1. ND Data Session NDTAC 2017 National Conference
June 13, 2017

2. Data Workshop
Data Workshop

3. Reflection/closing thoughts
Data Workshop Agenda
Importance of data
Workbook tour
New longitudinal data added
Excel basics
Using the workbook
Pinpoint low pre- and posttesting rates
Analyze performance in high school course credits
Reflection/closing thoughts

4. Importance of Data
Program enrollment and performance data can help to:
Identify struggling and high-performing subgrantees and facilities/programs.
Determine subgrantee and facility/program TA and professional development needs.
Evaluate program processes and effectiveness.
Review subgrantee applications.
Monitor subgrantees.
Promote interagency data sharing and collaboration.

5. Importance of Data (cont.)
Are you currently using some sort of data tool or dashboard to drive your decisionmaking and/or TA efforts?
If so, how? What might you change about your current practices and why?
If not, what key barriers or challenges prevent your use of data to drive program decisionmaking and/or TA activities? How might better data collection or organization inform your work as a coordinator?

6. Data Workshop
Workbook Tour

7. Help the user navigate the workbook
Workbook Tour
Blue Tabs
Help the user navigate the workbook
User’s Guide
Codebook

8. Provide aggregated data
Workbook Tour (cont.)
Green Tabs
Provide aggregated data
Aggregated Subpart 1
Aggregated Subpart 2

9. Provide large datasets of all the raw data
Workbook Tour (cont.)
Red Tabs
Provide large datasets of all the raw data
Can be used in statistical software such as SPSS, Stata, SASS, or R
CSPR Working Data
CSPR by Program Type

10. Yellow Tabs Workbook Tour (cont.)
Contain LEA data by demographics, academic/vocational outcomes, and academic performance (i.e., reading and mathematics data)
Tabs are divided by program type:
At-Risk (AR), Neglect (N), Juvenile Detention (JD), Juvenile Corrections (JC) and Other (OTH)
AR NEG Demographics
JD JC OTH Demographics
AR NEG Ac-Voc Outcomes
JD JC OTH Ac-Voc Outcomes
AR NEG Ac Progress
JD JC OTH Ac Progress

11. Orange Tabs Workbook Tour (cont.)
Contain longitudinal calculations comparing GPRA measures and Leading Indicator measures (SY and SY 13-14).
Tabs are divided by program type:
At-Risk (AR), Neglect (N), Juvenile Detention (JD), Juvenile Corrections (JC) and Other (OTH)
Long Trend – GPRA AR NEG
Long Trend – GPRA JD JC OTH
Long Trend – L.I. AR NEG
Long Trend – L.I. JD JC OTH

12. Data Workshop
Excel Basics

13. Freeze panes Hide rows and columns Sort data Rollover text
Excel Basics
Freeze panes
Hide rows and columns
Sort data
Rollover text

14. Freeze Panes
Freezing panes allows you to always see the rows and columns containing important labels, no matter how far you scroll down or right.
To freeze panes (i.e., lock both rows and columns):
Click the cell below and to the right of the rows and columns that you want to keep visible when you scroll.
On the View tab click the drop-down arrow below Freeze Panes.
Click Freeze Panes.

15. Freeze Panes (cont.) 2 3 1

16. Hide Rows and Columns
Hiding rows or columns help you focus on the data that are most important to you. For example, it may be helpful to hide columns of data for the types of programs you do not fund in your State.
To hide rows and columns:
Highlight a row or column (or a selection of multiple rows or columns).
Right-click on mouse.
Click Hide.

17. Hide Rows and Columns (cont.)
1. Highlight columns
2. Right click on mouse 3

18. Sort Data
Sorting data in Excel allows you to order data using specific indicators. For example, you can easily identify your largest and smallest LEAs or identify which LEAs are performing well and which are performing poorly in critical outcomes.

19. Sort Data: Method 1
Highlight all the data you want to sort (i.e., entire rows and columns of worksheet).
On the Home tab click the drop-down arrow below Sort & Filter.
Click Custom Sort.
Use the drop-down menus to customize your sorting.
Troubleshoot: If your column headers are not showing up in the drop-down menu, make sure you have selected the top row in Step 1 and in Step 4 and then click My data has headers in top right corner.

20. Sort Data: Method 1 (cont.)
1. Highlight all data 2 3

21. Sort Data: Method 1 (cont.)4

22. Sort Data: Method 2
Highlight the row with the variable names (i.e., the first row).
On the Home tab click the drop-down arrow below Sort & Filter.
Click Filter. A drop-down arrow will appear in the bottom right corner of the cell next to each variable name of the first row.
Click on the arrow next to the variable name you want to sort your data by.
Select smallest to largest (or largest to smallest based on preference for sorting).

23. Sort Data: Method 2 (cont.)
1. Highlight first row 2 3

24. Sort Data: Method 2 (cont.)4 5

25. Rollover Text
Rollover text can provide additional information that appears when the mouse hovers over a specific cell. For example, this feature can be used to identify the meaning of the variable names within each tab of the workbook.
How to create rollover text:
Select the cell by clicking on it.
On the Data tab click Validation.
Click the Input Message tab.
Enter your title and message text and click OK.

26. Rollover Text (cont.) 2 1 3 4

27. Rollover Text (cont.) 6

28. Data Workshop
Using the Workbook

29. Explore the data by: Using the Workbook Using conditional formatting
Creating graphs
Building simple formulas

30. Scenario 1: Low Pre- and Posttesting Rates
Data Workshop
Scenario 1: Low Pre- and Posttesting Rates

31. Monitoring: Pre- and Posttesting in Reading
Data Workshop Scenario 1 As you begin monitoring subgrantees based on risk, you decide that low rates of pre- and posttesting in reading is a factor you want to focus on when determining which LEAs with juvenile correction programs to monitor. You need to identify which subgrantees have low rates of reading pre- and posttest data.

