Certificate Course in SPSS

Objectives of the Course

  • To gain proficiency in entering research data accurately into SPSS 
  • To develop skills to explore and summarize research data using descriptive statistics, frequency distributions, and graphical representations to gain insights into the dataset’s characteristics.
  • To learn a variety of statistical techniques available in SPSS,
  • To enhance your ability to interpret statistical output generated by SPSS, 



Students pursuing bachelors, masters or higher degrees in the field of Behavioural Sciences and allied fields.

Learning Outcomes:

1. Continuous Evaluation via Quizzes, Practical Work

2. Globally Verified Certificate from We Avec U & Accredited bodies

3. Student-Friendly Timings

4. One Year access to resource material

5. Session Recording available for 1 year

Classes Conduction:

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  • Module 1: Introduction to Statistics

    ● Statistics: definition, functions and uses in research
    ● Basic concepts: Population, Sample, Variables; Frequency distributions
    ● Graphical representation – Bar graph, Pie chart, Line graphs, Histogram, Frequency
    polygon, Frequency curve, Ogive.

  • Module 2: Descriptive Statistics

    ● Measures of Central Tendency: mean, median, mode – calculation, interpretation, uses
    ● Measures of Variability: Range, Quartile Deviation, Average Deviation, Variance,
    Standard Deviation – calculation, interpretation, uses
    ● The Normal Curve: characteristics, applications
    ● Skewness, Kurtosis.

  • Module 3: Inferential Statistics

    ● Hypothesis/Significance Testing
    ● Errors in Significance Testing
    ● Measuring Statistical Significance: Variance, Standard Deviation, Standard Error,
    ● Application and Inferences of difference between two means: t-test – Independent
    samples t-test, Paired samples t-test; Analysis of Variance (ANOVA).

  • Module 4: Correlation and Regression Statistics

    ● Correlation and correlation coefficient
    ● Scatter plot
    ● Correlation methods: Pearson’s correlation, and Spearman’s rank correlation –
    Assumptions and Calculation
    ● Overview of Regression analysis: Linear Regression, Multiple Linear Regression,
    Logistic Regression.

  • Module 5: Non-parametric Statistics

    ● Difference between parametric and non-parametric statistics
    ● Assumptions for non-parametric techniques
    ● Types of Non-parametric tests: Chi-square test, McNemar’s test, Mann-Whitney U test,
    Wilcoxon Signed Rank test, Kruskal-Wallis test, Friedman’s test.

  • Module 6: Factor Analysis
    • Introduction to factor analysis and its applications in research
    • Understanding the underlying principles and assumptions of factor analysis
    • Exploring different types of factor analysis techniques (e.g., exploratory vs. confirmatory)
    • Hands-on practice with SPSS software for conducting factor analysis
  • Module 7: Research Analysis
    • Data Collection and Preliminary Analysis
    • Preparing the data file; Creating a data file and entering data
    • Screening and cleaning the data
    • Tests of Normality
    • Reliability Screening
    • Performing Statistical Analysis
    • Inferring Results


Holistic approach towards psychological and educational needs

Internationally & Nationally accredited Courses

Different types and modalities of therapies.

Experienced and Qualified Facilitators and Staff

Hands-on Practical Exposure with One to One Emphasis

Queer affirmative and trauma informed psychologists


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