Skip to main content
Question Protected by Sycorax
Slight editing; added references and error-propagation tag
Source Link

I have 365 daily measurements that all have standard errors associated with them.

    Date        | Prediction | Standard Error
    -----------------------------------------   
    Jan-01-2003 | 24.8574    | 10.6407
    Jan-02-2003 | 10.8658    | 3.8237
    Jan-03-2003 | 12.1917    | 5.7988
    Jan-04-2003 | 11.1783    | 4.3016
    Jan-05-2003 | 16.713     | 5.3177
    etc ...

What is the statistically appropriate way of getting the yearly average with a 95% Confidence Interval around it ? I am assuming that the errors must be propagating somehow and need to be accounted for.

Google returns mostly information on how to calculate the average or standard deviation of a set of numbers, not a set of numbers with errors.

I would also appreciate some type of internet reference so I can refer to it later.

Thanks !

I have 365 daily measurements that all have standard errors associated with them.

    Date        | Prediction | Standard Error
    -----------------------------------------   
    Jan-01-2003 | 24.8574    | 10.6407
    Jan-02-2003 | 10.8658    | 3.8237
    Jan-03-2003 | 12.1917    | 5.7988
    Jan-04-2003 | 11.1783    | 4.3016
    Jan-05-2003 | 16.713     | 5.3177
    etc ...

What is the statistically appropriate way of getting the yearly average with a 95% Confidence Interval around it ? I am assuming that the errors must be propagating somehow and need to be accounted for.

Google returns mostly information on how to calculate the average or standard deviation of a set of numbers, not a set of numbers with errors.

I would also appreciate some type of internet reference so I can refer to it later.

Thanks !

I have 365 daily measurements that all have standard errors associated with them.

    Date        | Prediction | Standard Error
    -----------------------------------------   
    Jan-01-2003 | 24.8574    | 10.6407
    Jan-02-2003 | 10.8658    | 3.8237
    Jan-03-2003 | 12.1917    | 5.7988
    Jan-04-2003 | 11.1783    | 4.3016
    Jan-05-2003 | 16.713     | 5.3177
    etc ...

What is the statistically appropriate way of getting the yearly average with a 95% Confidence Interval around it ? I am assuming that the errors must be propagating somehow and need to be accounted for.

Google returns mostly information on how to calculate the average or standard deviation of a set of numbers, not a set of numbers with errors.

I would also appreciate some type of internet reference so I can refer to it later.

Post Migrated Here from stackoverflow.com (revisions)
Source Link
user918967
  • 351
  • 1
  • 4
  • 14

Calculate average of a set numbers with reported standard errors

I have 365 daily measurements that all have standard errors associated with them.

    Date        | Prediction | Standard Error
    -----------------------------------------   
    Jan-01-2003 | 24.8574    | 10.6407
    Jan-02-2003 | 10.8658    | 3.8237
    Jan-03-2003 | 12.1917    | 5.7988
    Jan-04-2003 | 11.1783    | 4.3016
    Jan-05-2003 | 16.713     | 5.3177
    etc ...

What is the statistically appropriate way of getting the yearly average with a 95% Confidence Interval around it ? I am assuming that the errors must be propagating somehow and need to be accounted for.

Google returns mostly information on how to calculate the average or standard deviation of a set of numbers, not a set of numbers with errors.

I would also appreciate some type of internet reference so I can refer to it later.

Thanks !