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4.4 ANOVA ONE-WAY ANALYSIS

ANOVA One-way analysis of variance is similar to t-test, although it is used to compare the means of two or more
independent groups and determine if there is any significant difference between them on the same continuous, dependent
variable. In this research, the demographic items that are used to test the variance which is age, type of smartphone, and
experience with smartphone fitness apps that have a different number of groups. Therefore, to appear significant difference,
the significant value must be below 0.05.

Table 4.4: ANOVA Results for Age, Monthly Income and Annual Travel Capability

Items Sig. Value Means
26 - 35 36 - 45 46 - 55 56 years old
Age 0.136 years old years old years old and above
4.85 4.50 4.66 4.56
Below RM1001 - RM3001 - RM5001 - RM7001 - RM9001
Monthly Income 0.819 RM1000 RM3000 RM5000 RM7000 RM9000 and above
4.61 4.71 4.61 4.57 4.55 4.55
1 - 2 3 - 4 times 5 - 6 times 7 times and
Annual Travel 0.323 times above
Capability 4.54 4.69 4.67 4.72

The result of ANOVA One-way analysis shows that there is no significant difference between age (sig. = 0.136;
highest mean = 4.85 of 26 – 35 years old), monthly income (sig. = 0.819: highest mean = 4.71 of RM1001 - RM3000) and
annual travel capability (sig. = 0.323; highest mean = 4.76 of 7 times and above) in his research. All the service positioning
that conducted by Tiram by age, monthly income and annual travel capability as the result showed the significant value was
above 0.05.

4.5 SCALE MEASUREMENT

4.5.1 NORMALITY TEST

Normality test is a summarization of data into Skewness and Kurtosis that is used to determine whether a
sample or any group of data was taken from are a standard normal distribution. The value of the skewness shows the distribution's
symmetry. On the other hand, Kurtosis offers details regarding the distribution "peakedness". The skewness values should be
between -2 to +2 and kurtosis values should be between -7 and +7 then the data is considered acceptable, for a normal distribution
as stated by Hair et al. (2010).

Table 4.5: Normality Test

Std. Mean Skewness Kurtosis
Construct Variables
Deviation Value SE Value SE Value SE
Positioning DV .450 4.63 .041 -1.181 .221 .914 .438
Service Innovation IV1 .463 4.72 .042 -1.844 .221 2.934 .438
Reliability IV2 .515 4.54 .047 -1.286 .221 1.378 .438
Brand Endorsement IV3 .480 4.68 .044 -1.447 .221 1.445 .438

Based on table 4.5, the results of the normality test for all the variables are normally distributed. The Skewness and
Kurtosis values are considered acceptable as all values fall into the ideal range for skewness -2 to +2 and kurtosis between -7
to +7.

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