuming that other measures remain the same, as the sample estimate increases both ends of the confidence interval will increase. In effect, the confidence interval will be translated to a higher value without any change in its size.Assuming that other measures remain the same, as the sample estimate increases both ends of the confidence interval will increase. In effect, the confidence interval will be translated to a higher value without any change in its size.
A confidence interval of x% is an interval such that there is an x% probability that the true population mean lies within the interval.
No, it is not. A 99% confidence interval would be wider. Best regards, NS
Statistical estimates cannot be exact: there is a degree of uncertainty associated with any statistical estimate. A confidence interval is a range such that the estimated value belongs to the confidence interval with the stated probability.
It means that 95% of the values in the data set falls within 2 standard deviations of the mean value.
Why confidence interval is useful
What percentage of times will the mean (population proportion) not be found within the confidence interval?
That is with a confidence interval of approximately 95% the "true mean" is within the interval of [336.10, 353.90] and that the sample mean (which is an estimate of the "true mean") is $350.00. SMALL-SAMPLE CONFIDENCE INTERVAL FOR A POPLATION MEAN, t-DISTRIBUTION 95% Confidence Interval = x-bar +/- (t-critical value) * s/SQRT(n) x-bar = SAMPLE MEAN [350] s = STANDARD DEVIATION [100] n = NUMBER OF SAMPLES [200] n - 1 = 199 df (DEGREES OF FREEDOM) t-critical value = (approx) 1.972 from "look-up Table for "two-sided interval" df = 200 [CLOSED df IN TABLE] 95% Confidence Interval: 350+/- 1.972 *100 / SQRT(200) = [336.10, 353.90] That is with a confidence interval of approximately 95% the "true mean" is within the interval of [336.10, 353.90] and that the sample mean (which is an estimate of the "true mean") is $350.00. c. ANSWER: A random selection of 1537 customers will provide 95% confidence for estimating the mean extended warranty price paid. Why??? CHOOSING THE SAMPLE SIZE n = [(z-critical value * s)/B]^2 z-critical value = 1.96 (associated with 95% confidence level) s = STANDARD DEVIATION [100.00] B = BOUND ON THE ERROR OF ESTIMATION [5.00] n = [(1.96 * 100.00)/5.00]^2 = 1537 (ROUNDED - UP) CONCLUSION: A random selection of 1537 customers will provide 95% confidence for estimating the mean extended warranty price paid.