diff --git a/03-measurement.Rmd b/03-measurement.Rmd
index 05738524..5e7ee20b 100644
--- a/03-measurement.Rmd
+++ b/03-measurement.Rmd
@@ -72,7 +72,7 @@ To be useful for research, original data must be mapped to a research design thr
 
 - Detailed DIME Wiki articles explaining the data map components:
   -	**Data linkage table**: https://dimewiki.worldbank.org/Data_Linkage_Table
-  -	**Data flow chart**: https://dimewiki.worldbank.org/Data_Flow_Chart
+  -	**Data flowchart**: https://dimewiki.worldbank.org/Data_Flow_Chart
   -	**Master datasets**: https://dimewiki.worldbank.org/Master_Data_Set
 - **Appendix \@ref(design)** of this book includes intuitive descriptions of common impact evaluation research designs, targeted to research staff without PhD training such as research assistants and field coordinators
 
@@ -141,7 +141,7 @@ you will create and maintain a **master dataset**^[
 listing all observations of that unit relevant to the project.
 Finally, using these two resources
 you will create **data flowcharts**,^[
-  More details on DIME's data flow chart template
+  More details on DIME's data flowchart template
   and an example can be found on the DIME Wiki:
 	https://dimewiki.worldbank.org/Data_Flow_Chart.]
 describing how the original datasets and master datasets
@@ -365,9 +365,9 @@ and multi-level data like "district-school-teacher-student" structures.
 ```{block2, type = "ex"}
 ### Demand for Safe Spaces Example: Creating Data Flowcharts
 
-The data flow chart indicates how the original datasets are processed and combined to create a final respondent-level dataset that will be used for analysis. The analysis dataset resulting from this process is shown in green. The original  datasets are shown in blue (refer to the data linkage table example for details on the original datasets). The name of the uniquely identifying variable in the dataset is indicated in the format (ID: variable_name).
+The data flowchart indicates how the original datasets are processed and combined to create a final respondent-level dataset that will be used for analysis. The analysis dataset resulting from this process is shown in green. The original  datasets are shown in blue (refer to the data linkage table example for details on the original datasets). The name of the uniquely identifying variable in the dataset is indicated in the format (ID: variable_name).
 
-Each operation that changes the level of observation of the data is summarized in the flow chart. The chart also summarizes how datasets will be combined. Since these are the most error-prone data processing tasks, having a high-level plan for how they will be executed helps clarify the process for everyone in the data team, preventing future mistakes.
+Each operation that changes the level of observation of the data is summarized in the flowchart. The chart also summarizes how datasets will be combined. Since these are the most error-prone data processing tasks, having a high-level plan for how they will be executed helps clarify the process for everyone in the data team, preventing future mistakes.
 
 ![](examples/data-flow-chart.png)