Long Title:Business Statistics and Analytics
Language of Instruction:English
Module Code:H8BSTAT
Credits: 5
NFQ Level:LEVEL 8
Field of Study: Mathematics and statistics not further defined or elsewhere classified
Module Delivered in 3 programme(s)
Module Coordinator: CORINA SHEERIN
Module editor: CORINA SHEERIN
Teaching and Learning Strategy: Teaching and learning will take place primarily via practical based lectures which will be interactive in nature. The learning environment will be applied in nature and lectures will focus on the understanding and application of knowledge utilising a problem based learning approach. The teaching and learning strategy will encourage integration with peers in a variety of pedagogic contexts such as independent and inter-dependent teaching and online forums. Technology will be used as an important part of the learning strategy. Learners on completion of this module will have gained an understanding of how to use statistical tools and analytics using software (Microsoft excel and/or SPSS), thus enabling learners to undertake data analysis in most business environments, ranging from SMEs through to large corporations. Various datasets from a range of business contexts will be applied across the curriculum which will allow learners see the application of statistical tools and the use of analytics within the business environment. Learners will be expected outside of class time to access online materials which will facilitate them reinforcing their learning as well as applying new learning. Equally technology will be used to provide resources to learners to enable them to undertake preparatory work for classes.
Learning Environment: Learning will take place in a classroom and/or laboratory environment with access to IT resources. Learners will have access to library resources, both physical and electronic and to faculty outside of the classroom where required. Module materials will be placed on Moodle, the College’s virtual learning environment.
Module Description: The aim of this module is to introduce learners to descriptive and inferential statistics and their applications within the business context. In particular this module aims to ensure that students from all business disciplines are literate in the understanding of statistical and empirical data. This module will provide learners with the framework and toolkit necessary to clarify, redefine, analyse and solve contemporary business problems. On completion learners will be able to describe and present data, estimate relationships between variables such as price and quantity demanded, sales and advertising and make inferences about the population using analytical and statistical techniques.
Learning Outcomes
On successful completion of this module the learner will be able to:
LO1 Critique and apply statistical and analytical techniques in developing conclusions about populations based on sample results.
LO2 Synthesise data and analyse business problems under conditions of uncertainty, formulate null and alternative hypotheses and exercise judgement in the resolution of business problems using hypothesis testing.
LO3 Evaluate and interpret relationships between two or more variables through the use of correlation and regression analysis.
LO4 Construct appropriate hypothesis tests to model business problems and apply hypothesis testing procedures to develop recommendations.
LO5 Use appropriate software in the application and interpretation of statistical methods and techniques and present findings/output in a professional and technical or non technical manner as required.
Pre-requisite learning
Module Recommendations

This is prior learning (or a practical skill) that is required before enrolment on this module. While the prior learning is expressed as named NCI module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).
No recommendations listed
Requirements

This is prior learning (or a practical skill) that is mandatory before enrolment in this module is allowed. You may not enrol on this module if you have not acquired the learning specified in this section.
No requirements listed
 

Module Content & Assessment

Indicative Content
Business Analytics & Statistics- An Overview (Week 1)
• Role of Statistics and Analytics in Business • Descriptive vs. Inferential Statistics • Types of data and scales of measurement • Parametric and Non Parametric Statistics • Use and Misuse of Analytical Tools and Statistics
Sources of Statistical Data (Week 2)
• Types of Data Sources • Using Global, EU and Irish Business Data Sources • Big Data and Analytics within Business • Analysis of Data and Data Sources Software: Using the Data Analysis Toolpak: Excel Introduction to SPSS Sample Application of Content: Examining what statistics are appropriate for analysis given the scales of measurement of the variables under study.
An Introduction to Statistical Inference (Week 3-4)
• Sampling methods • Sampling distribution of the sample mean • Central Limit Theorem • Point estimates and confidence intervals for a mean Software: Developing a probability distribution using excel Using SPSS to calculate confidence intervals Sample Application of Content: Considering the shape of a distribution of raw data and hence applying the central limit theorem (CLT) to the samples selected in order to demonstrate the approximation to normality. Application of the CLT to allow for sampling distributions from bisuness to be used effectively to make inferences about the population, eg: if the mean hourly wage for business graduates is €X. What is the likelihood that we could select a sample of 50 business graduates with a mean wage of €X+0.50 or more per hour assuming the standard deviation of the sample equals €Y per hour.
Hypothesis Testing (Week 4-5)
•Introduction to Hypothesis Testing Hypothesis Testing Procedures • One Sample Tests of Hypothesis
Hypothesis Testing: Two Sample Tests of Hypothesis (Week 6,8,9)
• Two Samples Tests of Hypothesis: Independent Samples • Comparing Population Means with Unknown Population Standard Deviations (Pooled T Tests) • Comparing Population Means with Unknown Population Standard Deviations (Unequal) • Two Sample Tests of Hypothesis: Dependent Samples • Introduction to the F Distribution • Comparing Population Variances Software: Using excel/SPSS to carry out hypothesis tests Sample Application of Content: Selecting from a range of hypothesis tests to check the validity of a business statement(s) about a population parameter. For example candidates may be provided with a data set concerning hospital response rates by doctors in the surgical department A and B respectively and asked to test whether there is a difference in the mean response times for the two groups.
Correlation & Regression (Week 10-12)
• Correlation & Covariance Coefficient • Coefficient of Determination • Testing the Significance of the Correlation Coefficient • Introduction to Regression Analysis • Linear Regression: Principles of Ordinary Least Squares Technique (OLS) • Assumptions underlying Linear Regression • Using Regression for Predictions Software: Using excel/SPSS to test for relationships between variables using graphics, correlation and hence regression analysis Sample Application of Content: Exploring the relationship between crime and resulting police complaints and hence estimating the strength of the relationship, testing for spurious correlations and using the regression equation in prediction.
Revision & CA (Week 13)
n/a
Assessment Breakdown%
Coursework100.00%

