The "Statistics for Business Decisions" subject in the Bachelor of Management Studies (BMS) program for Semester 1 focuses on equipping students with fundamental statistical tools and techniques to support decision-making in business environments. The course typically includes:

1. Introduction to Business Statistics: Understanding the role and importance of statistics in business, different types of data, and the relevance of statistical methods in real-world business scenarios.

2. Descriptive Statistics: Learning methods to summarize and describe business data using measures of central tendency (mean, median, mode) and measures of dispersion (range, variance, standard deviation).

3. Data Presentation: Techniques for effectively presenting data through tables, charts, and graphs, aiding in visual analysis and interpretation.

4. Probability and Probability Distributions: Basics of probability theory, including concepts like random variables, probability distributions (binomial, Poisson, and normal), and their applications in business decision-making.

5. Sampling and Estimation: Introduction to sampling methods, and how to use sample data to make estimates about larger populations. Understanding concepts like confidence intervals and margins of error.

6. Hypothesis Testing: Applying statistical tests to validate assumptions or claims about business data, using techniques such as Z-tests, t-tests, and chi-square tests.

7. Correlation and Regression Analysis: Examining relationships between variables using correlation coefficients and simple linear regression models, helping businesses to understand trends and predict future outcomes.

8. Decision-Making under Uncertainty: Using statistical tools like decision trees and payoff matrices to make informed business decisions when outcomes are uncertain.

This subject provides a foundation for data-driven decision-making, enabling students to analyze business situations quantitatively and make evidence-based recommendations.