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MPSE-3 IGNOU Solved Assignment 2026-27
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MPSE-3 IGNOU Solved Assignment 2026-27

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This MPSE-3 IGNOU Tutor Marked Assignment (TMA) provides verified solutions for the Master of Arts (Psychology) Degree Programme, strictly adhering to the 2026-27 academic session guidelines. Solutions are formatted within prescribed word limits (500/250/100 words) and align with IGNOU’s official course curriculum for Psychological Statistics and Research Methods.

Syllabus & Overview

MPSE-3: Psychological Statistics and Research Methods Solved Assignment (TMA) Overview

The MPSE-3 TMA focuses on statistical analysis, research methodology, and psychological measurement as per the IGNOU MA Psychology curriculum. Below are verified solutions for key units, structured to meet 30% course weightage and plagiarism-free compliance.

Unit 1: Introduction to Psychological Statistics

This unit covers the fundamentals of descriptive and inferential statistics, including measures of central tendency, dispersion, and probability theory. The TMA requires solving problems on mean, median, mode, standard deviation, and hypothesis testing (e.g., t-tests, ANOVA).

  • Sample Solution: Calculate the mean and standard deviation for a dataset of psychological test scores (e.g., IQ scores of 100, 110, 95, 120).
  • Word Limit: 500 words for theoretical explanations + 250 words for numerical problems.

Unit 2: Research Design and Methodology

This block emphasizes experimental vs. non-experimental designs, sampling techniques, and ethical considerations in psychological research. The TMA includes critiquing research studies and designing a hypothetical experiment (e.g., testing the effect of sleep deprivation on memory retention).

  • Key Focus: Differentiate between correlational, quasi-experimental, and true experimental designs.
  • Submission Requirement: 250-word critique of a published study + 100-word experimental design outline.

Unit 3: Data Collection and Measurement

Covers psychometric scales (Likert, semantic differential), reliability, and validity in psychological instruments. The TMA requires analyzing a sample questionnaire (e.g., assessing anxiety levels) for face validity and internal consistency.

  • Example Task: Evaluate a 5-point Likert scale for measuring job satisfaction (e.g., 'I enjoy my work').
  • Note: Use : Kuder-Richardson Formula 20 for reliability analysis.

Unit 4: Statistical Software Applications

Introduces SPSS/Python basics for data analysis. The TMA includes interpreting output (e.g., regression analysis, chi-square tests) from provided datasets. Solutions must explain statistical significance (p-value) and effect size (Cohen’s d).

  • Critical Tip: Cite : SPSS syntax commands (e.g., `FREQUENCIES`, `REGRESSION`) in answers.

Unit 5: Advanced Topics in Psychological Research

Discusses meta-analysis, longitudinal studies, and mixed-methods research. The TMA requires a comparative analysis of two studies (e.g., cross-sectional vs. longitudinal designs in developmental psychology).

  • FAQ: Q: How do I cite sources in the TMA?: A: Use APA 7th edition for all references, including IGNOU study materials and peer-reviewed journals.
  • FAQ: Q: Are calculators allowed for numerical problems?: A: No—solutions must show step-by-step manual calculations (e.g., z-score formula).

Submission Deadlines & Format

The TMA must be submitted digitally via IGNOU’s eGyanKosh portal within the academic session deadline (check IGNOU’s official website). Use 12pt Times New Roman font, 1.5 line spacing, and page numbers. Attach a cover page with your enrollment number and course details.

Word Limits (Strict Compliance)

  • Theoretical questions: 500 words (excluding references).
  • Numerical problems: 250 words (show all work).
  • Short-answer questions: 100 words max.

Note: Plagiarism detection (Turnitin) is mandatory—ensure 100% originality with proper citations.

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By purchasing this item, you agree to our standard academic license terms. You may use this product for personal study, but you may not resell or redistribute the files online.

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