1. Statistical Analysis and Unit Improvement Plan Book pgs. 65 - 71
Classroom Curriculum
Continuous Improvement
Data-Based Decision Making
Assessment Analysis
Statistical Analysis and Unit Improvement Plan
Book pgs

2. The Information of Statistics
Classroom Curriculum
Continuous Improvement
Data-Based Decision Making
The Information of Statistics
Statistics
Identify the central tendencies of the class
Identify achievement among different groups of students
Teachers benefit from information about
Classroom Summative Assessments (TT & PA)
Standardized Test Results

3. Toward Continuous Improvement Assessment Analysis
Classroom Curriculum
Continuous Improvement
Data-Based Decision Making
Toward Continuous Improvement Assessment Analysis
Data-based Decision Making (DBDM) LEADING TO Continuous Improvement involves three steps: 1. Calculating the Descriptive Statistics 2. Analyzing Student Achievement from the Statistics 3. Using the analysis to construct an Improvement Plan for Future Instruction and Planning
Making decisions based on student achievement requires three components.

4. Toward Continuous Improvement Assessment Analysis
Classroom Curriculum
Continuous Improvement
Data-Based Decision Making
Toward Continuous Improvement Assessment Analysis
Data-based Decision Making (DBDM) LEADING TO Continuous Improvement involves three steps: 1. Calculating the Descriptive Statistics 2. Analyzing Student Achievement from the Statistics 3. Using the analysis to construct an Improvement Plan for Future Instruction and Planning
Making decisions based on student achievement requires three components. We will talk specifically about the first one now and then will follow up with the other two later.

5. Classroom Curriculum
Continuous Improvement
Data-Based Decision Making
Toward Continuous Improvement 1. Calculating the Descriptive Statistics
Measures of Central Tendency
Mean
Median
Measures of Distribution
Upper Quartile Score
Lower Quartile Score
Note: It is important to report the grading scale and number of students taking the assessment – context matters!

6. Free Excel statistical analysis package available at:
The Benefits of Statistical Analysis 1. Calculating the Descriptive Statistics
Many schools have similar programs which usually have similar statistics. Do not calculate these statistics by hand. Use a pre-made program.
Free Excel statistical analysis package available at:

7. Classroom Curriculum
Continuous Improvement
Data-Based Decision Making
Toward Continuous Improvement 1. Calculating the Descriptive Statistics
Central Tendency - MEAN
Definition: The average value in a data set.
This value gives a general sense for how average students in the class achieved.
Example:
A class’s test scores are:
{70, 71, 73, 75, 79, 80, 82, 84, 87, 89, 90, 92, 94, 95, 96, 99}
Mean = (1356)/(16) = 84.75

8. Classroom Curriculum
Continuous Improvement
Data-Based Decision Making
Toward Continuous Improvement 1. Calculating the Descriptive Statistics
Why might the mean not be the only useful measure of central tendency? Could it ever be misleading? I

9. Classroom Curriculum
Continuous Improvement
Data-Based Decision Making
Toward Continuous Improvement 1. Calculating the Descriptive Statistics
Central Tendency - MEDIAN
Definition: The middle value when all values are arranged in order from least to greatest.
Unlike the mean, the median is not affected by outliers.
Example:
A class’s test scores are:
{70, 71, 73, 75, 79, 80, 82, 84, 87, 89, 90, 92, 94, 95, 96, 99}
The mean of these scores = 84.75; The median = 85.5
Note: If there are an even number of scores, take the mean of the two middle scores.

10. Classroom Curriculum
Continuous Improvement
Data-Based Decision Making
Toward Continuous Improvement 1. Calculating the Descriptive Statistics
UPPER QUARTILE
Definition– The scores that occur in the highest 25% of a data set or class. The score is often reported as the lowest value in the highest 25%.
Example:
A class’s test scores are:
{70, 71, 73, 75, 79, 80, 82, 84, 87, 89, 90, 92, 94, 95, 96, 99}
The upper quartile = (94, 95, 96, 99).
The upper quartile would be indicated by the lowest score in that quartile = 94.
This is helpful to show on the board to show and indicate the top and bottom numbers. I usually use a list of 8 numbers and show the quartiles from there.

