MAED 403 – EDUCATIONAL STATISTICS WITH COMPUTER APPLICATION

Graduate School of Education
MAED 403 – EDUCATIONAL STATISTICS WITH
COMPUTER APPLICATION
Professor: DR. JESUS B. GOLLAYAN SUMMER, SY 2021-2022
FINAL EXAMINATION
Student: _________________________
PROBLEM SET Note : Submit Problem Set outputs in PDF files.
TEST I. True or False: In the blank before each statement write T for true statement
and F for false statement.
___1. Variable is any quantity or characteristics that can be measured or counted.
___2. Population is portion of a sample.
___3. Nominal data are classified into categories that may not be in particular order for
classification.
___4. Set of data grouped according to major academic program – Education, Tourism,
Business Management, and Medical Technology, is an example of ordinal data.
___5. “Level of Proficiency” in descriptive rating is an example of qualitative variable.
___6. Set of statistics scores in 50-item test organized in class intervals is a grouped
frequency distribution.
___7. Score is a variable consisting of ordinal scale of measurement.
___8. Rating scale: Slightly Effective; Moderately Effective; Effective; and Very
Effective is an interval scale of measurement.
___9. Variable in categories generates nominal data.
___10. Frequency distribution of qualitative variable presents count data.
___11. Arrangement of raw data in ascending order or descending order is called an
array.
___12. Relative frequency distribution is obtained by dividing the frequencies by the
number of observations and then multiplying by 100%.
___13. In the class interval 10 – 20, the upper limit is 20.5.
___14. In the class interval 20 – 30, the class mark is 10.
___15. Mean is a measure of central tendency.
___16. The higher the value of variance the less spread is the distribution.
___17. Standard deviation is a measure of dispersion of a set of quantitative data.
___18. In a test of hypothesis, the alternative hypothesis Ha is a statement expressing
not against the null hypothesis.
___19. Negative coefficient of correlation shows direct relationship.
___20. Value of p = 0.50 in a test of significant difference at α = 0.05 level of
significance indicates that null hypothesis is rejected.
TEST II. PROBLEM SOLVING
COMPARATIVE ANALYSIS. In problems 1-3, perform a test of hypothesis using the
decision model shown below. (Follow strictly the format.)
1. The data gathered from first year and second year students selected randomly regarding
their ratings on the foods served in school canteen are as follows : (rating scale: 1 – 5 )
First Year : 4 3 4 4 5 4 5 4 3 4 3
Second Year : 3 3 4 3 2 3 3 4 3 3 2 5 4
Do first year and second year students significantly differ in their ratings on the foods served
in school canteen? Use α = 0.05.
Descriptive ratings consist of N (Needs Improvement), F (Fair), S (Satisfactory),
VS (Very Satisfactory), and E (Excellent).
Rating scale: N = 1; F = 2; S = 3; VS = 4; E = 5,
2. Determine if the training strategy is effective by conducting a test of difference
between the Pre- test and Post- test scores (20-point rating scale) of 11 participants using 5%
level of significance.
Participant: 1 2 3 4 5 6 7 8 9 10 11
Post-test Scores: 17 15 17 20 18 16 19 15 14 17 19
Pre-test Scores: 12 10 13 11 14 14 16 16 10 12 14

3. The table presents data on overall job satisfaction mean ratings (scale of 1 – 5) among faculty
members grouped according to educational attainment.
INDICATOR
EDUCATIONAL ATTAINMENT
Bachelor’s
Degree
Master’s
Degree
Doctorate
Degree
General Working Condition 3.56 3.75 3.63
Salary 2.65 3.89 2.48
Promotion 2.54 3.98 3.11
Fringe Benefits 3.23 3.34 3.21
Work Relations 2.54 4.48 3.76
Use of Skills and Abilities 3.92 4.11 3.56
Work Activities 3.67 4.25 3.31
Is there a significant difference in the overall job satisfaction mean ratings among the
faculty members grouped according to educational attainment? Use five percent level
of significance.
CORRELATION-REGRESSION ANALYSIS
4. Consider the following data gathered from five (5) bookstores on the price of a specified
advanced educational management book and the demand for the book item.
4.1 Draw the scatter diagram.
4.2 Find “r” and interpret. Describe the strength and direction of the relationship between price
and demand.
4.3 Test the significance of relationship at five percent level of significance. Follow the decision
format. (Find p-value using fx : = T.DIST.2T(t,df))

5. Twelve students were given mental ability test and an achievement test in Statistics with
the following scores:
Mental Ability : 64 55 50 47 39 29 32 45 55 51 45 36
Achievement Test : 68 65 58 52 44 37 48 42 50 41 60 45
5.1 Construct the scatter diagram.
5.2 Calculate “r” and test the significance of relationship. Interpret the result and follow the
decision format.
5.3 Set the regression equation.
5.4 Test the significance of prediction. Interpret the result and follow the
decision format.
5.4 Construct the regression line.
5.5 Predict the Achievement Test score knowing Mental Ability Test score of 35.

