Corrected link to simple linear regression sample

Author: erwin-cabral-ge

README.md

@@ -11,7 +11,7 @@ These are sample analytics written for use with Predix Analytics:
 - **[demo-timeseries-adder-with-model](analytics/demo-timeseries-adder-with-model):** Takes 2 arrays of timeseries data and returns a timeseries array that contains the sums at each timestamp, adjusted by a threshold value provided in a trained model. Currently available in Java and Python.
 - **[demo-RTM-loco](analytics/demo-RTM-loco):** A reference analytic that is used to calculate locomotive efficiency using a linear regression model. It has been implemented in Java, Matlab (r2011b), and Python.
 - **[miners-rule](analytics/miners-rule):** A sample analytic that performs a Miner's Rule operation on 2 timeseries arrays and returns a timeseries array. Currently only available in Java.
-- **[sample-linear-regression](analytics/sample-linear-regression):**:new:  A sample analytic that performs a simple linear regression with two arrays as input and returns the p-value, r-value, slope, intercept and standard error. Currently only available in Python 3. 
+- **[simple-linear-regression](analytics/simple-linear-regression):**:new:  A sample analytic that performs a simple linear regression with two arrays as input and returns the p-value, r-value, slope, intercept and standard error. Currently only available in Python 3. 
 
 For more information on developing analytics for use with Predix Analytics, see [Analytic Development](https://docs.predix.io/en-US/content/service/analytics_services/analytics_framework/analytic-development) on Predix IO. 
 

analytics/README.md

@@ -7,6 +7,6 @@ These are sample analytics written for use with [Predix Analytics](https://docs.
 - **[demo-timeseries-adder-with-model](demo-timeseries-adder-with-model):** Takes 2 arrays of timeseries data and returns a timeseries array that contains the sums at each timestamp, adjusted by a threshold value provided in a trained model. Currently available in Java and Python.
 - **[demo-RTM-loco](demo-RTM-loco):** A reference analytic that is used to calculate locomotive efficiency using a linear regression model. It has been implemented in Java, Matlab (r2011b), and Python.
 - **[miners-rule](miners-rule):** A sample analytic that performs a Miner's Rule operation on 2 timeseries arrays and returns a timeseries array. Currently only available in Java.
-- **[sample-linear-regression](sample-linear-regression):**:new: A sample analytic that performs a simple linear regression with two arrays as input and returns the p-value, r-value, slope, intercept and standard error. Currently only available in Python 3.
+- **[simple-linear-regression](simple-linear-regression):**:new: A sample analytic that performs a simple linear regression with two arrays as input and returns the p-value, r-value, slope, intercept and standard error. Currently only available in Python 3.
 
 For more information on developing analytics for use with Predix Analytics, see [Analytic Development](https://docs.predix.io/en-US/content/service/analytics_services/analytics_framework/analytic-development) on Predix IO.