Full Time

Coursework
Assessment Type Assessment Description Outcome addressed % of total Assessment Date
Formative Assessment Formative assessment will be provided to students through the use of on-line quizzes and short answer questions. In addition in class problems and discussions will provide an opportunity for formative learning and student feedback to be provided. Provision of individual feedback will be provided individually outside of lecture time or on line through Moodle. 1,2,3,4,5 Non-Marked n/a
Continuous Assessment (0200) Learners will undertake a continuous assessment on the topics of Statistical Inference and Hypothesis testing. The continuous assessment may take the form of an in class test and/or problem set/case study. The in class assessment may include a mix of: short answer questions, long questions multiple choice, vignettes and or problem based questions. All questions presented to students will be within a business problem solving context. Learners will be expected to evaluate, combine and synthesise information in order to develop recommendations and conclusions to practical business problems across a variety of scenarios. Reference to class material, evidence of outside reading is essential. 1,2,4,5 30.00 n/a
Project (Proj) Learners will be presented with a data set and/or case study. Learners will be expected to undertake a number of prescribed tests on the data. A number of questions will be presented to the learner and they will be expected to evaluate, combine and synthesise the information and develop and present a detailed technical report of the findings. 1,2,3,4,5 70.00 n/a
No End of Module Assessment
No Workplace Assessment
Reassessment Requirement
Coursework Only
This module is reassessed solely on the basis of re-submitted coursework. There is no repeat written examination.
Reassessment Description
This module is reassessed solely on the basis of re-submitted coursework. There is no repeat written examination.

NCIRL reserves the right to alter the nature and timings of assessment

 

Module Workload

Workload: Full Time
Workload Type Workload Description Hours Frequency Average Weekly Learner Workload
Lecture No Description 2 Every Week 2.00
Practical No Description 2 Every Week 2.00
Independent Learning No Description 6.5 Every Week 6.50
Total Hours 10.50
Total Weekly Learner Workload 10.50
Total Weekly Contact Hours 4.00
Workload: Part Time
Workload Type Workload Description Hours Frequency Average Weekly Learner Workload
Lecture No Description 2 Every Week 2.00
Lab No Description 2 Every Week 2.00
Total Hours 4.00
Total Weekly Learner Workload 4.00
Total Weekly Contact Hours 4.00
 

Module Resources

Recommended Book Resources
  • Lind D.A., Marchal W.G., and Wathen S.A. 2015, Statistical Techniques in Business and Economics, 16th Ed., McGraw Hill
Supplementary Book Resources
  • Moore, D.S., Notz, W.I., and Fligner, M.A. 2015, The Basic Practice of Statistics, 7th Ed., Macmillan Education.
  • Swift, L. and S. Piff. 2014, Quantitative Methods for Business, Management and Finance, 4th Ed., Palgrave Macmillian
  • Oakshott, L. 2012, Essential Quantitative Methods for Business, Management and Finance, 5th Ed., Palgrave Macmillian
  • Pease,G., Beresford, B., and Walker, L. 2014, Developing Human Capital: Using Analytics to Plan and Optimize Your Learning and Development Investments, Wiley
  • Field, A. 2013, Discovering Statistics using IBM SPSS Statistics, 4th Ed., SAGE Publications.
  • Levine, D., and Stephan, D.F 2013, Statistics for Managers Using MS Excel, 7th Ed., Pearson Education.
  • Davies, G. and Pecar, B. 13, Business Statistics using Excel, 2nd Ed., Oxford University Press.
This module does not have any article/paper resources
Other Resources
 

Module Delivered in

Programme Code Programme Semester Delivery
BAHHRD BA (Honours) in Human Resource Management 5 Optional
BAHBMD BA (Hons) in Business 5 Core Subject
BAHACC BA Honours in Accounting 5 Group Elective 2