Business Statistics I
- Management Sciences
- 200 level
- 3 credit units
- 230 pages
- 16 units
This course introduces students to the fundamental concepts and principles of business statistics. It covers data collection methods, summarizing and presenting data, and measures of central tendency and dispersion. Students will also learn about set theory, permutations, combinations, and basic probability concepts. The course further explores probability distributions of discrete and continuous random variables, equipping students with essential tools for decision-making in business contexts.
About this course
- Difficulty
- Beginner
- Study hours
- 156 hours
- Maths
- Intermediate
- Content
- Theoretical, problem solving
- Practical work
- No
- Assignments
- Tutor Marked Assignments
- Final Examination
What you'll read
The real module and unit structure of SMS201, taken from the course material NOUN publishes.
- UNIT 1: STATISTICS AND DECISION MAKING PROCESS
- UNIT 2: DATA: NATURE, SOURCE AND METHODS OF COLLECTION
- UNIT 4: GRAPHICAL PRESENTATION OF DATA
- UNIT 5: MEASURE OF CENTRAL TENDENCY I
- UNIT 6
- Unit 7: MEASUREMENT OF CENTRAL TENDENCY 3 - MEDIAN AND MODE
- UNIT 8: FRACTILES, SKEWNESS AND KURTOSIS
- UNIT 9: MEASURES OF DISPERSION
- UNIT 10: SET THEORY
- UNIT 11: PERMUTATIONS AND COMBINATIONS
- Unit 12: SOME ELEMENTARY PROBABILITY CONCEPTS
- UNIT 13: PROBABILITY RULE, EVENTS AND BAYES' THEOREM
- UNIT 14 PROBABILITY DISTRIBUTION OF A DISCRETE RANDOM VARIABLE
- UNIT 15
- UNIT 17
- UNIT 18: NORMAL DISTRIBUTION
One paragraph, so you can see how it reads
SMS201 · UNIT 1: STATISTICS AND DECISION MAKING PROCESS
From all these definitions, you will realize that statistics are concerned with numerical data.. Examples of such numerical data are the heights and weights of pupils in a primary school when evaluating the nutritional well being of the pupils and the accident fatalities on a particular road for a period of time.
What you should be able to do
- Explain the nature and types of statistical data.
- Apply appropriate methods for collecting and summarizing data.
- Calculate measures of central tendency and dispersion.
- Apply set theory, permutations, and combinations to solve problems.
- Calculate probabilities of events using various rules and theorems.
- Apply probability distributions to model and analyze business scenarios.
What it prepares you for
- Business Analyst
- Market Researcher
- Data Entry Clerk
- Financial Analyst
- Operations Manager
- Finance
- Marketing
- Operations
- Human Resources
- Economics
Where it gets hard
The units students slow down on, and what makes each one heavy.
- Module 2: Measures of Central Tendency and Dispersion
Unit 9: Measures of Dispersion
The computation of standard deviation for grouped data involves multiple steps and formulas, requiring careful attention to detail and a strong understanding of algebraic manipulation.
- Module 3: Elementary Probability Concepts
Unit 13: Probability Rules, Events and Bayes' Theorem
Bayes' Theorem requires understanding conditional probability and applying a complex formula, making it challenging to grasp and apply correctly.
A suggested way through it
13 weeks, about 26 hours in total. Yours will differ.
- Week 1Module 1: Introduction to Statistics
Unit 1: Statistics and Decision Making Process · 2 hours
Read the introduction to statistics and decision making.. Understand the definitions of statistics.. Describe the uses of statistics in various fields.. Define basic statistical concepts such as entity, variable, and population..
- Week 2Module 1: Introduction to Statistics
Unit 2: Nature, Source and Method of Data Collection · 2 hours
Differentiate between primary and secondary data.. Identify sources of micro and macro statistical information.. Describe methods of data collection including surveys, observation, interviewing, and questionnaires.. Complete Student Assessment Exercise 2.1, 2.2, and 2.3.
- Week 3Module 1: Introduction to Statistics
Unit 3: Summarizing Data · 2 hours
Arrange unordered data in ordered form.. Prepare frequency distributions for grouped and ungrouped data.. Construct relative frequency and cumulative relative frequency distributions.. Complete Student Assessments Exercise 3.1.
- Week 4Module 1: Introduction to Statistics
Unit 4: Graphical Presentation of Data · 2 hours
Graph frequency distributions using histograms, frequency polygons, and ogives.. Construct simple, component, and multiple bar charts.. Draw pie charts to represent data.. Complete Exercise 4.1.
- Week 5Module 2: Measures of Central Tendency and Dispersion
Unit 5: Measures of Central Tendency 1 - The Arithmetic Mean · 2 hours
Compute the arithmetic mean of grouped and ungrouped data.. List the properties, advantages, and disadvantages of the arithmetic mean.. Compute weighted mean for data sets.. Complete Exercise 5.1.
