17Statistical Tool

There are four (4) kinds of statistical tool that will be used in our study. The

statistical tools used are Frequency and Percentage, Weighted Mean, Pearson Product and

the T- Test Significance Relationship. The purpose of statistical tool can help the

researcher to collect mathematical data for the beneficial to the upcoming outcome of the

study. This process helped the researcher to judge accordingly the gathered data whether

to accept the null hypothesis or not. These are the following formula:

Frequency and Percentage

Frequency refers to the number which tells how many times a particular data

appears. Percentage refers to the number or ratio expressed as a fraction of 100. The

formula for frequency is rendered as follows:

fi = f1, f2, f3, ................

The formula for percentage is rendered as follows:

(amount ÷ total) × 100 = percentage

Weighted Mean

In this method, the average is the data to be found. It is also defined as the central

tendency of a collection of numbers taken as the sum of the numbers is divided by the

collection’s size. Mean is also referred as the center of gravity of a distribution.

18Formula:

Where,

x¯ = weighted mean

xi = x1, x2, x3,. ..... = items given

and fi = f1, f2, f3, ...... = f requencies corresponding to the given items

Pearson Product

Is the relationship between independent and dependent variables. It indicates how

well the two sets of data are interconnected. Pearson correlation coefficient measures the

linear dependence of two variables upon each other. It is also referred as Pearson product-

moment correlation coefficient. The value of Pearson correlation coefficient lies between

-1 to +1. If the coefficient of correlation is zero, then there is no correlation between

given two variables. On the other hand, the perfectly positive correlation has a value of

+1, while a perfectly negative correlation has a value of -1.

Formula:

Where,

r = Pearson correlation coefficient

19x = Values in first set of data

y = Values in second set of data

n = Total number of values.

T- Test Significance Relationship

A t-test is one of the most frequently used procedures in statistics and it is probably

the most commonly used Statistical Data Analysis procedure for hypothesis testing. T test

is used to compare two different set of values.

Formula:

Where,

x1¯ = Mean of first set of values

x2¯ = Mean of second set of values

S1 = Standard deviation of first set of values

S2 = Standard deviation of second set of values

n1 = Total number of values in first set

n2 = Total number of values in second set.

The formula for standard deviation is given by:

20

Where,

x = Values given

x¯ = Mean

n = Total number of values