11. Continuous Improvement
Data-Based Decision Making
Toward Continuous Improvement 1. Calculating the Descriptive Statistics
LOWER QUARTILE
Definition– The scores that occur in the lowest 25% of a data set or class. The score is often reported as the highest value in the lowest 25%.
Example:
A class’s test scores are:
{70, 71, 73, 75, 79, 80, 82, 84, 87, 89, 90, 92, 94, 95, 96, 99}
The lower quartile = (70, 71, 73, 75).
The lower quartile would be indicated by the highest score in that quartile = 75.
This is helpful to show on the board to show and indicate the top and bottom numbers. I usually use the same 8 numbers as before and help them interpret this.

12. Toward Continuous Improvement Assessment Analysis
Classroom Curriculum
Continuous Improvement
Data-Based Decision Making
Toward Continuous Improvement Assessment Analysis
Data-based Decision Making (DBDM)
LEADING TO Continuous Improvement
involves three steps:
In the Fall we will analyze the Unit 2 that you taught.
In the Spring we will analyze the Unit 5 or 6 that you taught.
For each Unit you will need to bring the student results for the TT and PA, copies of the TT and PA, the Unit Cover page, and copies of the *Statistical Help Guide and *Unit Improvement Plan
*Download from
Making decisions based on student achievement requires three components. We will talk specifically about the first one now and then will follow up with the other two later.

13. Statistics Activity 1. Calculating the Descriptive Statistics
Classroom Curriculum
Continuous Improvement
Data-Based Decision Making
Statistics Activity 1. Calculating the Descriptive Statistics
In small groups, discuss the statistics and focus questions that are in your folder on the handout titled, “Statistics Activity.”
Discussion Questions:
For each assessment:
What do the measures of central tendency (mean/median) say about student achievement?
How are scores distributed among students?
Have I challenged the top performing students?
Are struggling students still able to reach the unit goal?
Looking at both assessments:
Did students improve over the course of the unit?
Did students favor one format over the other?
What general conclusions can I make about the unit results?

14. Toward Continuous Improvement 2. Analyzing Student Achievement
Classroom Curriculum
Continuous Improvement
Data-Based Decision Making
Toward Continuous Improvement 2. Analyzing Student Achievement
Data-based Decision Making (DBDM) LEADING TO Continuous Improvement involves three steps: 1. Calculating the Descriptive Statistics 2. Analyzing Student Achievement from the Statistics 3. Using the analysis to construct an Improvement Plan for Future Instruction and Planning
Making decisions based on student achievement requires three components. We will talk specifically about the first one now and then will follow up with the other two later.

15. Toward Continuous Improvement 2. Analyzing Student Achievement
Classroom Curriculum
Continuous Improvement
Data-Based Decision Making
Toward Continuous Improvement 2. Analyzing Student Achievement
Measures of Central Tendency – Average Students
Mean
Median
Measures of Distribution
Upper Quartile Score - Succeeding Students
Lower Quartile Score - Struggling Students
Grading Scale
We discussed THE MATHEMATICAL MEANING of these statistics prior to the break.
We now discuss what these numbers tell us about student achievement.

16. Toward Continuous Improvement 2. Analyzing Student Achievement
Classroom Curriculum
Continuous Improvement
Data-Based Decision Making
Toward Continuous Improvement 2. Analyzing Student Achievement
If the MEAN and MEDIAN are close, we know the achievement of AVERAGE students on the test.
Central Tendency - MEAN
Definition: The average value in a data set.
Central Tendency - MEDIAN
Definition: The middle value when all values are arranged in order from least to greatest.

17. Toward Continuous Improvement 2. Analyzing Student Achievement
Classroom Curriculum
Continuous Improvement
Data-Based Decision Making
Toward Continuous Improvement 2. Analyzing Student Achievement
From the UPPER QUARTILE
we know the lowest achievement
of SUCCEEDING students on the test.