BOOKSTORE 1 2 3 4 5
PRICE 1,300 1,250 1,150 1,100 1,000
DEMAND 100 150 200 300 250
6. The data gathered from ten (10) college students selected randomly are presented below.
Student
Senior High School
General Average
Grade, X1
Assessment Rating
on School Facilities
X2
First Year BS Course
General Average
Grade, Y
1 79 3 80
2 85 5 86
3 76 3 75
4 89 5 90
5 80 4 78
6 78 4 79
7 90 5 87
8 82 4 80
9 92 5 95
10 90 5 90

6.1 Develop the regression equation, Y = a + b1X1 + b2X2
6.2 Test the significance of prediction at five percent level of significance. Follow the decision
format.
6.3 Predict the First year BS Course General Average Grade given Senior High School
General Average Grade of 86 and Assessment Rating of 4 on School Facilities.
DECISION MODEL FORMAT
Present EXCEL DATA
ANALYSIS computations/outputs in separate EXCEL worksheet for
a. Comparative Analysis b. Correlation Analysis. and c. Regression Analysis.
FOR COMPARATIVE ANALYSIS
Null Hypothesis:
Alternative Hypothesis:
Data Analysis: (Perform the calculations.)

(For ANOVA, F-test)
Bachelor’s
Degree
Master’s
Degree
Doctorate
Degree
Mean
Variance
Observations
F-value =
p-value =
Decision/Conclusion:

FOR CORRELATION ANALYSIS
Null Hypothesis:
Alternative Hypothesis:
Mean
Variance
Observations
t-value =
p-value (2T) =
Data Analysis: (Perform the calculations.)
Correlates: Price x Demand
Observations =
r-value =
t-value =
p-value (2T) =
(NOTE: Find p-value using fx : = T.DIST.2T(t,df)
Decision/Conclusion:
FOR REGRESSION ANALYSIS
Null Hypothesis:
Alternative Hypothesis:
Data Analysis: (Perform the calculations.)
Regression Model: Y = a + b(Mental Ability Test)
Observations =
Intercept, a =
Coefficient, b =
t Stat (for X) =
p-value (2T) =
Decision/Conclusion:
Regression Model: a + b1( ) + b2( )
Observations =
Intercept, a =
Coefficients:
b1 =
b2 =
t Stat (for X1) =
p-value (for X1) =
t Stat (for X2) =
p-value (for X2) =
Decision/Conclusion:
RESEARCH WORK: Submit research paper (through internet referencing) on:
1. CORRELATION
– Definition
– Pearson’s “r” Coefficient of Correlation and interpretation of r-value
– Scatter Diagram and Interpretation
– Sample solved problem on a) direct relationship and on b) inverse
relationship
2. SIMPLE LINEAR REGRESSION AND MULTIPLE REGRESSION
– Definition
– Sample applied problem and solution on a) simple linear regression
and on b) multiple regression
Note: Research Work must be accomplished in MS word document using legal size paper, Arial
(font 12), single space.

Rating Scale for Performance Task:
SUBMISSION Highest Possible Rating (%)
Highest
Descriptive
Rating
On or Before the Deadline
(Cut-off Date) 99- 100 Outstanding
Two days (Grace Period)
Beyond Cut-off Date 96- 98 Very
Satisfactory
Beyond the Grace Period 93- 95 Satisfactory
Non-submission Before
Automate Encoding of
Final Grade
INCOMPLETE
Grading Description:
Percentage (%) Numerical
Equivalent
Description
99- 100 1.00 Outstanding
96- 98 1.25 Very Satisfactory
93- 95 1.50 Satisfactory
90- 92 1.75 Passing for PhD
87- 89 2.00 Passing for MA
Below 90 (PhD)
Below 87 (MA)
5.00 Failure
OD Officially Dropped
UD Unofficially Dropped
NC No Credit
FA Failure Due to Excessive
Absences

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