The fundamental aim of this module is to give students an understanding of how statistics operates in Business and Economics; To provide both a foundation for further study and a broadly based introduction to statistics; To enable students to summarize, present and analyze data from a sample; To enable students to understand and apply the practice of statistical inference to sample data to estimate full population variable parameters; To enable students to work comfortably with variables as probability distributions, introducing some common and practicably useful probability distributions.

(LO1) Students will understand the basis of data analysis

(LO2) Students will understand the fundamental notion of statistical inference

(LO3) Students will be able to summarise, describe and present raw data

(LO4) Students will be able to estimate key summary statistics(e.g. mean, median, standard deviation, variance, co-variance, inter-quartile range)

(LO5) Students will be able to formulate and test hypotheses about values in the population based on random samples

(LO6) Students will be able to carry out basic statistical computations and graphical analysis

(LO7) Students will be able to identify and model relationships between two variables

(LO8) Students will understand the use of and apply probability models in data and statistics problems

(LO9) Students will be able to interpret and effectively communicate results of statistical analysis

(S1) Adaptability

(S2) Problem solving skills

(S3) Numeracy

(S4) Commercial awareness

(S5) Organisational skills

(S6) Communication skills

(S7) International awareness

(S8) Lifelong learning skills

Teaching Method: Large Group Teaching
Scheduled Directed Student Hours: 24
Attendance Recorded: Yes

Teaching Method – Tutorial and Assessment Feedback
Description: Online (synchronous) Tutorial discussing solutions to assessments including questions and guidance on improving approaches.
Scheduled Directed Student Hours: 5
Attendance Recorded: Yes
Notes: 5 x 1hr tutorials (fortnightly from week 4)

Teaching Method - Workshop
Scheduled Directed Student Hours: 12
Attendance Recorded: Yes
Notes: Weekly workshops

Self Directed Learning Hours - 109

There are the following pre-requisites:
Students must have taken one of the following: ACFI127, ECON121 or ECON127. Students who are not studying on a joint honours programme with the maths department must also have taken ACFI111 or ECON111 and ECON112.

This module is a pre-requisite for the following modules:
ECON211 / ECON233 / ECON322 / ECON326 / E CON346

Skills and Attribute Mapping

Skill/Other Attribute 1: "Lifelong learning skills"
How this is developed: "Some discussion of sourcing of reliable statistics and limitations of data and statistical skills considered"
Mode of assessment (if Applicable): Coursework and Examination

Skill/Other Attribute 2: "International awareness"
How this is developed: "Real-world data used for some exercises from international sources."
Mode of assessment (if Applicable): Coursework and Examination

Skill/Other Attribute 3: "Communication skills"
How this is developed: "This course does not just require mechanical calculations. Students must undertake calculations and consider their relevance to the problem set and communicate interpretations of the data and/or how they relate to solutions of specific problems"
Mode of assessment (if Applicable): Coursework and Examination

Skill/O ther Attribute 4: "Organisational skills"
How this is developed: "Students are expected to organize their own learning within the guidelines given."
Mode of assessment (if Applicable): Coursework and Examination

Skill/Other Attribute 5: "Commercial awareness"
How this is developed: "Real-world data used for some exercises"
Mode of assessment (if Applicable): Coursework and Examination

Skill/Other Attribute 6: "Numeracy"
How this is developed: "The ability to think logically, to appreciate the significance of the relationships between relevant economic variables. The consequences of specific changes, to think through a sequence of steps of a statistical problem. To apply knowledge to new scenarios. Direct numerically based problems."
Mode of assessment (if Applicable): Coursework and Examination

Skill/Other Attribute 7: "Problem solving skills"
How this is developed : "The ability to think logically, to appreciate the significance of the relationships between relevant economic variables. The consequences of specific changes, to think through a sequence of steps of a statistical problem. To apply knowledge to new scenarios. Direct numerically based problems."
Mode of assessment (if Applicable): Coursework and Examination

Skill/Other Attribute 8: "Adaptability"
How this is developed: "The ability to think logically, to appreciate the significance of the relationships between relevant economic variables. The consequences of specific changes, to think through a sequence of steps of a statistical problem. To apply knowledge to new scenarios. Direct numerically based problems."
Mode of assessment (if Applicable): Coursework and Examination

The module will comprise the following elements which include application of techniques to data sets and practical problems:

An Introduction to the Course including - Displaying distributions with graphs; Describing distributions with numbers; Density curves and Normal distributions as well as visual representations of Time series data and Scatterplots.

The relationship between 2 variables including Correlation & Least Squares Regression (and cautions in application); Data analysis for 2-way tables and the question of causation.

Sampling designs and design of experiments toward statistical inference.

The Study of Randomness & probability models including probability and sampling distributions; General Probability Rules and conditional probability.

Applications of Binomial & Poisson distributions.

Estimating with Confidence via Tests of Significance (including use (and abuse) of significance tests).

Inference for decision making i ncluding - Inference for the mean of a population; Comparing 2 means; Inference for a proportion of a population; Inference for Regression parameters.

ANOVA (Analysis of Variance) and multi-variate regression.

Analysis of Two-Way Tables including - Tests for independence; Comparing several populations and testing Goodness of Fit.