Exploring ANCOVA: Shopping Well-Being and Consumer Income

1.Does shopping well-being vary due to consumer income under the potential effect of utilitarian value? (ANCOVA) STEP 1 : Click Analysis > General Linear Model > Univariable

STEP 2 : In the Univariable box, switching SWB1, which is dependencies to the Dependent Variables box and Income to independently to the Fixed Factor(s) and UV1 to covariables STEP 3 : Click Options to open the Univariable: Options box. Select Descriptive Statistics (to win the description). Estimates of effect size (for estimating effect size), homogeneity tests (for checking the homogeneity of the wrong way). Then click Continue.

STEP 4 : Click Save to open the Univariable: Save box. Select Unstandardized (proposal of non-standardized residual data), Standardized (to export standardized residual data). And finally, clicking the Continue button to run the result

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● The Descriptive Statistics table presents descriptive statistics (mean, standard deviation, number of participants) on the dependent var. ● Look in the Levene's Test of Equality of Error Variances, under the Sig. column. This is the p-value that is interpreted. If the p-value is LESS THAN .05, then researchers have violated this assumption and should check for outliers or run non-parametric tests.

If the p-value is MORE THAN .05, then researchers have met the assumption and continue with the analysis. ● The main section of the results is presented in the Tests of Between- Subjects Effects table, as shown below: ● This table informs you whether the different interventions were statistically significantly different having adjusted for your covariate. Look at the table, under the Sig. column. These are the p-values that are interpreted. If the p-value is LESS THAN .05, then the covariate significantly adjusts the association between the predictor and outcome variable. If the p-value is MORE THAN .05, then the covariate does NOT adjust the association between the predictor and outcome variable.

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In this example, as we can see from the table, the p-value is more than .05, so we can conclude that the covariate does NOT adjust the association between the predictor and outcome variable.

2. Does shopping well-being vary due to consumer income under the potential effect of hedonic value? (ANCOVA) STEP 1 : Click Analysis > General Linear Model > Univariable STEP 2 : In the Univariable box, switching SWB1, which is dependencies to the Dependent Variables box and Income to independently to the Fixed Factor(s) and HV1 to covariables STEP 3 : Click Options to open the Univariable: Options box. Select Descriptive Statistics (to win the description). Estimates of effect size (for estimating effect size), homogeneity tests (for checking the homogeneity of the wrong way). Then click Continue. STEP 4 : Click Save to open the Univariable: Save box. Select Unstandardized (proposal of non-standardized residual data), Standardized (to export standardized residual data). And finally, clicking the Continue button to run the result

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● The Descriptive Statistics table presents descriptive statistics (mean, standard deviation, number of participants) on the dependent var. ● Look in the Levene's Test of Equality of Error Variances, under the Sig. column. This is the p-value that is interpreted. If the p-value is LESS THAN .05, then researchers have violated this assumption and should check for outliers or run non-parametric tests. If the p-value is MORE THAN .05, then researchers have met the assumption and continue with the analysis.

● The main section of the results is presented in the Tests of Between- Subjects Effects table, as shown below: ● This table informs you whether the different interventions were statistically significantly different having adjusted for your covariate. Look at the table, under the Sig. column. These are the p-values that are interpreted. If the p-value is LESS THAN .05, then the covariate significantly adjusts the association between the predictor and outcome variable. If the p-value is MORE THAN .05, then the covariate does NOT adjust the association between the predictor and outcome variable. In this example, as we can see from the table, the p-value is more than .05, so we can conclude that the covariate does NOT adjust the association between the predictor and outcome variable.

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CÂU 3: Does shopping well-being vary due to consumer income under the potential effect both utilitarian value and hedonic value? (ANCOVA)

Look in the Levene's Test of Equality of Error Variances, under the Sig. column, the p-value is MORE THAN .05, then researchers have met the assumption and continue with the analysis.

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In the Tests of Between-Subjects Effects table, In this example, as we can see from the table, the p-value is more than .05, so we can conclude that the covariate does NOT adjust the association between the predictor and outcome variable. CÂU 4: Does shopping well-being vary due to consumer income and gender under the potential effect of utilitarian value and hedonic value? (ANCOVA)

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Look in the Levene's Test of Equality of Error Variances, under the Sig. column, the p-value is LESS THAN .05, then the covariate significantly adjusts the association between the predictor and outcome variable.

CHẠY ANCOVA SPSS DOCX

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