32. Monitoring: Pre- and Posttesting in Reading (cont.)
In order to do this, we will:
Save a new version of the workbook.
Hide columns of data you don’t need.
Sort the data based on the percentage of students with reading pre- and posttest data.
Use conditional formatting to identify low rates of testing data.

33. Step 1: Save a New Version of the Workbook
Click File.
Click Save As.
Rename file to include something about “pre-posttest rank.”

34. Step 2: Hide Columns of Data You Don’t Need
For example, if focusing on Juvenile Corrections in the JD JC OTH Ac Progress tab:
Highlight columns B through AC.
Right click on mouse.
Click Hide.
This will hide all data that are not juvenile corrections.

35. Screenshot 1
2. Right click on mouse. 3

36. Step 3: Sort the Data (Using Method 1)
Highlight all the data you want to sort (avoid “Grand Total” row).
On the Home tab click the drop-down arrow below Sort & Filter.
Click Custom Sort.
In drop-down menu, select:
Sort by: PCTJCreadprepostdata.
Sort On: Values.
Order: Smallest to Largest.

37. Step 3: Sort the Data (Using Method 1) (cont.)2 1 3

38. Step 3: Sort the Data (Using Method 1) (cont.)4

39. Step 4: Use Conditional Formatting (Method 1)
Highlight column AE, which is labeled PCTJCreadprepostdata.
On the Home tab click the drop-down arrow below Conditional Formatting.
Select Highlight Cells Rules.
Click Less Than…
Use menu to customize conditional formatting:
Format cells that are LESS THAN: 50%.
With: Light Red Fill with Dark Red Text.

40. Step 4: Use Conditional Formatting (Method 1) (cont.)2 3 4 1

41. Step 5: Use Conditional Formatting (Method 1) (cont.)6

42. What Stories Are the Data Telling?
Reading Pre- and Posttest Data:
Which facilities have less than a 50% test rate (i.e., less than 50% of long-term students have complete reading pre- and posttest data)?
Any facilities with 100% of long-term students with complete pre- and posttest data?
Additional questions for future discovery:
How are the facilities’ testing rates in mathematics?
Are there facilities with higher rates of success (larger portion of students gaining more than one grade level from pre- to posttest)? What are they doing differently?

43. Scenario 2: Performance in High School Course Credits
Data Workshop
Scenario 2: Performance in High School Course Credits

44. Needs Assessment: Earned High School Course Credits
Data Workshop Scenario 2 You are conducting a needs assessment of your Part D programs. You want to compare those facilities/programs with high rates of students earning high school course credits while in the facilities to those with low rates.

45. Needs Assessment: Earned High School Course Credits (cont.)
In order to do this we will:
Copy and paste data into a new workbook.
Graph the data.
Identify National and State averages for comparison purposes.
Format the graph.

46. Step 1: Copy and Paste Data Into a New Workbook
If focusing on Juvenile Corrections in JC OTH Ac-Voc Outcomes tab:
Highlight data in Column A (State Subpart 2 SY2013–14).
Right click on the mouse.
Click Copy.
Open a new (blank) workbook.
Keyboard Shortcuts
Copy: Ctrl+C
New File: Ctrl+N
Paste Values: Ctrl+Alt+V

47. Step 1: Copy and Paste Data Into a New Workbook (cont.)
Select the top left cell in the new workbook.
Right click on the mouse.
Select Paste Values (icon of clipboard with subscript numbers 123).
Repeat Steps 1–7 for Column BJ (PCTJCHSCCinfac1321).
Tip: If the cells with percentages say “#REF!” when you paste the columns, you did not paste the values. Click undo, and this time select Paste Values.

48. Step 1: Copy and Paste Data Into a New Workbook (cont.)
2. Right click on mouse. 1
3 (or use Ctrl+C)

49. Step 1: Copy and Paste Data Into a New Workbook (cont.)
2. Right click on mouse.
3. Select Paste Values (or use Ctrl+Alt+V)
1. Select top left cell.

50. Step 2A: Graph the Data Highlight the data you want to graph.
On the Insert tab click the drop-down arrow beside the Insert Column Chart icon.
Select Clustered Column.

51. Step 2B: Insert Column Chart Icon1

52. 2
Screenshot 3

53. Step 3A: Identify National and State Averages for Comparison Purposes
National Average:
Look up earned high school course credits on the United States Subpart 2 page on NDTAC’s Fast Facts (
State Average:
The State average for percentage of students who earned high school course credits in juvenile corrections is in the Grand Total row.
Note: The data on Fast Facts is across all program types, not just Juvenile Corrections.

54. Step 3B: Identify National Average

55. Step 4: Format the Graph
If you are sharing the graph with others, you may want to do some of the following formatting:
Change the title to include the following:
The indicator highlighted
The Subpart and program type
The school year
Format axis to end at 100%.
Add data labels.
Add the National and State averages to the graph as benchmark lines, for easy visual comparison.
Note: Links to tutorials for how to format Excel graphs are provided in the notes section of this PowerPoint

57. What Stories Are the Data Telling?
Reflection on Earned High School Course Credits:
Are any facilities underperforming?
Are there facilities with a percentage above 100%?
Are there facilities that are performing well (e.g., above 80%)?
Additional questions for future discovery:
Are there trends in the types of facilities/programs and their outcomes?
How are facilities/programs performing in other outcomes?

58. Closing Thoughts
Have you had the opportunity to use the workbooks since the last conference?
What would you like to see added/changed?