Phase

Focus Area

Classes

Duration

Phase 1

Foundation & Research Design

Class 1 – 3

Weeks 1–4

Phase 2

Data Management & Descriptive Analysis

Class 4 – 6

Weeks 5–8

Phase 3

Inferential Statistics & Hypothesis Testing

Class 7 – 11

Weeks 9–14

Phase 4

Advanced Analysis & Research Writing

Class 12 – 13

Weeks 15–16

Phase 5

Project Presentation & Certification

Class 14 – 15

Weeks 17–18

Topics Covered

What is research? Types of research (qualitative, quantitative, mixed). Introduction to data analysis. Overview of SPSS interface, menus, and workspace. Installing and setting up SPSS.

Teaching Mode

Lecture + Hands-on Lab

Mini Project

Explore & Navigate SPSS

Task

Open a pre-loaded sample dataset in SPSS. Identify Variable View and Data View. List 5 variables with their types and measurement scales. Take a screenshot of the SPSS workspace and label key components.

Deliverable

Annotated screenshot + variable list (handwritten/typed)

Topics Covered

Formulating research questions & hypotheses. Identifying variables: independent, dependent, control, mediating, moderating. Scales of measurement: nominal, ordinal, interval, ratio. Conceptual framework design.

Teaching Mode

Lecture + Workshop

Mini Project

Design Your Research Framework

Task

Choose a topic of personal/professional interest. Write 1 research objective, 2 research questions, and 2 hypotheses. Identify all variables (IV, DV, control) and their measurement scales. Draw a simple conceptual framework diagram.

Deliverable

1-page research framework document

Topics Covered

Designing effective questionnaires (Likert scale, open/closed-ended). Sampling techniques: probability & non-probability. Data collection methods. Introduction to Google Forms & data entry in SPSS.

Teaching Mode

Lecture + Practical

Mini Project

Build a Survey Instrument

Task

Design a 15-question questionnaire for your research topic (mix of demographics + Likert scale items). Create it in Google Forms. Distribute to at least 20 respondents (classmates/friends). Export responses to Excel/CSV.

Deliverable

Google Form link + collected responses in Excel

Topics Covered

Variable View vs Data View in SPSS. Defining variables: type, label, values, measure. Data entry, importing from Excel/CSV. Data cleaning: finding errors, missing values, outliers. Recoding & computing new variables.

Teaching Mode

Hands-on Lab

Mini Project

Clean & Prepare Your Dataset

Task

Import your survey data (from Class 3) into SPSS. Set up Variable View properly (labels, values, measure). Identify and handle missing values (at least 2 methods). Recode one variable and compute one new variable. Save the clean .sav file.

Deliverable

Clean SPSS dataset (.sav file) + data cleaning log

Topics Covered

Measures of central tendency (mean, median, mode). Measures of dispersion (range, variance, SD). Frequency tables, cross-tabulation. Charts: bar, pie, histogram, boxplot, scatter plot. Interpreting SPSS output.

Teaching Mode

Lecture + Lab

Mini Project

Descriptive Profile Report

Task

Using your own dataset: generate frequency tables for all demographic variables, compute descriptive statistics (mean, SD, min, max) for all Likert-scale variables, create at least 4 charts (bar, pie, histogram, boxplot), and write a 1-page summary interpreting the demographic profile of your respondents.

Deliverable

SPSS output + 1-page written interpretation

Topics Covered

Understanding normal distribution. Normality tests: Shapiro-Wilk, Kolmogorov-Smirnov, skewness, kurtosis. Q-Q plots and histogram inspection. Reliability analysis: Cronbach’s Alpha. Validity concepts overview.

Teaching Mode

Lecture + Lab

Mini Project

Normality & Reliability Check

Task

Run normality tests (Shapiro-Wilk, K-S) on your key variables. Generate Q-Q plots and histograms. Report skewness and kurtosis values. Run Cronbach’s Alpha on each construct/dimension of your questionnaire. Decide which tests (parametric vs non-parametric) are appropriate for your data.

Deliverable

Normality & reliability report with SPSS output tables

Topics Covered

One-sample t-test. Independent samples t-test. Paired samples t-test. Assumptions checking. Interpreting output: t-value, p-value, confidence intervals. Effect size (Cohen’s d). APA-style reporting.

