IGNOU MCS-068 Assignment 2026-27
Predictive Data Analysis
Last updated by IGNOU: 29 Jul 2026. Guide written from the official PDF on 28 Oct 2026, 04:25 pm.
| Course code | MCS-068 |
|---|---|
| Course title | Predictive Data Analysis |
| Programme | Master of Science Data Science and Analytics (MSCDSA)MSCDSA |
| School | School of Computer and Information Sciences |
| Assignment code | MSCDSA (II)/068/Assign/2026-27 |
| Session | July 2026 and January 2027 |
| Maximum marks | 100 |
| Weightage | 30% |
| Last date (June exam) | 30 Apr 2027 |
| Last date (December exam) | 31 Oct 2026 |
| Medium | English |
About the MCS-068 assignment
The MCS-068 assignment covers statistical measures, correlation, forecasting, optimisation, document similarity, regression, classification, clustering and model evaluation. It also tests understanding of data structures in R through numerical problems and explanations.
There are 12 questions worth 80 marks, with another 20 marks reserved for the compulsory viva-voce. Individual questions carry between 5 and 10 marks. Illustrations and diagrams may be used to support explanations, and suitable assumptions may be made where needed.
What the assignment asks
| Question | Marks | Topic |
|---|---|---|
| Q1 | 5 | Calculate quartile deviation from the supplied grouped frequency distribution. |
| Q2 | 5 | Use Kendall’s Tau to assess the association between project complexity rankings and completion-time rankings. |
| Q3 | 5 | Calculate and interpret a three-month simple moving average for the given monthly sales figures. |
| Q4 | 8 | Determine a profit-maximising production plan for two products subject to labour and raw-material limits. |
| Q5 | 7 | Calculate Jaccard similarity between two documents using their shingle-presence matrix. |
| Q6 | 8 | Find the interquartile range of grouped data and assess whether outliers are present. |
| Q7 | 7 | Derive a linear regression equation relating students’ study hours to their marks. |
| Q8 | 10 | Forecast fourth-day sales with the specified ARIMA (1,1,1) model, showing how its components lead to the forecasting equation. |
| Q9 | 8 | Predict a new student’s pass-or-fail outcome from study hours and attendance using KNN with K = 3. |
| Q10 | 7 | Perform two-cluster K-means with the supplied initial centroids and Euclidean distance until convergence, then interpret the final groups. |
| Q11 | 5 | Calculate accuracy, precision, recall, sensitivity, specificity and F1-score from a disease-screening confusion matrix. |
| Q12 | 5 | Explain vectors, lists, matrices, arrays and frames as data structures in R. |
This is a summary of each question. Download the official PDF above for the exact questions and word limits.
How to write and submit it
- Submit the assignment to the Coordinator of your Study Centre by the applicable deadline.
- Timely assignment submission is compulsory for eligibility to appear in the corresponding term-end examination.
- Attend the compulsory assignment viva-voce; submitting the assignment without attending the viva results in zero marks and unsuccessful completion.
- Follow the assignment guidelines in the MSCDSA Programme Guide.
- You may include illustrations and diagrams to support your explanations.
- Make suitable assumptions where necessary.
Submission dates: 30 April 2027 (June term-end exam; January 2027 session); 31 October 2026 (December term-end exam; July 2026 session).
Frequently asked questions
What is the assignment code for MCS-068 in the 2026-27 session?
The course page prints the assignment code as MSCDSA (II)/068/Assign/2026-27.
What are the submission deadlines for MCS-068?
The deadline is 31 October 2026 for the July 2026 session and December term-end exam, and 30 April 2027 for the January 2027 session and June term-end exam.
How many questions are there, and how are marks distributed?
There are 12 questions carrying 80 marks in total. The remaining 20 marks are for viva-voce, making the maximum 100 marks.
Is the MCS-068 assignment viva compulsory?
Yes. If you submit the assignment but do not attend the viva-voce, the assignment is treated as unsuccessfully completed and receives zero marks.
What is the weightage of the MCS-068 assignment?
The assignment has a weightage of 30%.
Where should I submit the MCS-068 assignment?
Submit it to the Coordinator of your Study Centre on or before the relevant deadline.
Other IGNOU MSCDSA assignments
- MCS-061: Mathematical Foundations-I
- MCS-066: Mathematical Foundations for Data Science-II
- MCS-067: Data Wrangling and Visualization
- MCS-207: Database Management Systems
- MCS-224: Artificial Intelligence & Machine Learning
- MCSL-069: Artificial Intelligence & Machine Learning Lab
- MCSL-070: Data Analysis Lab
Assignment details and PDFs come from IGNOU's official website; the guide is a summary of the official PDF. Always check the latest instructions and last dates on ignou.ac.in or with your Regional Centre before submitting.