Linear regression: Difference between revisions
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1. ''Statistics - financial statistics.'' | |||
A statistical technique which aims to establish whether a linear relationship exists between one quantity and another. | A statistical technique which aims to establish whether a linear relationship exists between one quantity and another. | ||
2. ''Forecasting - cash flow forecasting.'' | |||
Applying such a linear relationship for forecasting. | |||
:<span style="color:#4B0082">'''''Data quality is paramount'''''</span> | |||
:"While [cash flow forecast] automation is important, data quality is also paramount to success. | |||
:When building the forecast, each line item may be sourced in different ways... | |||
:For example, many treasury teams prefer to import accounts payable data directly from the enterprise resource planning system, while for receivables information they may wish to extrapolate historical data and model using a linear regression." | |||
:''The Treasurer magazine, August 2019, p25 - Bob Stark, Vice president Strategy at Kyriba.'' | |||
== See also == | == See also == | ||
* [[Cash flow forecast]] | |||
* [[Cash management]] | |||
* [[Correlation]] | * [[Correlation]] | ||
* [[Enterprise resource planning]] | |||
* [[Extrapolation]] | |||
* [[Forecast]] | |||
* [[Linear]] | * [[Linear]] | ||
* [[Model]] | |||
* [[Payables]] | |||
* [[Receivables]] | |||
* [[Regression analysis]] | * [[Regression analysis]] | ||
* [[Statistics]] | |||
* [[Vice president]] (VP) | |||
[[Category:Identify_and_assess_risks]] | |||
[[Category:Manage_risks]] | |||
[[Category:Risk_reporting]] | |||
[[Category:Risk_frameworks]] | |||
[[Category:The_business_context]] | |||
Latest revision as of 21:03, 4 December 2023
1. Statistics - financial statistics.
A statistical technique which aims to establish whether a linear relationship exists between one quantity and another.
2. Forecasting - cash flow forecasting.
Applying such a linear relationship for forecasting.
- Data quality is paramount
- "While [cash flow forecast] automation is important, data quality is also paramount to success.
- When building the forecast, each line item may be sourced in different ways...
- For example, many treasury teams prefer to import accounts payable data directly from the enterprise resource planning system, while for receivables information they may wish to extrapolate historical data and model using a linear regression."
- The Treasurer magazine, August 2019, p25 - Bob Stark, Vice president Strategy at Kyriba.
