ULMS Electronic Module Catalogue
The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module.
Title STATISTICS FOR ECONOMICS AND BUSINESS
Code ECON112
Coordinator Dr S Phythian-Adams
Economics
S.L.Phythian-Adams@liverpool.ac.uk
Year CATS Level Semester CATS Value
Session 2019-20 Level 4 FHEQ Second Semester 15

Pre-requisites before taking this module (other modules and/or general educational/academic requirements):
ECON111 MATHEMATICS FOR ECONOMICS AND BUSINESS 

Modules for which this module is a pre-requisite:
 

Programme(s) (including Year of Study) to which this module is available on a required basis:
 

Programme(s) (including Year of Study) to which this module is available on an optional basis:
 

Teaching Schedule
  Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
Study Hours 24

   5

     12

10

 51
Timetable (if known)              
Private Study 99
TOTAL HOURS 150

Assessment
EXAM Duration Timing
(Semester)		 % of
final
mark		 Resit/resubmission
opportunity		 Penalty for late
submission		 Notes
Assessment 2 There is a resit opportunity. Assessment Schedule (When) :2  2-hours    80       
CONTINUOUS Duration Timing
(Semester)		 % of
final
mark		 Resit/resubmission
opportunity		 Penalty for late
submission		 Notes
Assessment 1 There is a resit opportunity. Non-standard penalty applies for late submission - Assessment Schedule (When) :2  5 exercises    20       

Aims

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.

Learning Outcomes

(LO1) The basis of data analysis

(LO2) The fundamental notion of statistical inference

(LO3) Summarise,describe and present raw data

(LO4) Estimate the mean of a population (and other statistics)

(LO5) How to formulate and test hypotheses about values in the population based on random samples

(LO6) How to carry out basic statistical computations and graphical analysis

(LO7) How to identify and model relationships between two variables

(LO8) Understand the use of probability in statistics

(LO9) Communicating results

(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 and Learning Strategies

Teaching Method 1 - Lecture
Description:
Attendance Recorded: Not yet decided

Teaching Method 2 - Tutorial
Description:
Attendance Recorded: Not yet decided
Notes: 5 x 1hr tutorials (fourtnightly from week 4)

Teaching Method 3 - Workshop
Description:
Attendance Recorded: Not yet decided
Notes: Weekly workshops

Teaching Method 4 - Assessment
Description:
Attendance Recorded: Not yet decided
Notes: 5 continuous assessment exercises

Syllabus
 

An Introduction to the Course Displaying distributions with graphs Describing distributions with numbers Density curves and Normal distributions Scatterplots Correlation & Least Squares Regression Least-squares regression continued & cautions Data analysis for 2-way tables + question of causation Sampling designs and design of experiments Designs toward statistical inference The Study of Randomness + probability models Probability and sampling distributions General Probability Rules (& conditional probability) Binomial & Poisson distributions Estimating with Confidence Tests of Significance Use (and abuse) of significance tests Inference for decision making Inference for the mean of a population Comparing 2 means Inference for a proportion of a population Analysis of Two-Way Tables Analysis of Two-Way Tables – Goodness of Fit More on Simple Linear Regression (not examined here) Review & Exam Prep

Recommended Texts
Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module.