Module Code: |
H7IBSA |
Long Title
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Introduction to Business Statistics and Analytics
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Title
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Introduction to Business Statistics and Analytics
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Module Level: |
LEVEL 7 |
EQF Level: |
6 |
EHEA Level: |
First Cycle |
Module Coordinator: |
COLETTE DARCY |
Module Author: |
Isabela Da Silva |
Departments: |
School of Business
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Specifications of the qualifications and experience required of staff |
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Learning Outcomes |
On successful completion of this module the learner will be able to: |
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Learning Outcome Description |
LO1 |
Demonstrate an understanding of statistical principles, theories and methods and appreciate how they apply in a range of business and management decision making situations. |
LO2 |
Recognise different types of data and associated statistical measures and their appropriateness in a range of scenarios |
LO3 |
Utilise a range of descriptive statistics in order to evaluate and present information and data associated with univariate analyses and appreciate how they contribute in business intelligence. |
LO4 |
Demonstrate proficiency in the principles and application of probability theory |
LO5 |
Use appropriate software in the presentation and organisation of statistical data and hence select and apply appropriate statistical methods and techniques. |
Dependencies |
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).
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No recommendations listed |
Co-requisite Modules
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No Co-requisite modules listed |
Entry requirements |
As per programme requirements (outlined in 4.2.2 Minimum requirements for general learning)
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Module Content & Assessment
Indicative Content |
Introduction
Introduction to Data
Role of Statistics and Analytics in Business
Descriptive vs. Inferential Statistics
Data and Data Sources
Use and Misuse of Analytical Tools and Statistics
Measurement Scales
Sample Application of Content: Differentiating between qualitative and quantitative variables and identifying what scales of measurement are appropriate in a variety of business contexts.
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Describing Data: Frequency Tables & Graphics
Frequency Data & Frequency Tables
Graphical Representation of Data:
Bar Charts
Pie Charts
Histograms
Scatter Plots & Linear Representation
Sample Application of Content: Using a variety of business data sets containing raw data, both discrete and continuous.
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Describing Data: Measures of Central Tendency
Mean
Mode
Median
Sample Application of Content: Compare and contrast the main measures of central tendency and hence using both raw and frequency data from business contexts, identify a suitable measure of central tendency and hence calculate and interpret as appropriate.
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Describing Data: Measures of Dispersion
Range & Mean Absolute Deviation
Variance & Standard Deviation (Population and Sample)
Symmetric Distributions and Skewness
Kurtosis
Sample Application of Content: Develop a frequency distribution and hence calculate the mean and standard deviation. Graphically present the distribution and discuss the symmetry of the distribution and the implications of same.
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Basics of Probability
The concept and language of probability
The role of probability in statistics
Approaches to assigning probabilities
Rules of addition and multiplication for computing probability
Conditional probability
Sample Application of Content: Using probability trees to model business problems and hence calculate conditional probabilities. For example, in the case of finance, modelling an investment problem using a probability tree and hence calculation of conditional probabilities and expected values.
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SOFTWARE APPLICATION:
The practical lab session(s) will be dedicated to the use of software, for example MS Excel, in order to develop appropriate tables and graphics to summarise data and to calculate measures of centre and dispersion for both grouped and ungrouped data. Learners will have access to the virtual desktop in order to access MS Excel or other software deemed appropriate.
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Assessment Breakdown | % |
Coursework | 40.00% |
End of Module Assessment | 60.00% |
AssessmentsFull Time
Coursework |
Assessment Type: |
Formative Assessment |
% of total: |
Non-Marked |
Assessment Date: |
n/a |
Outcome addressed: |
1,5 |
Non-Marked: |
Yes |
Assessment Description: Formative assessment will be provided to learners using 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 online through Moodle. |
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Assessment Type: |
In class assessment |
% of total: |
40 |
Assessment Date: |
n/a |
Outcome addressed: |
1,2,3,5 |
Non-Marked: |
No |
Assessment Description: Learners will be given a time-constrained in class assessment. The time-constrained assessment will take place in class and is worth 40% of the module grade. It may include a mix of short answer questions, multiple-choice choice, vignettes and/or problem based. |
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End of Module Assessment |
Assessment Type: |
Terminal Exam |
% of total: |
60 |
Assessment Date: |
End-of-Semester |
Outcome addressed: |
1,4,5 |
Non-Marked: |
No |
Assessment Description: The examination will be two hours in duration with learners required to answer two questions, each worth 50 marks. Each question will have multiple parts and will include both calculation and theory elements. All questions will be marked according to clarity and the ability to apply statistical and quantitative techniques to solve business problems. Learners are required to interpret findings. |
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Reassessment Requirement |
Repeat examination
Reassessment of this module will consist of a repeat examination. It is possible that there will also be a requirement to be reassessed in a coursework element.
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Reassessment Description The repeat strategy for this module is by examination. Learners will be afforded an opportunity to repeat the assessment(s) at specified times.
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NCIRL reserves the right to alter the nature and timings of assessment
Module Workload
Module Target Workload Hours 0 Hours |
Workload: Full Time |
Workload Type |
Workload Description |
Hours |
Frequency |
Average Weekly Learner Workload |
Lecture |
Classroom and demonstrations |
24 |
Per Semester |
2.00 |
Independent Learning |
Independent learning |
101 |
Per Semester |
8.42 |
Total Weekly Contact Hours |
2.00 |
Module Resources
Recommended Book Resources |
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Lind, D.A., Marchal, W.G. and Wathen, S.A , (2021). Statistical Techniques in Business and Economics,18th Ed , McGraw-Hill.
| Supplementary Book Resources |
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Camm, J.D, Cochran, J.J, Fry, M.J. and Ohlmann, J.W, (2021) , Business Analytics (eTextbook version also available. Cengage Learning.
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Anderson, D.R., Sweeney, D.J, Williams, T.A, Camm, J.D. and Cochran, J.J., (2020). Modern business statistics with Microsoft Excel. Cengage Learning.
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Field, A. (2017) Discovering Statistics using IBM SPSS Statistics. SAGE Publications.
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Salkind, N.J. and Frey, B.B, (2021). Statistics for People who (Think They) Hate Statistics Using Microsoft Excel. Sage publications.
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Levine, D, Stephan, D.F. and Szabat, K.A. (2021). Statistics for Managers Using MS Excel, Pearson Education.
| This module does not have any article/paper resources |
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Other Resources |
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[Website], Jonathan Lambert NCI Mathematics
Development and Support Videos,
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[Website], European Commission (Eurostat),
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[Website], Central Statistics Office,
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[Website], Irish Stock Exchange,
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[Website], Economic & Social Research Institute,
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[Website], European Social Survey,
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[Website], World Bank Data,
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[Website], Institute for Statistics Education,
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[Website], OECD Statistical Data,
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[Website], United States Department of Labour
Bureau of Labour Statistics,
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[Website], United States Census Bureau,
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[Journal], Applied Quantitative Methods.
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[Journal], Computational Statistics & Data
Analysis..
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[Journal], Business and Economic Statistics..
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[Journal], Financial and Quantitative Analysis..
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[Journal], Review of Economics and Statistics..
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[Journal], Oxford Bulletin of Economics and
Statistics..
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[Journal], Applied Statistics.
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[Journal], Quantitative and Qualitative Analysis in
Social Sciences.
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[Journal], Quantitative Finance..
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[Journal], Journal of Multivariate Analysis..
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[Journal], Review of Quantitative Finance and
Accounting..
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[Journal], Review of Economic Analysis..
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[Journal], Decision Analysis..
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