Business Statistics

Course Title: Business Statistics

Course No: STT 201

Nature of the Course: Theory + Lab

Semester: 3

Full Marks: 60 + 40

Pass Marks: 0 + 0

Credit Hours: 3

Course Description

Statistics in business and management, describing data using graphs and tables. Numerical measures: central tendency, dispersion, skewness and kurtosis. Probability: laws of probability, conditional probability. Probability distribution: discrete probability distribution and continuous probability distribution. Sampling theory: sampling techniques, sampling and non-sampling errors. Estimation: point and interval estimates. Hypothesis testing: test of significance for large samples. Linear correlation and regression.

Course Objectives

The principal objective of Business Statistics is for students to describe data and make evidence based business decisions making using descriptive and inferential statistics that are based on well-reasoned statistical arguments. The course will cover the basic tools used to describe data for the purposes of transforming data into information. In addition, the course will present the fundamentals of statistical inference showing how it is possible to examine a small subset of data to reach conclusions about the larger set of data. The statistical tools should be introduced from an applied perspective using business related examples. Microsoft Excel software will be used throughout the course to aid in statistical analysis.

Course Contents

1. Describing Data using Graphs and Tables

4 hrs

1.1. Uses and scope of statistics in business and management

1.2. Frequency distribution

1.3. Stem-and-leaf plots

1.4. Diagrams

Simple bar diagram

Sub-divided bar diagram

Multiple bar diagram

Pie-chart

1.5. Graphical presentation of frequency distribution

Histogram

Ogive curve

1.6. Problems using Excel

2. Describing Data Using Numerical Measures

9 hrs

2.1. Measures of central tendency

Mean, Median and Mode

Partition values (Quartiles, Deciles and Percentiles)

2.2. Measures of variation

Range, Inter Quartile Range, Quartile deviations, Standard deviation

2.3. Variance and Coefficient of Variation

2.4. Measurement of skewness

Karl Pearson coefficient of skewness

Bowley coefficient of skewness

2.5. Measurement of kurtosis (Percentile coefficient of kurtosis)

2.6. Five number summery, Box-and-Whisker plot

2.7. Problems using Excel

3. Simple Linear Correlation Analysis

5 hrs

3.1. Introduction

3.2. Scatter plot

3.3. Karl Pearson's correlation coefficient including bi-variate frequency distribution

3.4. Coefficient of determination

3.5. Test of significance of sample correlation coefficient using probable error

3.6. Spearman's rank correlation coefficient

3.7. Problems using Excel

4. Simple Linear Regression Analysis

4 hrs

4.1. Introduction

4.2. Simple linear regression models

4.3. Assumptions of linear regression model

4.4. Line of best fit, Linear regression model by least-squares method

4.5. Interpretation of regression coefficients

4.6. Properties of regression coefficient

4.7. Regression coefficient for bi-variate frequency distribution

4.8. Problems using Excel

5. Probability

4 hrs

5.1. Introduction

5.2. Sample space and events

5.3. Probability

5.4. Laws of probability

5.5. Conditional probability

5.6. Problems using Excel

6. Probability Distributions

6 hrs

6.1. Introduction

6.2. Discrete probability distribution

Binomial distribution

Poisson distribution

6.3. Continuous probability distribution

Normal distribution

6.4. Problems using Excel

7. Sampling Theory

3 hrs

7.1. Introduction

7.2. Population and sample

7.3. Objectives of sampling

7.4. Sampling techniques

7.5. Sampling and non-sampling errors

7.6. Standard error

7.7. Concept of central limit theorem

8. Estimation

6 hrs

8.1. Introduction

8.2. Properties of good estimator

Consistency

Unbiasedness

Efficiency and Sufficiency

8.3. Point and interval estimates

8.4. Level of confidence

8.5. Confidence interval estimates for mean and proportion

8.6. Determination of sample size for mean and proportion

8.7. Problems using Excel

9. Introduction to Hypothesis Testing

7 hrs

9.1. Introduction

9.2. Steps of hypothesis testing

9.3. Level of significance

9.4. Critical region

9.5. One tailed test and two tailed test

9.6. Hypothesis testing using critical value and p-value approaches

9.7. Test of significance for large samples (Z-test)

Test of significance of a single mean and difference between two means

Test of significance of a single proportion and difference between two proportions

9.8. Problems using Excel

Text Books

1.Davis, G. and B. Pecar. Business Statistics using EXCEL, Oxford University Press.
2.Levine, D.V., D.F. Stephan and K. A. Szabat. Statistics for managers using MS excel, Pearson.
3.Linda, H. and F. John. Applied Statistics for Business and Management using Microsoft Excel, Springer.
4.Trevor, W. Applied Statistics: Methods and Excel-Based Application, JUTA Academics.

Notes:

This syllabus follows the official BIM curriculum of Tribhuvan University. In case of any doubt or revision, the university’s published syllabus shall be considered authoritative.https://www.fomecd.edu.np/syllabuses

Business Statistics

Business Statistics

Select University

Select Program

TabFlux . Business Statistics . TU . BIM