diff --git a/docs/en/ml/images/ml-population-anomaly.jpg b/docs/en/ml/images/ml-population-anomaly.jpg
index cde94e8c8d5..9fa726d050c 100644
Binary files a/docs/en/ml/images/ml-population-anomaly.jpg and b/docs/en/ml/images/ml-population-anomaly.jpg differ
diff --git a/docs/en/ml/images/ml-population-job.jpg b/docs/en/ml/images/ml-population-job.jpg
index b4b0766eb79..a51fa9c9c37 100644
Binary files a/docs/en/ml/images/ml-population-job.jpg and b/docs/en/ml/images/ml-population-job.jpg differ
diff --git a/docs/en/ml/images/ml-population-results.jpg b/docs/en/ml/images/ml-population-results.jpg
index 5023b0df819..ae4eb7609f5 100644
Binary files a/docs/en/ml/images/ml-population-results.jpg and b/docs/en/ml/images/ml-population-results.jpg differ
diff --git a/docs/en/ml/populations.asciidoc b/docs/en/ml/populations.asciidoc
index 1bea1a000ab..53e10ce8d41 100644
--- a/docs/en/ml/populations.asciidoc
+++ b/docs/en/ml/populations.asciidoc
@@ -58,15 +58,16 @@ PUT _xpack/ml/anomaly_detectors/population
 //include only workstations as servers and printers would behave differently
 //from the population
 
-If your data is stored in {es}, you can create an advanced job with these same
-properties. In particular, you specify the `over_field_name` property when you
-add detectors:
+If your data is stored in {es}, you can use the population job wizard in {kib}
+to create a job with these same properties. For example, the population job
+wizard provides the following job settings:
 
 [role="screenshot"]
-image::images/ml-population-job.jpg["Create a detector for population analysis]
+image::images/ml-population-job.jpg["Job settings in the population job wizard]
 
 After you open the job and start the {dfeed} or supply data to the job, you can
-view the results in {kib}. For example:
+view the results in {kib}. For example, you can view the results in the
+**Anomaly Explorer**:
 
 [role="screenshot"]
 image::images/ml-population-results.jpg["Population analysis results in the Anomaly Explorer"]
@@ -76,7 +77,7 @@ data points for the selected time period. Population analysis is particularly
 useful when you have many entities and the data for specific entitles is sporadic
 or sparse.
 
-If you click on a section in the time line or swim lanes, you can see more
+If you click on a section in the timeline or swimlanes, you can see more
 details about the anomalies:
 
 [role="screenshot"]