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CHAPTER 5
UTILIZATION OF ASSESSMENTDATA
CHRISTINE P. MEJINO
BSEd III-A English
STATISTICS
• It is an important tool in the utilization of the assessment data most
especially in describing, analyzing, and interpreting the performance of the
students in the assessment procedures.
DEFINITION OF STATISTICS
• Is a branch of science, which deals with the collection,
presentation, analysis, and interpretation of quantitative data.
Collection Presentation Analysis Interpreta-tion
STATISTICAL QUESTION
• A question where you expect to get a variety of
answers, and you are interested in the distribution and
tendency of those answers.
• Is a method concerned with collecting, describing and
analyzing a set of data without drawing conclusions (or
inferences) about a large group.
DESCRIPTIVE STATISTICS
• Is a branch of statistics, concerned with the analysis of
a subset of data leading to predictions or inferences
about the entire set of data.
INFERENTIAL STATISTICS
• Is a tabular arrangement of data into appropriate
categories showing the number of observations in each
category or group.
FREQUENCY DISTRIBUTION
A. It encompasses the size of the table.
B. It makes the data more interpretative.
ADVANTAGES OF FREQUENCY
DISTRIBUTION
1. Class limit is the groupings or categories defined by the lower
or upper limits.
PARTS OF FREQUENCY TABLE
Example
Lower limits
(LL)
Upper limits
(UL)
10 14
15 19
20 24
• Lower class limit (LL) represents the smallest number in each group.
• Upper class limit (UP) represents the highest number in each group.
2. Class Size (c.i) is the width of each class interval.
Example
Lower limits
(LL)
Upper limits
(UL)
10 14
15 19
20 24
The class size in this score distribution is 5.
11-12-13
16-17-18
21-22-23
3. Class Boundaries are the numbers used to separate each category in
the frequency distribution but without gaps created by the class limits.
The scores of the students are discrete. Add 0.5 to the upper limit to get
the upper class boundary and subtract 0.5 to the lower limit to get the
lower class boundary in each group or category.
Lower limits
(LL)
Upper limits
(UL)
10 14
15 19
20 24
LCB UCB
9.5 14.5
14.5 19.5
19.5 24.5
4. Class Marks are the midpoint of the lower and upper class limits.
The formula is 𝑋 𝑚 =
𝐿𝐿+𝑈𝐿
2
Lower limits
(LL)
Upper limits
(UL) 𝑋 𝑚
10 14 12
15 19 17
20 24 22
1. Compute the value of range (R).
RANGE is the difference between the highest score and the lowest score.
Determine the class size (c.i). The class size is the quotient when your divide the
range by the desired number of classes or categories. The desired numbers of classes are
usually 5, 10 or 15 and they depend on the number of scores in the distribution. If the desired
number of classes is not identified, find the value of k, where k= 1+3.3 log n.
STEPS IN CONSTRUCTING FREQUENCY
DISTRIBUTION
R= HS-LS
𝑐. 𝑖 =
𝑅
𝑑𝑒𝑠𝑖𝑟𝑒𝑑 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑐𝑙𝑎𝑠𝑠𝑒𝑠
𝑜𝑟 𝑐. 𝑖 =
𝑅
𝑘
(5, 10, 15)
R=HS-LS
k=1+3.3 log n
2. Set up the class limits of each class or category. Each class defined by the
lower limit and upper limit. Use the lowest score as the lower limit of the
first class.
3. Set up the class boundaries if needed. Use the formula:
𝑐𝑏 =
𝐿𝐿 𝑜𝑓 𝑡ℎ𝑒 𝑠𝑒𝑐𝑜𝑛𝑑 𝑐𝑙𝑎𝑠𝑠 − 𝑈𝐿 𝑜𝑓 𝑡ℎ𝑒𝑓𝑖𝑟𝑠𝑡 𝑐𝑙𝑎𝑠𝑠
2
4. Tally the scores in the appropriate classes.
5. Find the other parts if necessary such as class marks, among
others.
EXAMPLE:
• Raw scores of 40 students in a 50-item Mathematics quiz. Construct a frequency
distribution following the steps given previously.
17 25 30 33 25 45 23 19
27 35 45 48 20 38 39 18
44 22 46 26 36 29 15 21
50 47 34 26 37 25 33 49
22 33 44 38 46 41 37 32
Construct the class limit starting with the lowest score as the lower limit of the first
category. The last category should contain the highest score in the distribution.
Each category should contain 6 as the size of the width (X). Count the number of
scores that falls in each category (f).
17 25 30 33 25 45 23 19
27 35 45 48 20 38 39 18
44 22 46 26 36 29 15 21
50 47 34 26 37 25 33 49
22 33 44 38 46 41 37 32
15-20
21-26
27-32
33-38
39-44
45-50
Utilization of Data: Introduction to Statistics

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Utilization of Data: Introduction to Statistics

