quotes to ticks for spell check

anvilPoll2024MainAnalysis.Rmd

@@ -236,7 +236,7 @@ Overall, there is less comfort with containers or workflows than using various p
 
 <details><summary>Description of variable definitions and steps for preparing the data </summary>
 
-We bind the rows of two dataframes, one for returning users and one for potential users. The steps for building the dataframes are essentially the same once the first `filter` and `mutate` steps are completed. The first step of building each data frame is to filter based on the `UserType` of interest. We then select the columns that start with "Score_" or "Score_AllTech" that we created in `TidyData.Rmd`. For potential users, we only need the "Score_AllTech" columns, not the "Score_ReturningAnVILTech" columns as well. Because the scores are integers and we want to sum the scores across responses, we use a column sum function and send those sums to a data frame where the rowname is the previous column name and the summed scores are stored in the `totalScore` column. We add columns `nscores`, `avgScore`, and `UserType` that store the number of responses or scores, the average score (total divided by number of), and the applicable type of user. Rownames are then moved to a column called `WhereTool` and this column is separated into two separate columns, separating on the word "Tech" Such that the new `AnVILorNo` column will contain either "Score_All" or "Score_ReturningAnVIL". We translate those to be "Separate from the AnVIL" or "On the AnVIL" respectively. And the new "Tool" column will contain the shorthand tool names which we recode to add spaces or more info.   
+We bind the rows of two dataframes, one for returning users and one for potential users. The steps for building the dataframes are essentially the same once the first `filter` and `mutate` steps are completed. The first step of building each data frame is to filter based on the `UserType` of interest. We then select the columns that start with `Score_` or `Score_AllTech` that we created in `TidyData.Rmd`. For potential users, we only need the `Score_AllTech` columns, not the `Score_ReturningAnVILTech` columns as well. Because the scores are integers and we want to sum the scores across responses, we use a column sum function and send those sums to a data frame where the rowname is the previous column name and the summed scores are stored in the `totalScore` column. We add columns `nscores`, `avgScore`, and `UserType` that store the number of responses or scores, the average score (total divided by number of), and the applicable type of user. Rownames are then moved to a column called `WhereTool` and this column is separated into two separate columns, separating on the word "Tech" Such that the new `AnVILorNo` column will contain either `Score_All` or `Score_ReturningAnVIL`. We translate those to be "Separate from the AnVIL" or "On the AnVIL" respectively. And the new `Tool` column will contain the shorthand tool names which we recode to add spaces or more info.   
 
 </details>