Business Statistics Ii
- Management Sciences
- 200 level
- 3 credit units
- 171 pages
- 18 units
This course introduces the basic concepts and principles of statistics in a business context. It covers data collection methods, summarizing data, graphical presentations, and measures of index numbers and dispersion. Students will learn correlation and regression analysis, hypothesis testing, and time series analysis. The course also explores distributions of discrete and continuous random variables, providing a foundation for informed decision-making in business environments.
About this course
- Difficulty
- Intermediate
- Study hours
- 156 hours
- Maths
- Intermediate
- Content
- Theoretical, problem solving, case study
- Practical work
- No
- Assignments
- Tutor marked assessments
- Final examination
What you'll read
The real module and unit structure of SMS202, taken from the course material NOUN publishes.
One paragraph, so you can see how it reads
SMS202 · UNIT 1: ROLE OF STATISTICS (APPLICATION OF STATISTICS)
In this unit you have learned a number of important issues that relate to the meaning and roles of statistics. The various definitions and examples of concepts given in this unit will assist tremendously in the studying of the units to follow.
What you should be able to do
- Apply statistical techniques to business problems
- Interpret statistical data for decision-making
- Perform regression and correlation analyses
- Conduct hypothesis tests
- Analyze time series data
- Use statistical software for data analysis
What it prepares you for
- Business Analyst
- Market Researcher
- Financial Analyst
- Data Analyst
- Management Consultant
- Finance
- Marketing
- Economics
- Management
- Healthcare
Where it gets hard
The units students slow down on, and what makes each one heavy.
- Module 3: CORRELATION AND REGRESSION ANALYSIS
Unit 2: Pearson's Correlation Co-efficient
Requires strong understanding of statistical relationships and ability to interpret correlation coefficients.
- Module 4: STATISTICAL TEST
Unit 3: Chi-Square Distribution
Involves complex calculations and understanding of hypothesis testing principles.
A suggested way through it
13 weeks, about 60 hours in total. Yours will differ.
- Week 1Module 1: Role and Concepts of Statistics
Unit 1: Role of Statistics (Application of Statistics) · 4 hours
Understand the definitions of statistics and its role as a management tool.. Identify and differentiate between numerical and non-numerical data.. Explore the applications of statistics in various fields like government and business..
- Week 2Module 1: Role and Concepts of Statistics
Unit 2: Measurement of Variables · 4 hours
Define variables and differentiate between quantitative and qualitative variables.. Learn about discrete and continuous variables.. Understand the four measurement scales: nominal, ordinal, interval, and ratio..
- Week 3Module 1: Role and Concepts of Statistics
Unit 3: Measures of Dispersion, Skewness and Kurtosis · 6 hours
Compute the range, quartile deviation, mean deviation, variance, and standard deviation for a given dataset.. Understand the concept of coefficient of variation.. Learn about Pearson's coefficients of skewness and kurtosis..
- Week 4Module 1: Role and Concepts of Statistics
Unit 4: Decision Analysis and Administration · 5 hours
Understand the administrative and decision-making process.. Differentiate between analytical and creative thinking.. Explore methods like critical examinations, brainstorming, analogies, and morphological approach..
- Week 5Module 2: INDEX NUMBER AND SAMPLING THEORIES
Unit 1: Index Number · 4 hours
Understand the uses of index numbers in measuring economic trends and deflation.. Differentiate between price, quantity, and value index numbers.. Learn about the problems encountered in constructing index numbers..
- Week 6Module 2: INDEX NUMBER AND SAMPLING THEORIES
Unit 2: Statistical Data · 4 hours
Distinguish between primary and secondary data.. Understand the advantages and disadvantages of each data type.. Learn about cross-sectional, time-series, and panel data..
- Week 7Module 2: INDEX NUMBER AND SAMPLING THEORIES
Unit 3: Sample and Sampling Theory · 5 hours
Define population, sample, and sampling unit.. Differentiate between probability and non-probability sampling.. Explore different sampling designs like simple random, systematic, stratified, and cluster sampling..
- Week 8Module 2: INDEX NUMBER AND SAMPLING THEORIES
Unit 4: Estimation Theory · 4 hours
Understand the methods of point estimation.. Learn about the method of maximum likelihood.. Apply estimation theory to solve business and economic problems..
- Week 9Module 3: CORRELATION AND REGRESSION ANALYSIS
Unit 1: Correlation Theory and Goodness of Fit · 4 hours
Understand the concept of correlation and its types: perfect positive, perfect negative, strong positive, strong negative.. Interpret scatter plots to determine the strength and direction of correlation..
- Week 10Module 3: CORRELATION AND REGRESSION ANALYSIS
Unit 2: Pearson's Correlation Co-efficient · 5 hours
Compute Pearson's correlation coefficient.. Interpret the value of the correlation coefficient to determine the strength and direction of the relationship between two variables.. Apply the concept of correlations in business decisions..
- Week 11Module 3: CORRELATION AND REGRESSION ANALYSIS
Unit 3: Spearman's Regression Analysis · 5 hours
Explain the computation of rank correlation coefficients.. Apply Spearman's rank correlation technique to evaluate the strength of the relationship between two sets of ranked data.. Understand the concept of tied ranks and their adjustment in the formula..
- Week 12Module 3: CORRELATION AND REGRESSION ANALYSIS
Unit 4: Ordinary Lease Square Estimation (Regression) · 5 hours
Understand the concept of regression analysis and its uses for prediction and description.. Learn about simple and multiple regression.. Apply the least squares method to determine the regression line..
- Week 13Module 3: CORRELATION AND REGRESSION ANALYSIS
Unit 5: Multiple Regression Analysis · 5 hours
Understand the concept of multiple regression analysis.. Learn how to solve multiple regression equations.. Apply multiple regression analysis to solve business and economic problems..
Preparing for the exam
- Create flashcards for statistical formulas and definitions from Units 2-4.
- Practice regression analysis problems from Units 10-13 weekly.
- Review hypothesis testing steps from Units 14-16 and apply to sample datasets.
- Focus on interpreting statistical results in context, not just calculations.
- Allocate equal time to each module during the final week of study.
Questions students ask about this course
What is SMS202 about?
This course introduces the basic concepts and principles of statistics in a business context. It covers data collection methods, summarizing data, graphical presentations, and measures of index numbers and dispersion. Students will learn correlation and regression analysis, hypothesis testing, and time series analysis. The course also explores distributions of discrete and continuous random variables, providing a foundation for informed decision-making in business environments.
How many units does SMS202 have?
SMS202, Business Statistics Ii, has 18 units across 4 modules, over 171 pages of course material. You can read it one unit at a time.
How many credit units is SMS202?
SMS202 carries 3 credit units, at 200 level in Management Sciences.
Is SMS202 hard?
SMS202 is rated intermediate level, with intermediate mathematical content. It is mostly theoretical, problem solving and case study work.
How long does SMS202 take to study?
About 156 hours of study, spread across its 18 units.
How is SMS202 assessed?
SMS202 is assessed by assignments, tutor marked assessments and final examination.
What can I do with SMS202?
Business Analyst, Market Researcher, Financial Analyst, Data Analyst and Management Consultant.