SPSS OUTPUT & INTERPRETATION

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Presentation transcript:

SPSS OUTPUT & INTERPRETATION 13/11/2018 SPSS/SITINORYAACOB/PJJSEM2_2015/2016 SPSS OUTPUT & INTERPRETATION Dr. Siti Nor Binti Yaacob

Quantitative Research 13/11/2018 SPSS/SITINORYAACOB/PJJSEM2_2015/2016 Quantitative Research Type of research objectives Objective Data analysis Descriptive (univariate) To describe demographic background (e.g., age, gender), and the levels of independent variables (e.g., loneliness) and dependent variable (e.g., internet addiction. Descriptive analysis Difference between two groups (0,1) (bivariate) To examine the difference on tested variables (e.g., loneliness) among two groups (males and females). Independent t-test Relationship (bivariate) To examine the relationship between independent and dependent variables. Pearson correlation

SPSS/SITINORYAACOB/PJJSEM2_2015/2016 13/11/2018 SPSS/SITINORYAACOB/PJJSEM2_2015/2016 Title: Relationship between loneliness and internet addiction among adolescents in Penang. Steps in analysis: Descriptive analysis Bivariate analysis T-test (Ho: There is no significant difference in internet addiction between male and female adolescents.) Pearson correlation (Ho: There is no significant relationship between loneliness and internet addiction.)

SPSS/SITINORYAACOB/PJJSEM2_2015/2016 13/11/2018 SPSS/SITINORYAACOB/PJJSEM2_2015/2016 Descriptive Analysis Step 1: Analyze  Descriptive Statistics  Frequencies… Step 2: select the variables and click in the box

SPSS/SITINORYAACOB/PJJSEM2_2015/2016 13/11/2018 SPSS/SITINORYAACOB/PJJSEM2_2015/2016 Step 3: Click “statistics” and choose “ mean, median, std. deviation, variance, range, minimum and maximum”.  click “continue”

SPSS/SITINORYAACOB/PJJSEM2_2015/2016 13/11/2018 SPSS/SITINORYAACOB/PJJSEM2_2015/2016 Step 4: Click “OK”. Step 5: Interpret output

Example of Descriptive Table: 13/11/2018 SPSS/SITINORYAACOB/PJJSEM2_2015/2016 Example of Descriptive Table:

Example of Interpretation: 13/11/2018 SPSS/SITINORYAACOB/PJJSEM2_2015/2016 Example of Interpretation: Respondents’ age The respondents aged between 15 to 18 years old (mean=16.09, SD.=0.670). Majority (55.1%) of the respondents were 16 years old.

SPSS/SITINORYAACOB/PJJSEM2_2015/2016 13/11/2018 SPSS/SITINORYAACOB/PJJSEM2_2015/2016 Independent t-test Step 1: Analyze  Compare Means  Independent Sample t-test

SPSS/SITINORYAACOB/PJJSEM2_2015/2016 13/11/2018 SPSS/SITINORYAACOB/PJJSEM2_2015/2016 Step 2: Choose tested variable and put “groups” into “Grouping Variable”. Step 3: State “Define Groups” (e.g., male= 0; female=1)  continue

SPSS/SITINORYAACOB/PJJSEM2_2015/2016 13/11/2018 SPSS/SITINORYAACOB/PJJSEM2_2015/2016 Step 4: Click “OK” Step 5: Output

SPSS/SITINORYAACOB/PJJSEM2_2015/2016 13/11/2018 SPSS/SITINORYAACOB/PJJSEM2_2015/2016 Step 6: Interpret output Based on F significant value of Levene’s test (Circle with red color), If F Value is not significant (p≥.05), report t-value and p value [sig. (2-tailed)] from “equal variance assumed”. if F Value is significant (p<.05), report t-value and p value [sig. (2-tailed)] from “equal variance not assumed”. Mean scores

Example of t-test table: 13/11/2018 SPSS/SITINORYAACOB/PJJSEM2_2015/2016 Example of t-test table: Example of Interpretation: There was a significant difference (t=3.489, p<.01) in internet addiction between male and female adolescents. Male adolescents (mean= 55.42) were found to have higher level of internet addiction than female adolescents (mean= 47.29). Therefore, null hypothesis was rejected. Note: Can add some related past studies to support the results.

SPSS/SITINORYAACOB/PJJSEM2_2015/2016 13/11/2018 SPSS/SITINORYAACOB/PJJSEM2_2015/2016 Pearson Correlation Step 1: Analyze  Correlate  Bivariate..

SPSS/SITINORYAACOB/PJJSEM2_2015/2016 13/11/2018 SPSS/SITINORYAACOB/PJJSEM2_2015/2016 Step 2: Select variables and click into “Variables” box then click “OK”

SPSS/SITINORYAACOB/PJJSEM2_2015/2016 13/11/2018 SPSS/SITINORYAACOB/PJJSEM2_2015/2016 Step 3: Interpret output

Example of Pearson correlation table: 13/11/2018 SPSS/SITINORYAACOB/PJJSEM2_2015/2016 Example of Pearson correlation table: Example of interpretation: There was a significant correlation (r= .213, p<.001) between loneliness and internet addiction. The positive correlation between loneliness and internet addiction indicated that the higher the loneliness, the higher the internet addiction among adolescents. Therefore, null Hypothesis was rejected. Note: Can add some related past studies to support the results.