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FMS202Management Sciences2 Unitsintermediate

Business Statistics

This course introduces the basic concepts and principles of statistics and decision-making processes. It covers forms of data, methods of data estimation, summarizing data, and graphical presentation. Students will learn about measures of index numbers, dispersion, correlation, regression analysis, hypothesis tests, and time series analysis. The course also explores distributions of discrete and continuous random variables, equipping students with essential statistical tools for business applications and informed decision-making.

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200h
Study Time
13
Weeks
15h
Per Week
intermediate
Math Level
Course Keywords
StatisticsRegressionCorrelationHypothesis TestingTime Series

Course Overview

Everything you need to know about this course

Course Difficulty

Intermediate Level
Builds on foundational knowledge
65%
intermediate
📊
Math Level
Moderate Math
🔬
Learning Type
Hands-on Practice

Course Topics

Key areas covered in this course

1

Descriptive Statistics

2

Index Numbers

3

Sampling Theory

4

Estimation Theory

5

Correlation Analysis

6

Regression Analysis

7

Hypothesis Testing

8

Time Series Analysis

9

ANOVA

Total Topics9 topics

Requirements

Knowledge and skills recommended for success

Basic Mathematics

Introductory Statistics

💡 Don't have all requirements? Don't worry! Many students successfully complete this course with basic preparation and dedication.

Assessment Methods

How your progress will be evaluated (3 methods)

Assignments

Comprehensive evaluation of course material understanding

Written Assessment

Tutor-Marked Assessments

Comprehensive evaluation of course material understanding

Written Assessment

Final Examination

Comprehensive evaluation of course material understanding

Computer Based Test

Career Opportunities

Explore the career paths this course opens up for you

Business Analyst

Apply your skills in this growing field

Market Research Analyst

Apply your skills in this growing field

Financial Analyst

Apply your skills in this growing field

Data Analyst

Apply your skills in this growing field

Management Consultant

Apply your skills in this growing field

Industry Applications

Real-world sectors where you can apply your knowledge

FinanceMarketingEconomicsManagementHealthcareManufacturing

Study Schedule Beta

A structured 13-week journey through the course content

Week
1

Module 1: Role and Concepts of Statistics

3h

Unit 1: Role of Statistics (Application of Statistics)

3 study hours
  • •Understand the various definitions of statistics.
  • •Describe the uses of statistics in different fields.
  • •Define and differentiate basic statistical concepts such as entity, variable, and population.
  • •Complete Exercise 1.1 to test understanding of the roles of statistics.
Week
2

Module 1: Role and Concepts of Statistics

3h

Unit 2: Measurement of Variables

3 study hours
  • •Define variable and distinguish between quantitative and qualitative variables.
  • •Understand the different scales of measurement: nominal, ordinal, interval, and ratio.
  • •Apply the appropriate measurement scale to different types of data.
  • •Complete the tutor-marked assignment to reinforce understanding of variable measurement.
Week
3

Module 1: Role and Concepts of Statistics

4h

Unit 3: Measurement of Dispersion, Skewness and Kurtosis

4 study hours
  • •Calculate measures of dispersion such as range, quartile deviation, mean deviation, variance, and standard deviation.
  • •Compute the coefficient of variation to compare variability of different data sets.
  • •Determine the skewness and kurtosis of a distribution.
  • •Work through the tutor-marked assignment to apply these measures to a given data set.
Week
4

Module 1: Role and Concepts of Statistics

4h

Unit 4: Decision Analysis and Administration

4 study hours
  • •Understand the administrative and decision-making process.
  • •Apply analytical and creative thinking to problem-solving.
  • •Learn about decision-making under certainty and uncertainty.
  • •Construct a payoff table and analyze decision problems using expected monetary value.
Week
5

Module 2: INDEX NUMBER AND SAMPLING THEORIES

3h

Unit 1: Index Number

3 study hours
  • •Define index numbers and describe their uses.
  • •Understand the different types of index numbers.
  • •Identify the problems encountered in the construction of index numbers.
  • •Calculate index numbers using simple and weighted aggregate methods.
  • •Complete the tutor-marked assignment to practice index number calculations.
Week
6