Teaching Mode

Lecture + Lab

Mini Project

Gender/Group Difference Analysis

Task

Using your dataset or a provided dataset: run an independent samples t-test comparing a key variable between two groups (e.g., male vs female satisfaction). Check assumptions (Levene’s test). Calculate Cohen’s d. Write the result in APA format: t(df) = value, p = value, d = value.

Deliverable

SPSS output + APA-formatted results paragraph

Topics Covered

One-way ANOVA: concept, assumptions, interpretation. Post-hoc tests (Tukey, Bonferroni, LSD). Two-way ANOVA (factorial design). Repeated Measures ANOVA. Effect size (Eta squared). APA-style reporting of ANOVA results.

Teaching Mode

Lecture + Lab

Mini Project

Multi-group Comparison Study

Task

Run a one-way ANOVA comparing a continuous variable across 3+ groups (e.g., satisfaction by education level or age group). Perform post-hoc tests to identify which groups differ. Create a means plot. Report in APA format: F(df1, df2) = value, p = value, η² = value. If assumptions are violated, note the alternative.

Deliverable

SPSS output + APA results + means plot

Topics Covered

When to use non-parametric tests. Chi-Square test (goodness of fit & independence). Mann-Whitney U test. Wilcoxon Signed-Rank test. Kruskal-Wallis H test. Friedman test. Interpreting and reporting results.

Teaching Mode

Lecture + Lab

Mini Project

Association & Distribution Analysis

Task

Using your dataset: run a Chi-Square test of independence between two categorical variables (e.g., gender vs preference). Run a Mann-Whitney U test as the non-parametric alternative to the t-test from Class 7. Compare parametric vs non-parametric results. Report both in APA format.

Deliverable

Comparative analysis report (parametric vs non-parametric)

Topics Covered

Pearson correlation (parametric). Spearman rank correlation (non-parametric). Partial correlation. Correlation matrix and interpretation. Scatter plots with regression line. Assumptions and limitations.

Teaching Mode

Lecture + Lab

Mini Project

Correlation Matrix & Interpretation

Task

Generate a Pearson correlation matrix for all continuous variables in your dataset. Create scatter plots for the 3 strongest correlations. Run a partial correlation controlling for one variable. Write a summary: which variables are significantly correlated? What is the direction and strength? Any surprising findings?

Deliverable

Correlation matrix table + scatter plots + interpretation

Topics Covered

Simple linear regression. Multiple linear regression. Assumptions: linearity, normality, multicollinearity (VIF/Tolerance). Model summary: R², adjusted R², ANOVA table. Interpreting coefficients. Stepwise and hierarchical regression. Reporting regression results.

Teaching Mode

Lecture + Lab

Mini Project

Predictive Model Building

Task

Run a multiple regression with your DV and 3–5 IVs. Check all assumptions: multicollinearity (VIF < 5), normality of residuals (P-P plot), homoscedasticity (scatter plot). Report the model: R², F-value, each predictor’s β, t, and p. Identify which predictors are significant. Write findings in APA format.

Deliverable

Regression output + assumption checks + APA write-up

Topics Covered

Exploratory Factor Analysis (EFA): KMO, Bartlett’s test, eigenvalues, scree plot, rotated component matrix. Confirmatory concepts overview. Introduction to mediation and moderation analysis. Process Macro / SPSS Macro for mediation.

Teaching Mode

Lecture + Lab

Mini Project

Factor Structure Discovery

Task

Run EFA on your Likert-scale items. Report KMO value and Bartlett’s test significance. Determine the number of factors using eigenvalues > 1 and scree plot. Present the rotated component matrix. Name each factor based on loaded items. If applicable, run a simple mediation analysis using Process Macro.

Deliverable

EFA output + named factor table + scree plot

Topics Covered

Structure of a research paper/thesis. Writing Introduction, Literature Review, Methodology, Results, Discussion. APA 7th edition formatting for tables and figures. Presenting statistical results in academic writing. Citation and referencing.

Teaching Mode

Lecture + Workshop

Mini Project

Draft Your Results Chapter

Task

Using all your SPSS outputs from Classes 5–12, write a complete Results chapter for your mini research. Include: respondent profile, reliability results, normality assessment, hypothesis testing results (with APA tables and figures). Format everything in APA 7th edition style.

