Coming soon
Statistical Analysis using Software
This course aims to equip students with practical statistical analysis skills using MS Excel and SPSS. By integrating statistical concepts with hands-on data analysis, students will develop data- driven decision-making abilities essential for business and research
|
Course |
Learning outcomes (at course level) |
Learning and teaching strategies |
Assessment Strategies |
|
|
Course Code |
Course Title |
|||
|
25VBBA 201 |
Statistical Analysis using Software (Practical) |
CO:Organize, manage, and prepare datasets efficiently in MS Excel and SPSS for statistical processing. CO:Construct and analyze frequency tables and graphical representations to summarize datasets using Excel and SPSS. CO: Utilize Excel’s built-in functions and SPSS tools to perform descriptive statistical analysis and generate meaningful insights. CO: Conduct correlation analysis in Excel and SPSS, interpret correlation coefficients, and draw conclusions for business and research applications. CO: Interpret regression output, assess model accuracy, and apply regression analysis for real- world business and research scenarios using MS Excel and SPSS. CO: Contribute effectively in course-specific interaction. |
Approach in teaching: Interactive sessions, Case Study Discussions, Tutorials, Reading assignments.
Learning activities for the students: Self-learning assignments, Solving question-based problems, Project tasks |
Continuous Assessment Test, Semester End Examination, Quiz, Solving problems in tutorials, Assignment, Presentation, Individual and group projects, Project file and Viva-voce |
Overview of MS Excel and SPSS for statistical analysis, Data types, measurement scales, and data entry in Excel & SPSS, Creating and managing datasets
Construction of frequency tables in Excel & SPSS, Graphical representation of data: Bar charts, Pie charts, Histograms, Box plots and Scatterplots, Line graphs and Trend analysis, Formatting and customizing graphs for reports
Measures of central tendency: Mean, Median, Mode, Measures of dispersion: Range, Variance, Standard Deviation, Coefficient of Variation, Using MS Excel: Built-in statistical functions, Data Analysis ToolPak, Using SPSS: Descriptive Statistics, Explore function, Frequencies
Understanding correlation: Types & Interpretation, Methods of correlation: Pearson’s correlation coefficient, Spearman’s rank correlation, Using MS Excel: Correlation matrix, Data Analysis ToolPak, Using SPSS: Bivariate correlation analysis, Correlation coefficient interpretation
Introduction to Regression Analysis, Simple Linear Regression: Model building, Interpretation, and Business Applications, Using MS Excel: Regression modelling with Data Analysis ToolPak, Using SPSS: Running regression models, Practical case studies using real-world business datasets
1. Albright, S. C., Winston, W. L., & Zappe, C. J. (2022). Data analysis and decision making with Microsoft Excel (7th ed.). Cengage Learning.
2. Field, A. (2018). Discovering statistics using IBM SPSS statistics (5th ed.). SAGE Publications.
3. Keller, G. (2022). Statistics for management and economics (12th ed.). Cengage Learning.
1. Black, K. (2019). Business statistics: For contemporary decision making (10th ed.). Wiley.
2. Levin, R. I., & Rubin, D. S. (2021). Statistics for management (8th ed.). Pearson.
3. Berenson, M. L., Levine, D. M., & Szabat, K. A. (2019). Basic business statistics: Concepts and applications (14th ed.). Pearson.
E-Resources
1. https://openstax.org/books/introductory-business-statistics/pages/1-intr...
2. https://learn.microsoft.com/en-us/training/paths/analyze-data-excel/
3. https://www.ibm.com/docs/en/spss-statistics