Module 2: INDEX NUMBER AND SAMPLING THEORIES

3h

Unit 2: Statistical Data

3 study hours
  • •Distinguish between primary and secondary data.
  • •Understand the advantages and disadvantages of each type of data.
  • •Identify various sources of statistical data.
  • •Differentiate between cross-sectional, time-series, and panel data.
Week
7

Module 2: INDEX NUMBER AND SAMPLING THEORIES

4h

Unit 3: Sample and Sampling Theory

4 study hours
  • •Define population, sample, sampling unit, and sampling frame.
  • •Distinguish between probability and non-probability sampling methods.
  • •Understand the different types of probability and non-probability sampling designs.
  • •Discuss the factors affecting the response rate of mail questionnaires.
Week
8

Module 2: INDEX NUMBER AND SAMPLING THEORIES

4h

Unit 4: Estimation Theory

4 study hours
  • •Understand the theory behind estimation.
  • •Apply estimation theory to solve business and economic problems.
  • •Learn about methods of point estimation, including maximum likelihood.
  • •Complete the tutor-marked assignment to practice estimation techniques.
Week
9

Module 3: CORRELATION AND REGRESSION ANALYSIS

3h

Unit 1: Correlation Theory

3 study hours
  • •Define correlation and understand different types of correlation.
  • •Distinguish between positive and negative correlation.
  • •Apply correlation theory to solve business and economic problems.
  • •Complete the tutor-marked assignment to reinforce understanding of correlation types.
Week
10

Module 3: CORRELATION AND REGRESSION ANALYSIS

3h

Unit 2: Pearson's Correlation Co-efficient

3 study hours
  • •Describe the computation of linear correlation coefficients.
  • •Apply the concept of correlations in business decisions.
  • •Calculate Pearson's correlation coefficient for a given data set.
  • •Interpret the results and understand the strength and direction of the relationship.
Week
11

Module 3: CORRELATION AND REGRESSION ANALYSIS

4h

Unit 3: Spearman's Regression Analysis

4 study hours
  • •Explain the computation of rank correlation coefficients.
  • •Apply the concept of correlations in business decisions.
  • •Calculate Spearman's rank correlation coefficient for a given data set.
  • •Interpret the results and understand the strength and direction of the relationship.
Week
12

Module 3: CORRELATION AND REGRESSION ANALYSIS

4h

Unit 4: Ordinary Lease Square Estimation (Regression)

4 study hours
  • •Understand the theory behind regression analysis.
  • •Apply regression analysis to solve business and economic problems.
  • •Learn about simple and multiple regression.
  • •Calculate regression lines using the least squares method.
Week
13

Module 3: CORRELATION AND REGRESSION ANALYSIS

4h

Unit 5: Multiple Regression Analysis

4 study hours
  • •Understand the theory behind multiple regression analysis.
  • •Apply multiple regression analysis to solve business and economic problems.
  • •Learn about non-linear models and linearization.
  • •Complete the tutor-marked assignment to reinforce understanding of multiple regression.

This study schedule is in beta and may not be accurate. Please use it as a guide and consult the course outline for the most accurate information.

Course PDF Material

Read the complete course material as provided by NOUN.

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Study Tips & Exam Preparation

Expert tips to help you succeed in this course

1

Review all tutor-marked assignments (TMAs) and their solutions to understand key concepts and problem-solving techniques.

2

Create concept maps linking statistical concepts from different modules (e.g., Module 2 sampling to Module 4 hypothesis testing).

3

Practice calculating statistical measures (mean, standard deviation, correlation) from various units weekly to build proficiency.

4

Focus on understanding the assumptions and limitations of each statistical test (t-test, F-test, Chi-square) covered in Module 4.

5

Work through example problems from the textbook and study units, focusing on the steps involved in each calculation.

6

Allocate specific study time for each module, prioritizing areas of weakness identified through self-assessment exercises.

7

Practice interpreting statistical results and drawing conclusions in the context of business scenarios.

8

Review key formulas and definitions regularly, creating flashcards for memorization.

9

Simulate exam conditions by completing practice questions within a set time limit to improve time management skills.

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