Page 180 - Contributed Paper Session (CPS) - Volume 8

CPS2231 Syafawati A. R. et al.
2. Methodology
Data
The objective of this study is to determine the impact of tourism
industry on CPI for the case of Melaka. The monthly time series data on
total number of tourist arrival and CPI for Melaka over the period of 2013
to 2017 are utilised in this study. The data of the total number of tourist
arrival was obtained from Melaka Tourism Board (MTB), while the data on
CPI was obtained from Department of Statistics Malaysia (DOSM). The
variables used in this study are symbolized and describes as follows:
Tourist: Total number of tourist arrival to Melaka
CPI: Consumer price index
Methodology
This section described briefly about the statistical techniques applied
to analyse data collected from DOSM and MTB. Two methods were used
in this study; Simple Linear Regression Model and Stepwise Regression
Analysis.
a) Simple Linear Regression Model (SLR)
Regression analysis is a statistical methodology that attempts to
explore and model the relationship between two continuous variables.
SLR is a model with single regressor x that has a relationship with a
response y that is a straight line. The SLR model can be expressed as:

= 0 + 1 +

where x denotes the independent variable (tourist arrival); y is the
dependent variable (CPI) and ε is a random error.
b) Stepwise Regression Model
Stepwise regression is a semi-automated process of building a
model by successively adding or removing variables based solely on
the t-statistics of their estimated coefficients. In order to use the
stepwise regression, simple (pair-wise) correlation coefficient and
partial correlation coefficient between y and each of x variables need
to be calculated.
The simple correlation coefficient between two variables, y and x,
is simply the ratio between their covariance and the product of their
respective standard deviation, which is:

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