18. Toward Continuous Improvement 2. Analyzing Student Achievement
Classroom Curriculum
Continuous Improvement
Data-Based Decision Making
Toward Continuous Improvement 2. Analyzing Student Achievement
From the LOWER QUARTILE
we know the highest achievement
of STRUGGLING students on the test.

19. Toward Continuous Improvement 2. Analyzing Student Achievement
Classroom Curriculum
Continuous Improvement
Data-Based Decision Making
Toward Continuous Improvement 2. Analyzing Student Achievement
IN FOLDERS: Handout of HS Chemistry Unit included of these statistics, analysis, and improvement plan.
This is a high school chemistry unit on chemical bonding for which the goal is, “SWBAT demonstrate the composition of compounds symbolically, with Lewis dot structures and with appropriate naming”. Concerned that several students appeared to struggle during the traditional test, the teacher takes action. Knowing that future units depend heavily on these foundational concepts, he scans struggling students’ tests to find if any failed, and notes the reasons why. He reviews and ensures that the first question of each E&R tiered assignment and lesson plan assessment addresses the unit goal at an unsophisticated level. Doing so for both E&R lesson plans provides failing students with 2 additional opportunities to engage with and demonstrate unit goal competency. He also scans succeeding students’ tests to see on which questions they struggled and adjusts the challenging questions of the assignments and assessments. Having addressed these immediate concerns, he will grade the tests over the next several days.
This is a new set of statistics. The teacher analyzed these and now is doing the second step – reflecting on both the statistics and his own practice. Which statistics would raise questions.
What trends do you notice about student achievement?

20. Toward Continuous Improvement 3. Improvement Plan
Classroom Curriculum
Continuous Improvement
Data-Based Decision Making
Toward Continuous Improvement 3. Improvement Plan

21. Toward Continuous Improvement 3. Improvement Plan
Classroom Curriculum
Continuous Improvement
Data-Based Decision Making
Toward Continuous Improvement 3. Improvement Plan
Students may have done well or poorly on the TT, but that tells us little about the effectiveness of the TT. Careful analysis of the data may lead to many students passing a poorly constructed TT or to few students passing a well-constructed TT. Further analysis is needed to identify possible problems.

22. Toward Continuous Improvement 3. Improvement Plan
Classroom Curriculum
Continuous Improvement
Data-Based Decision Making
Toward Continuous Improvement 3. Improvement Plan
Analysis of TT data may lead to the conclusion that instructional planning or instructional activities were weak.

23. Toward Continuous Improvement 3. Improvement Plan
Classroom Curriculum
Continuous Improvement
Data-Based Decision Making
Toward Continuous Improvement 3. Improvement Plan
Analysis of TT data may also lead to the conclusion that The Unit Cover page was poorly planned or constructed.

24. Toward Continuous Improvement 3. Improvement Plan
Classroom Curriculum
Continuous Improvement
Data-Based Decision Making
Toward Continuous Improvement 3. Improvement Plan
Data-based Decision Making (DBDM) LEADING TO Continuous Improvement involves three steps: 1. Calculating the Descriptive Statistics 2. Analyzing Student Achievement from the Statistics 3. Using analysis to construct an Improvement Plan for Future Instruction and Planning
Using analysis to construct an Improvement Plan for Future Instruction and Planning is the focus of the Year 2 Fall Visit. During that visit, each teacher will engage in the process of creating an Improvement Plan based on the statistics and analysis of student achievement.

25. Toward Continuous Improvement 3. Constructing an Improvement Plan
Classroom Curriculum
Continuous Improvement
Data-Based Decision Making
Toward Continuous Improvement 3. Constructing an Improvement Plan

26. Toward Continuous Improvement 3. Improvement Plan
Data-Based Decision Making
Toward Continuous Improvement 3. Improvement Plan
In the Fall, you will construct a Unit Improvement Plan For Diocesan Unit 2. Please bring the following Unit 2 artifacts: Unit Cover Page Traditional Test and Performance Assessment Prompt *Statistics for TT and PA student results *Statistical Analysis Help Guide and Improvement Plan Guide *Improvement Plan Template *Can be downloaded from Statistical Analysis Program.zip