Dr. Siti Nor Binti Yaacob 18/9/2018 SPSS/SITINORYAACOB/SEM2_2014/2015 SPSS Dr. Siti Nor Binti Yaacob

Quantitative Research 18/9/2018 SPSS/SITINORYAACOB/SEM2_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 18/9/2018 SPSS/SITINORYAACOB/SEM2_2014/2015 Quantitative Research Type of research objectives Objective Data analysis 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

SPSS/SITINORYAACOB/SEM2_2014/2015 18/9/2018 SPSS/SITINORYAACOB/SEM2_2014/2015 Data Entry Varaible View

Data Transformation(recode data) 18/9/2018 SPSS/SITINORYAACOB/SEM2_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

SPSS/SITINORYAACOB/SEM2_2014/2015 18/9/2018 SPSS/SITINORYAACOB/SEM2_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.

SPSS/SITINORYAACOB/SEM2_2014/2015 18/9/2018 SPSS/SITINORYAACOB/SEM2_2014/2015 Descriptive Analysis Step 1: Analyze  Descriptive Statistics  Frequencies… Step 2: select the variables and click in the box

SPSS/SITINORYAACOB/SEM2_2014/2015 18/9/2018 SPSS/SITINORYAACOB/SEM2_2014/2015 Step 3: Click “statistics” and choose “ mean, median, std. deviation, variance, range, minimum and maximum”.  click “continue”

SPSS/SITINORYAACOB/SEM2_2014/2015 18/9/2018 SPSS/SITINORYAACOB/SEM2_2014/2015 Step 4: Click “OK”. Step 5: Interpret output

Example of Descriptive Table: 18/9/2018 SPSS/SITINORYAACOB/SEM2_2014/2015 Example of Descriptive Table:

SPSS/SITINORYAACOB/SEM2_2014/2015 18/9/2018 SPSS/SITINORYAACOB/SEM2_2014/2015 Independent t-test Step 1: Analyze  Compare Means  Independent Sample t-test

SPSS/SITINORYAACOB/SEM2_2014/2015 18/9/2018 SPSS/SITINORYAACOB/SEM2_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

SPSS/SITINORYAACOB/SEM2_2014/2015 18/9/2018 SPSS/SITINORYAACOB/SEM2_2014/2015 Step 4: Click “OK” Step 5: Output

SPSS/SITINORYAACOB/SEM2_2014/2015 18/9/2018 SPSS/SITINORYAACOB/SEM2_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: 18/9/2018 SPSS/SITINORYAACOB/SEM2_2014/2015 Example of t-test table:

SPSS/SITINORYAACOB/SEM2_2014/2015 18/9/2018 SPSS/SITINORYAACOB/SEM2_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

SPSS/SITINORYAACOB/SEM2_2014/2015 18/9/2018 SPSS/SITINORYAACOB/SEM2_2014/2015 Output

SPSS/SITINORYAACOB/SEM2_2014/2015 18/9/2018 SPSS/SITINORYAACOB/SEM2_2014/2015

One way ANOVA- Interpretation 18/9/2018 SPSS/SITINORYAACOB/SEM2_2014/2015 One way ANOVA- Interpretation

SPSS/SITINORYAACOB/SEM2_2014/2015 18/9/2018 SPSS/SITINORYAACOB/SEM2_2014/2015 Pearson Correlation Step 1: Analyze  Correlate  Bivariate..

SPSS/SITINORYAACOB/SEM2_2014/2015 18/9/2018 SPSS/SITINORYAACOB/SEM2_2014/2015 Step 2: Select variables and click into “Variables” box then click “OK”

SPSS/SITINORYAACOB/SEM2_2014/2015 18/9/2018 SPSS/SITINORYAACOB/SEM2_2014/2015 Step 3: Interpret output

Example of Pearson correlation table: 18/9/2018 SPSS/SITINORYAACOB/SEM2_2014/2015 Example of Pearson correlation table:

SPSS/SITINORYAACOB/SEM2_2014/2015 18/9/2018 SPSS/SITINORYAACOB/SEM2_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.

SPSS/SITINORYAACOB/SEM2_2014/2015 18/9/2018 SPSS/SITINORYAACOB/SEM2_2014/2015

SPSS/SITINORYAACOB/SEM2_2014/2015 18/9/2018 SPSS/SITINORYAACOB/SEM2_2014/2015