Multiple Regression Analysts Data Analysis Method
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independent variable. X
1
= Independent Variable Celebrity Athlete Endorser X
2
= Independent Variable Brand Awareness X
3
= Independent Variable Brand Association X
4
= Independent Variable Brand Personality E = Standard errors
From the counting with SPSS 20 gain the information and explanation on the coefficient determination, F test, and T test to answer the formulation
of the problems. The following explanations are connecting the problems above:
a. The coefficient Determination R
2
The coefficient of determination R
2
essentially measures how far the ability of models to explain variation in the dependent variable. The
value determination of coefficient is between zero and one. The R
2
is small means that the ability of independent variables in explaining
variations in the dependent variable is very limited. Each additional independent variable then would increase R
2
, no matter whether these variables affect the dependent variable or not. Therefore, this study uses
the R
2
that have been adapted or adjusted for the variables used. The adjusted R
2
value can rise or fall if an independent variable added into the model Ghazali, 2005.
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b. Hypothesis testing for F-test Simultaneously Test F test essentially indicates whether all the independent variables or
independent variables included in the model have jointly influence on the dependent variable or bound. The probability is smaller than 0.05, then the
result means that there are significant effects of independent variables collectively against the dependent variable Ghazali, 2005:84. These steps
are applied to examine the hypothesis with F Test is as follows: 1 Determine Ho and Ha
Ho: β
1
, β
2
= 0, this means there is no significant influence between independent variable and dependent variable.
Ho: β
1
, β
2
≠ 0, this means there is significant influence between independent variable and dependent variable.
a Determining level of significance Level of significant level used is 5 or
α = 0.05 b Determining the criteria acceptance and reject of Ho
If probability 0, 05 reject Ho If probability 0, 05 fail to reject Ho
If F test F table, so Ho is rejected and Ha is accepted; this means independent variable together have significant influence to dependent
variable. If F test F table, so Ho is accepted and Ha is rejected; this means
independent variable together do not have significant influence to dependent variable.
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c. Hypotheses testing for t Test Partial Test This test method is used to test the partial coefficient of the free
variable to the variable bound by the hypothesis put forward. T test basically shows how much influence a single dependent variable. The
probability is smaller than 0.05, then the result means that there are significant independent variables individually influence on the dependent
variable Ghozali, 2006:84. 1 If -t table t test +t table, then Ho is rejected and Ha is accepted, it
means there is significant influence between independent variable toward dependent variable.
2 If t test t table or -t test -t table, then Ho is accepted and Ha is rejected, it means there is no significant influence between
independent variable toward dependent variable. Ho: Using celebrity athlete endorser, brand awareness, brand
association, and brand personality there is no significant influence toward purchase intention.
Ha: Using celebrity athlete endorser, brand awareness, brand association, and brand personality there is significant influence toward
purchase intention. The criteria to making decision significance with
α = 0,05; 1 If probability
α 0.05, so Ho accept. It means using celebrity athlete endorser, brand awareness, brand association, and brand personality
there is no influence toward purchase intention.
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2 If probability α 0.05, so Ho reject. It means using celebrity athlete
endorser, brand awareness, brand association, and brand personality there is influence toward purchase intention.