- Week 6Module 2: Measures of Central Tendency and Dispersion
Unit 6: Measures of Central Tendency 2 - Geometric Mean and Harmonic Mean · 2 hours
Compute geometric mean for a set of values.. Compute harmonic mean for a set of values.. List the uses of geometric and harmonic means.. Complete Exercise 6.1 and 6.2.
- Week 7Module 2: Measures of Central Tendency and Dispersion
Unit 7: Measures of Central Tendency 3 - Median and Mode · 2 hours
Compute the median for both ungrouped and grouped data.. Estimate the median from the cumulative frequency curve.. Compute the mode for both ungrouped and grouped data.. Estimate the mode from a histogram.. List the advantages and disadvantages of median and mode.. Complete Exercise 7.1 and 7.2.
- Week 8Module 2: Measures of Central Tendency and Dispersion
Unit 8: Fractiles, Skewness and Kurtosis · 2 hours
Compute different types of fractiles in a distribution.. Describe different types of skewness.. Compute the degree of skewness in a distribution.. Locate the relative positions of mode, median, and mean in a distribution.. Explain measures of Kurtosis of a distribution.. Complete Exercise 8.1 and 8.2.
- Week 9Module 2: Measures of Central Tendency and Dispersion
Unit 9: Measures of Dispersion · 2 hours
Compute the range for a distribution.. Compute the semi-interquartile range for a distribution.. Compute mean deviation for a distribution.. Compute standard deviation for a distribution.. Compute the coefficient of variation.. Complete Exercise 9.1 and 9.2.
- Week 10Module 3: Elementary Probability Concepts
Unit 10: Set Theory · 2 hours
Understand set and the basic concepts in set theory.. Perform basic operations in set theory.. Use Venn Diagrams to solve problems involving set theory.. Complete Student Assessment Exercise 10.1.
- Week 11Module 3: Elementary Probability Concepts
Unit 11: Permutations and Combinations · 2 hours
Compute factorials of values.. Compute permutations for objects that are different.. Compute permutations for objects that are not all different.. Compute values of combinations for objects.. Complete Student Assessment Exercise 11.1 and 11.2.
- Week 12Module 3: Elementary Probability Concepts
Unit 12: Some Elementary Probability Concepts · 2 hours
Understand different views of probability.. Understand elementary properties of probability.. Compute the probability of an event.. Complete Student Assessment Exercise 12.1.
- Week 13Module 3: Elementary Probability Concepts
Unit 13: Probability Rules, Events and Bayes' Theorem · 2 hours
Understand the addition and multiplication rules in probability.. Explain independent and complimentary events.. Solve problems involving joint probability.. Apply Bayes' Theorem to solving questions involving probability.. Complete Exercise 13.1 and 13.2.
Preparing for the exam
- Review all definitions and formulas from Units 5-9 related to measures of central tendency and dispersion.
- Practice solving problems involving permutations and combinations from Unit 11, focusing on application to real-world scenarios.
- Create flashcards for probability rules and theorems covered in Unit 13, including addition rule, multiplication rule, and Bayes' Theorem.
- Work through all Student Assessment Exercises (SAEs) in each unit, paying close attention to areas where you struggled.
- Dedicate extra time to understanding the application of probability distributions (Units 14-18) by working through additional examples from textbooks.
- Create concept maps linking Units 3-4 data summarization and graphical presentation techniques to measures of central tendency and dispersion.
- Practice applying set theory operations (Unit 10) to solve probability problems involving mutually exclusive and non-mutually exclusive events.
Questions students ask about this course
What is SMS201 about?
This course introduces students to the fundamental concepts and principles of business statistics. It covers data collection methods, summarizing and presenting data, and measures of central tendency and dispersion. Students will also learn about set theory, permutations, combinations, and basic probability concepts. The course further explores probability distributions of discrete and continuous random variables, equipping students with essential tools for decision-making in business contexts.
How many units does SMS201 have?
SMS201, Business Statistics I, has 16 units across 1 module, over 230 pages of course material. You can read it one unit at a time.
How many credit units is SMS201?
SMS201 carries 3 credit units, at 200 level in Management Sciences.
Is SMS201 hard?
SMS201 is rated beginner level, with intermediate mathematical content. It is mostly theoretical and problem solving work.
How long does SMS201 take to study?
About 156 hours of study, spread across its 16 units.
How is SMS201 assessed?
SMS201 is assessed by Assignments, Tutor Marked Assignments and Final Examination.
What can I do with SMS201?
Business Analyst, Market Researcher, Data Entry Clerk, Financial Analyst and Operations Manager.