Descriptive StatisticsMeasures of Central Tendency, Variability, Location, Skewness, and Shapes.

Inferential StatisticsHypothesis Testing, relationship and regression, parametric and non-parametric statistics such as z-test, t-test, chi-square test, F –test (ANOVA), mann-whitney U test, Spearman rank correlation, etc.

Sources: Glass,G.V. and J.C. Stanley. (1970). Statistical Methods in Education

and Psychology. U.S.A.: Prentice –Hall ,Inc.

Brase, C.H. and C.P. Brase. (1987). Understandable Statistics.U.S.A.: Heath and Company.

Hypothesis Testing

Hypothesis testing is the process of inferring from a sample whether to accept or reject a certain statement about the population. In most cases, a working hypothesis is an educated guess that a researcher made about the chosen sample of used in the study. Examples of hypothesis is as follows:

1.Boys are better than girls in manipulative skills.

2.There is no significant correlation between interest in science and the career choice of high school graduates in science.

3.Girls are better than boys in taking down notes.

4.Method A is more effective in developing the higher order thinking skills of the learners than Method B.

The acceptance or rejection of the working or statistical hypothesis is based on the level of significance selected. Usually, the level of significance is generally set at 5% or at alpha (ά) = 0.05. If you will allow yourself to make 5% error in your final statement, then choose ά = 0.05 or if you would like to make a more stringent statement, then improve the level of significance to ά = 0.01 or 0.001.

The term null hypothesis (Ho) is used for any hypothesis which is set up primarily for the purpose of seeing whether it can be rejected.

Any hypothesis which differs from the null hypothesis is called an alternative hypothesis (Ha). An alternative hypothesis is constructed in such a way that it is the one to be accepted when the null hypothesis must be rejected.

Example1. If we are going to test the correlation of Physics and Physical Education subjects, we formulate the Null hypothesis (Ho) and the Alternative hypothesis (Ha) as follows:

Ho: There is no correlation between Physics and Physical Education subjects

Physics and Physical education subjects are not correlated.

Ha: There is a correlation between Physics and Physical Education subjects

Physics and Physical education subjects are correlated.

Example 2. If we are to test the Different responses of the Different Groups, the Ho and Ha would be as follows:

Ho: The responses of the different groups do not differ

There is no significant difference among the responses of the different groups.

Ha: The responses of the different groups differ

There is a significant difference among the responses of the different groups.

Additional Examples:

Ho: The Filipino and Non-Filipino do not differ from their views of war.

Ha: The Filipino and Non-Filipino differ from their views of war.

Ho: The students do not differ in their views of war when classified according to sex, educational level, curriculum year and leadership status.

Ha: The students differ in their views of war when classified according to sex, educational level, curriculum year and leadership status.

Title: Views of War Among Undergraduate and Graduate Students: A Cross- Cultural Study

by Lupdag, Rayos & Santos

Additional Examples:

Ho: There is no significant relationship between the grades in Mathematics of the Deaf and Mute students and their grades in English subjects.

Ha: There is a significant relationship between the grades in Mathematics of the Deaf and Mute students and their grades in English subjects

Ho: There is no significant difference between the sexes of the Deaf and Mute students in terms of their grades in

a. English b. Mathematics

Ha: There is a significant difference between the sexes of the Deaf and Mute students in terms of their grades in

a. English b. MathematicsTitle: Relationship between the English Grades and the Mathematics Grades of the Deaf and Mute Students by Subia & Mamaclay

Additional Examples:

Ho: There is no significant difference between the competencies of BHW of San Jose and Sta. Arcadia

Ha: There is a significant difference between the competencies of BHW of San Jose and Sta. Arcadia

Ho: SDP,HCDS, and BHW do not predict level and frequency of Community Involvement

Ha: SDP,HCDS, and BHW predict level and frequency of Community Involvement

Title: Predictors of Community Involvement in Health and Heath Related Projects and Programs in Two Barangays in Nueva ecija by M. Gonzales Dean Marilyn Bautista, AdviserGener Subia, Statistician

Smith, C. R. (2004). Learning disabilities: The Interaction of students and their environment (5th ed.). Boston: Pearson

Education. Choate,J.S., Enright, J.S., Enright, B.E. Miller,L.J., Poteet, J.A., &

Rakes, T. A. (1995). Curriculum-based assessment and programming. Boston: Allyn & Bacon.

Cohen, L.G. & Speciner, L.J. (2003). Assessment of children and youth with special needs. Boston: Allyn & Bacon.

APA FORMAT

PARAMETRIC TESTParametric tests are applied to data that are

normally distributed, the levels of measurement of which are expressed in interval and ratio. Parametric statistics are more powerful than nonparametric statistics. The parametric tests are:

z-test

t-test

F-test (ANOVA)

r ( Pearson Product Moment Correlation)

The p-value

The smallest level of significance at which Ho will be rejected based on the information contained in the sample.

An Alternative form of decision rule (based on the p-value)

Reject Ho if the p-value is less than or equal to the level of significance(ά).

Example: at ά = 0.05

p-value Decision

0.01 Reject Ho

0.05 Reject Ho

0.17 Do not reject Ho

Z-test

It is used to compare the two sample means taken from the samples are equal to or greater than 30. The z- test can be applied in two ways: the One-Sample Mean Test and the Two-Sample Mean Test.

The z-test is a parametric statistics used to compare two means the sample mean and the perceived population mean.