Deliverable

Complete draft Results chapter (3–5 pages)

Topics Covered

Participants present their complete mini research projects. Each project includes: research question, methodology, SPSS analysis, findings, and interpretation. Peer review and instructor feedback. Q&A and troubleshooting.

Teaching Mode

Presentation + Discussion

Mini Project

Final Research Presentation

Task

Prepare and deliver a 10–15 minute presentation of your complete research project covering: Introduction & Research Questions, Methodology (sampling, instrument, data collection), Results (all SPSS analyses with APA tables/figures), Discussion & Conclusion. Respond to peer and instructor questions.

Deliverable

PowerPoint presentation + final research report

Topics Covered

Comprehensive review of all topics. Written certification examination (MCQ + practical SPSS tasks). Result compilation. Certificate distribution ceremony. Course feedback and future learning pathways.

Teaching Mode

Exam + Ceremony

Mini Project

Certification Examination

Task

Part A: 30 MCQs covering research methodology, statistical concepts, SPSS interpretation, and APA formatting (30 marks). Part B: Practical SPSS test - given a raw dataset, perform specified analyses, interpret output, and write results in APA format (45 marks). Submit final polished research report (25 marks).

Deliverable

Exam paper + practical output + final research report

Component

Details

Domain

Education / Social Science

Variables

IV: Social media usage (hours/day, platform type, purpose). DV: Academic performance (CGPA, self-reported grades). Control: Gender, year of study, department.

SPSS Analyses Required

Descriptive statistics, Independent t-test (gender comparison), One-way ANOVA (year-wise comparison), Pearson correlation (usage hours vs CGPA), Multiple regression (predictors of academic performance), Chi-Square (platform preference by gender).

Sample Size & Method

150–200 university students across departments using stratified random sampling.

Research Instrument

30-item structured questionnaire (demographics + 5-point Likert scale items on usage patterns, academic habits, and self-assessed impact).

Component

Details

Domain

Business / Marketing

Variables

IV: Service quality dimensions (SERVQUAL: tangibility, reliability, responsiveness, assurance, empathy). DV: Customer satisfaction, Loyalty intention. Mediator: Perceived value.

SPSS Analyses Required

Descriptive statistics, Reliability analysis (Cronbach’s Alpha per dimension), EFA (factor analysis on service quality items), Correlation matrix, Multiple regression (service quality dimensions → satisfaction), Mediation analysis (perceived value as mediator), Independent t-test (urban vs suburban users).

Sample Size & Method

200–250 active MFS users in Dhaka using convenience sampling.

Research Instrument

35-item questionnaire based on modified SERVQUAL model + satisfaction and loyalty scales.

Component

Details

Domain

HRM / Organizational Behavior

Variables

IV: Salary & benefits, work environment, career growth opportunities, workload, management support. DV: Job satisfaction. Moderator: Teaching experience (years).

SPSS Analyses Required

Descriptive statistics & demographic profiling, Reliability testing, Normality assessment, Independent t-test (satisfaction by gender), One-way ANOVA (satisfaction by experience group), Pearson & Spearman correlation, Hierarchical regression (moderation by experience), EFA on satisfaction dimensions.

Sample Size & Method

120–150 private university teachers across 5–8 universities using purposive sampling.

Research Instrument

40-item questionnaire (demographics + adapted Minnesota Satisfaction Questionnaire + custom items).

Component

Details

Domain

Public Administration / ICT

Variables

IV: Awareness level, digital literacy, trust in government, perceived usefulness, perceived ease of use. DV: E-government service adoption (frequency and range of services used). Control: Age, education, income.

SPSS Analyses Required

Descriptive statistics (awareness levels, usage frequency), Chi-Square (adoption by education level, age group), Mann-Whitney U (adoption by digital literacy: high vs low), Correlation analysis, Multiple regression (predictors of adoption), EFA (on Technology Acceptance Model items), Cross-tabulation with charts.

Sample Size & Method

200+ citizens of Dhaka (diverse age, education, income groups) using quota sampling.

Research Instrument

32-item questionnaire based on modified TAM (Technology Acceptance Model) + awareness and trust scales.