Dr. Siti Nor Binti Yaacob 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 APPENDIX 2 CONTOH PENYEDIAAN JADUAL DAN INTERPRETASI DATA SPSS Dr. Siti Nor Binti Yaacob

Quantitative Research 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 Quantitative Research Type of research objectives Objective Data analysis Descriptive 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 groups (bivariate) Difference between two groups (0,1) To examine the difference on tested variables (e.g., loneliness) among two groups (males and females). Independent t-test Difference between more than two groups (0,1,2) To examine the difference on tested variables (e.g., internet addiction) among ethnics groups (Malay, Chinese and Indian). One way ANOVA

Quantitative Research 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 Quantitative Research Type of research objectives Objective Data analysis Association between 2 categorical variables To examine the association between 2 categorical variables Chi-Square Relationship (bivariate) To examine the relationship between independent and dependent variables. Pearson correlation Relationship / Predicting Effect (multivariate) To determine the unique predictor of dependent variable. Multiple regression analysis

SITINORYAACOB/FEM4999B/2014/2015 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 Data Entry Varaible View

Data Transformation(recode data) 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 Data Transformation(recode data) Transform  Recode Into Different Variable  “choose your item”  input variable --> renew the name in output variable (name and label)  Change. Old and New Values  eg. 1 change to 5  add  continue  OK

SITINORYAACOB/FEM4999B/2014/2015 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 Reliability test Analyze  Scale  Reliability Analysis  choose all of the tested items Scale label, type the name of variable . Statistics  Choose “Item, Scale, and Scale if Item Deleted”. Continue OK.

SITINORYAACOB/FEM4999B/2014/2015 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 Descriptive Analysis Step 1: Analyze  Descriptive Statistics  Frequencies… Step 2: select the variables and click in the box

SITINORYAACOB/FEM4999B/2014/2015 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 Step 3: Click “statistics” and choose “ mean, median, std. deviation, variance, range, minimum and maximum”.  click “continue”

SITINORYAACOB/FEM4999B/2014/2015 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 Step 4: Click “OK”. Step 5: Interpret output

Example of Descriptive Table: 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 Example of Descriptive Table:

Example of Interpretation: 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 Example of Interpretation: Respondents’ age The respondents aged between 15 and 18 years old (Mean=16.09, SD.=0.670). Majority of the respondents (55.1%) were 16 years old.

SITINORYAACOB/FEM4999B/2014/2015 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 Independent t-test Step 1: Analyze  Compare Means  Independent Sample t-test

SITINORYAACOB/FEM4999B/2014/2015 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 Step 2: Choose tested variable and put “groups” into “Grouping Variable”. Step 3: State “Define Groups” (e.g., male= 0; female=1)  continue

SITINORYAACOB/FEM4999B/2014/2015 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 Step 4: Click “OK” Step 5: Output

SITINORYAACOB/FEM4999B/2014/2015 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 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: 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 Example of t-test table: Example of Interpretation: There was difference in internet addiction between male and female adolescents (t=3.489, p<.01). Male adolescents (mean= 55.42) were found to have higher level of internet addiction than female adolescents (mean= 47.29). Null hypothesis was rejected. Note: You can add some related past studies to support the result.

SITINORYAACOB/FEM4999B/2014/2015 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 One way ANOVA Step 1: Analyze  Compare Means  One-Way Anova Step 2: Choose “tested continuous variables into the “Dependent list”. Step 3: Choose categorical variable into the “Factor”. Step 4: Post Hoc  Tukey Step 5: Options  Choose “Descriptive”. Step 6: Continue  OK

SITINORYAACOB/FEM4999B/2014/2015 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 Output

SITINORYAACOB/FEM4999B/2014/2015 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015

One way ANOVA- Interpretation 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 One way ANOVA- Interpretation

SITINORYAACOB/FEM4999B/2014/2015 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 Chi-Square Step 1: Analyze  Descriptive statistics  Crosstabs Step 2: Row: “races”; Column: “internet access” Step 3: Statistics  check “chi-square” & “contingency coefficient”  Continue  OK

SITINORYAACOB/FEM4999B/2014/2015 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 Output of Chi-square

SITINORYAACOB/FEM4999B/2014/2015 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 Output of Chi-square A valid Chi-square will present the expected count of less than 5 in the table should not be more than 15.0% of the total number in the same row (Sirkin, 2005). X² Not a valid chi-square model.

SITINORYAACOB/FEM4999B/2014/2015 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 Interpretation If there is a valid chi-square model: 28.8

SITINORYAACOB/FEM4999B/2014/2015 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 Pearson Correlation Step 1: Analyze  Correlate  Bivariate..

SITINORYAACOB/FEM4999B/2014/2015 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 Step 2: Select variables and click into “Variables” box then click “OK”

SITINORYAACOB/FEM4999B/2014/2015 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 Step 3: Interpret output

Example of Pearson correlation table: 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 Example of Pearson correlation table: Example of interpretation: The result showed that there was a significant positive correlation between loneliness and internet addiction (r= .213, p<.001). The direction of relationship indicated that respondents with higher loneliness score, tend to report higher internet addiction. Therefore, null hypothesis that there is no significant relationship between loneliness and internet addiction was rejected. Note: You can add some related past studies to support the results.

SITINORYAACOB/FEM4999B/2014/2015 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015 Multiple regression Step 1: Analyze  Regression  Linear. Step 2: Choose dependent variable into “Dependent”. Step 3: Choose independent variables into “Independent variables”. Step 4: Statistics  Estimates, Confidence intervals, model fit, descriptives”. Step 5: Continue OK.

SITINORYAACOB/FEM4999B/2014/2015 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015

SITINORYAACOB/FEM4999B/2014/2015 3/6/2018 SITINORYAACOB/FEM4999B/2014/2015