  • 1. CHAPTER 5 UTILIZATION OF ASSESSMENTDATA CHRISTINE P. MEJINO BSEd III-A English
  • 2. STATISTICS • It is an important tool in the utilization of the assessment data most especially in describing, analyzing, and interpreting the performance of the students in the assessment procedures.
  • 3. DEFINITION OF STATISTICS • Is a branch of science, which deals with the collection, presentation, analysis, and interpretation of quantitative data. Collection Presentation Analysis Interpreta-tion
  • 4. STATISTICAL QUESTION • A question where you expect to get a variety of answers, and you are interested in the distribution and tendency of those answers.
  • 5. • Is a method concerned with collecting, describing and analyzing a set of data without drawing conclusions (or inferences) about a large group. DESCRIPTIVE STATISTICS
  • 6. • Is a branch of statistics, concerned with the analysis of a subset of data leading to predictions or inferences about the entire set of data. INFERENTIAL STATISTICS
  • 7.
  • 8. • Is a tabular arrangement of data into appropriate categories showing the number of observations in each category or group. FREQUENCY DISTRIBUTION
  • 9. A. It encompasses the size of the table. B. It makes the data more interpretative. ADVANTAGES OF FREQUENCY DISTRIBUTION
  • 10. 1. Class limit is the groupings or categories defined by the lower or upper limits. PARTS OF FREQUENCY TABLE
  • 11. Example Lower limits (LL) Upper limits (UL) 10 14 15 19 20 24 • Lower class limit (LL) represents the smallest number in each group. • Upper class limit (UP) represents the highest number in each group.
  • 12. 2. Class Size (c.i) is the width of each class interval. Example Lower limits (LL) Upper limits (UL) 10 14 15 19 20 24 The class size in this score distribution is 5. 11-12-13 16-17-18 21-22-23
  • 13. 3. Class Boundaries are the numbers used to separate each category in the frequency distribution but without gaps created by the class limits. The scores of the students are discrete. Add 0.5 to the upper limit to get the upper class boundary and subtract 0.5 to the lower limit to get the lower class boundary in each group or category. Lower limits (LL) Upper limits (UL) 10 14 15 19 20 24 LCB UCB 9.5 14.5 14.5 19.5 19.5 24.5
  • 14. 4. Class Marks are the midpoint of the lower and upper class limits. The formula is 𝑋 𝑚 = 𝐿𝐿+𝑈𝐿 2 Lower limits (LL) Upper limits (UL) 𝑋 𝑚 10 14 12 15 19 17 20 24 22
  • 15. 1. Compute the value of range (R). RANGE is the difference between the highest score and the lowest score. Determine the class size (c.i). The class size is the quotient when your divide the range by the desired number of classes or categories. The desired numbers of classes are usually 5, 10 or 15 and they depend on the number of scores in the distribution. If the desired number of classes is not identified, find the value of k, where k= 1+3.3 log n. STEPS IN CONSTRUCTING FREQUENCY DISTRIBUTION R= HS-LS
  • 16. 𝑐. 𝑖 = 𝑅 𝑑𝑒𝑠𝑖𝑟𝑒𝑑 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑐𝑙𝑎𝑠𝑠𝑒𝑠 𝑜𝑟 𝑐. 𝑖 = 𝑅 𝑘 (5, 10, 15) R=HS-LS k=1+3.3 log n
  • 17. 2. Set up the class limits of each class or category. Each class defined by the lower limit and upper limit. Use the lowest score as the lower limit of the first class.
  • 18. 3. Set up the class boundaries if needed. Use the formula: 𝑐𝑏 = 𝐿𝐿 𝑜𝑓 𝑡ℎ𝑒 𝑠𝑒𝑐𝑜𝑛𝑑 𝑐𝑙𝑎𝑠𝑠 − 𝑈𝐿 𝑜𝑓 𝑡ℎ𝑒𝑓𝑖𝑟𝑠𝑡 𝑐𝑙𝑎𝑠𝑠 2 4. Tally the scores in the appropriate classes. 5. Find the other parts if necessary such as class marks, among others.
  • 19. EXAMPLE: • Raw scores of 40 students in a 50-item Mathematics quiz. Construct a frequency distribution following the steps given previously. 17 25 30 33 25 45 23 19 27 35 45 48 20 38 39 18 44 22 46 26 36 29 15 21 50 47 34 26 37 25 33 49 22 33 44 38 46 41 37 32
  • 20. Construct the class limit starting with the lowest score as the lower limit of the first category. The last category should contain the highest score in the distribution. Each category should contain 6 as the size of the width (X). Count the number of scores that falls in each category (f).
  • 21. 17 25 30 33 25 45 23 19 27 35 45 48 20 38 39 18 44 22 46 26 36 29 15 21 50 47 34 26 37 25 33 49 22 33 44 38 46 41 37 32 15-20 21-26 27-32 33-38 39-44 45-50

Notes de l'éditeur

  1. What is the connection of Statistics to us? it is for us to assess the students’ learning in order to give a correct description and interpretation about the achievement of the students in a certain test in any form of classroom assessment. It is therefore important that a teacher knows or must have a background knowledge (good background knowledge) in order to do so. Sought for example is Maam Salvanera. (Elaborate…)
  2. Data doesn’t appear to you, and that the first process came… Collection of data- survey, perf experiments, measure and record Organize or Presentation- least to greatest, put in table, or graph Analyze- What does the data tell us, find the mean, median, mode, or range To get the sense what the date is all about Interpret- What does it help, answer the questions we have in mind.
  3. Survey Question- how much do you weigh? Statistical Question- Ho much does the six grades weigh?
  4. Examples could be: mean, median, mode, and standard deviation.
  5. To make a generalization, Examples are T-test, enova, etc.
  6. When we collect data from a sample, we could use either wo types of statistics we can run,
  7. Solve for Range R=HS-LS Solve for the value of K, since the desire number of class is not mentioned. Then, find the class size.