The document outlines the course structure for CSC1108 - System Analysis & Design, focusing on activity planning, project control tools such as Gantt charts and PERT diagrams, and the information requirements analysis process. It details sampling techniques and methods to investigate data, including interviews, questionnaires, and observations, and explains descriptive and inferential statistics used in data analysis. Students are expected to apply these concepts through class activities and scenarios related to healthcare and retail inventory management.

1. Course: CSC1108 - System Analysis & Design
Semester: January 2024
Lecturer: Ms Jayashiry Morgan

2. Recap: • Activity Planning
• Control
• Two tools for Project Planning and
Control:
 Gantt Chart
 PERT diagram
• Tasks involved in the project:
 Task Identification
 Task Sequencing
 Estimation of Time and Resources
 Task Assignment
 Schedule Development
 Monitoring and Tracking
 Adjustments and Fine-tuning

3. Chapter 7:
Information Requirements Analysis:
Sampling And Investigating Data

4. Learning Outcome
By end of this session, students should be able to explain:
• The importance of information requirements analysis in the system
development life cycle,
• Various sampling techniques,
• Process of investigating data through interviews, questionnaires,
and observation methods
• Descriptive statistics and inferential statistics.

5. Information Requirement Analysis
• is the process of determining the data and information needs of an
organization or system to support its goals and objectives.
• This involves identifying and defining the type, format, and content of the
data and information required, as well as the sources of this information.
• Purpose:
 to provide a comprehensive understanding of the information that
is necessary to support the goals and objectives of a system,
organization, or process
 to ensure that all necessary information is available, accurate, and
accessible.

6. Process of Information Requirements
Analysis Includes:
• Identifying stakeholders
• Defining the business requirements
• Determining the data sources
• Evaluating the existing data
• Defining data and information requirements
• Designing the information architecture
• Validation and verification

7. Information Requirement Analysis
• Sampling
• Investigating Data

8. Sampling Technique
• Random Sampling
• Stratified Sampling
• Cluster Sampling
• Convenience Sampling

9. Sampling Technique
• Random Sampling
• Stratified Sampling
• Cluster Sampling
• Convenience Sampling

10. #1 Random Sampling
• Involves selecting a sample from a population in such a way that each
member of the population has an equal chance of being selected.
• This technique helps in avoiding biases and ensures that the sample is
representative of the entire population.
• Example: Simple random sampling, systematic sampling, and stratified
random sampling.

11. Sampling Technique
• Random Sampling
• Stratified Sampling
• Cluster Sampling
• Convenience Sampling

12. #2 Stratified Sampling
• In stratified sampling, the population is divided into subgroups or strata
based on certain characteristics.
• Samples are then randomly selected from each stratum proportionate to
its size in the population.
• This method ensures representation from all segments of the population,
making it useful when there are significant variations within the
population.

13. Sampling Technique
• Random Sampling
• Stratified Sampling
• Cluster Sampling
• Convenience Sampling

14. #3 Cluster Sampling
• Involves dividing the population into clusters or groups.
• A random sample of clusters is then selected, and data is collected from
all elements within the chosen clusters.
• This technique is advantageous when it is difficult to obtain a complete
list of the population but relatively easy to access clusters.

15. Sampling Technique
• Random Sampling
• Stratified Sampling
• Cluster Sampling
• Convenience Sampling

16. #4 Convenience Sampling
• Involves selecting subjects based on their easy availability and
accessibility to the researcher.
• While this method is convenient, it may introduce bias into the sample,
as it does not ensure representative selection from the population.

17. Types Of Sampling Techniques
Watch this video: Click Here

18. Investigating Data
• Interview
• Questionnaires
• Observation

19. Investigating Data
• Interview
• Questionnaires
• Observation

20. #1 Interview
• Interviews are structured conversations conducted with stakeholders, users,
and subject matter experts to gather information about their requirements
and preferences.
• Open-ended questions allow for detailed responses, while closed-ended
questions can be used for specific data gathering.
• Interview techniques such as structured interviews, semi-structured
interviews, and unstructured interviews can be employed based on the
information needed and the nature of the stakeholders.

21. Investigating Data
• Interview
• Questionnaires
• Observation

22. #2 Questionnaires
• Questionnaires are written instruments containing a series of questions
designed to gather specific information from respondents.
• They can be administered in person, through mail, or electronically,
depending on the target audience.
• Closed-ended questions provide quantifiable data, while open-ended
questions allow for more detailed responses.

23. Investigating Data
• Interview
• Questionnaires
• Observation

24. #3 Observation
• Observation involves directly observing users or processes in their natural
environment to understand their behaviors, interactions, and
requirements.
• This method provides firsthand insights into how tasks are performed and
can uncover implicit requirements that may not be articulated through
interviews or questionnaires.

25. Data Analysis Techniques
• Descriptive Statistics
• Inferential Statistics

26. Data Analysis Techniques
• Descriptive Statistics
• Inferential Statistics

27. Descriptive Statistics
• Descriptive statistics, such as mean, median, mode, standard deviation,
and variance, are used to summarize and describe the characteristics
of a dataset.
• These statistics provide valuable insights into the central tendency,
dispersion, and distribution of the data.

28. Data Analysis Techniques
• Descriptive Statistics
• Inferential Statistics

29. Inferential Statistics
• Inferential statistics involve making inferences or predictions about a
population based on sample data.
• Techniques such as hypothesis testing, regression analysis, and analysis
of variance (ANOVA) are used to draw conclusions and make
generalizations about the population.

30. Conclusion
Information requirements analysis through sampling and investigating
data is essential for understanding the needs of stakeholders and
defining the data requirements of a system accurately.

31. Watch
Watch this video: Click Here

32. Class Activity 1: Discussion
1. Divide into 2 groups.
2. Each group will be given a scenario.
3. Answer to the questions based on the scenario given to each group.
4. You will discuss about your findings to the other group, and vice versa.
Time given to prepare: 15 minutes
Discussion time: 10 minutes

33. Scenario #1
You are a data analyst hired by a healthcare
organization to improve patient care services
through the implementation of a new
electronic health record (EHR) system. Your
task is to conduct information requirements
analysis to understand the data needs of
healthcare providers, administrative staff,
and patients.
Question: As the appointed data analyst for
the healthcare organization, outline your plan
for sampling and investigating data to gather
crucial information for the development of
the new electronic health record (EHR)
system.
Scenario #2
You are a consultant working with a retail
chain to enhance their inventory
management system. The company is
experiencing issues with stockouts and
overstocking, leading to revenue loss and
inefficient operations. As part of your
consulting project, you need to conduct
information requirements analysis to
understand the data needs for improving
inventory management.
Question: As the consultant tasked with
improving the inventory management system
for the retail chain, outline your plan for
sampling and investigating data to gather
essential information for system
enhancement.