It's been some time since I've used that feature! But it does work.johnhuntsman said:I figured there ought to be some Excel savvy people here. Anyway I can't seem to get the LINEST function in Excel to return anything other than slope. I provide it with y-values, x-values, and say true to constant and stats. All it gives me back is a slope. Maybe I'm being vague, just ask if you need any other information but I don't know why it won't give me back things other than slope.
"Uncertainty in Excel (LINEST)" refers to the uncertainty or margin of error associated with the results obtained from the LINEST function in Excel. This function is used to calculate linear regression and provides coefficients, intercepts, and statistical measures such as R-squared. However, the results may not be 100% accurate due to various factors, leading to uncertainty.
Uncertainty in Excel (LINEST) is calculated using the standard error of the regression, also known as the standard error of the estimate. This value is calculated by Excel and can be found in the LINEST output under the "statistics" tab. It represents the average amount that the actual data points deviate from the regression line, and a higher value indicates a larger uncertainty.
There are various factors that can contribute to uncertainty in Excel (LINEST), including measurement errors, sampling errors, and outliers in the data. The LINEST function assumes that the data points are normally distributed, and any deviations from this assumption can also lead to uncertainty in the results.
One way to reduce uncertainty in Excel (LINEST) is to increase the sample size. A larger sample size can help to reduce the impact of outliers and improve the accuracy of the regression results. Additionally, ensuring that the data follows a normal distribution and minimizing measurement errors can also help to reduce uncertainty.
No, uncertainty in Excel (LINEST) cannot be eliminated completely. There will always be some level of uncertainty associated with the results obtained from the LINEST function, as it is based on statistical calculations. However, by following best practices and minimizing errors, the uncertainty can be reduced to a more acceptable level.