MATH08005 2013 Statistics
The student should be able to have a foundation in statistical analysis and be able to manipulate statistical data.
Learning Outcomes
On completion of this module the learner will/should be able to;
Summarise, describe data and identify the position of a data value in a dataset.
Determine the probability of an event using probability rules.
Calculate the probability for outcomes using discrete and continuous distributions.
Calculate confidence intervals for population mean, proportion and variance.
Perform hypothesis testing using parametric and nonparametric tests.
Make decisions and draw conclusions on the basis of statistical analysis.
Indicative Syllabus
 Descriptive Statistics: Measures of Central Tendency and Measures of Dispersion, Sampling. Use of corresponding statistical functions in Excel/statistical software.
 Laws of Probability: Addition Rule, Multiplication Rule, Conditional Probability, Bayes's Theorem
 Discrete Probability Distributions: Binomial, Poisson, Geometric and Hypergeometric distributions. Use of statistical software to calculate probability distributions.
 Continuous Probability Distributions: Uniform, Normal and Exponential distributions. Normal distribution as approximation to Binomial. Central Limit Theorem. Use of statistical software to calculate probability distributions.
 Estimation: Point estimation and confidence intervals. Confidence intervals for population mean. T Distribution. Confidence Intervals for a population proportion. Determining sample size. Confidence Intervals for a population variance. Distribution. Use of statistical software to develop confidence intervals.
 Hypothesis Testing: Fundamentals, Testing a claim about a mean, proportion, standard deviation or variance. Pvalues. Use statistical software to perform hypothesis testing.
 Inference from Two Samples: Inference about two means, independent samples and matched pairs. Inference about two proportions. Comparing variation in two samples. F Distribution. Use of statistical software to perform corresponding test.
 Chi Squared Tests: Goodness of Fit Testing, Contingency Tables
 Nonparametric Statistics: Sign test, Wilcoxon test.
Coursework & Assessment Breakdown
Coursework Assessment
Title  Type  Form  Percent  Week  Learning Outcomes Assessed  

1  Assignment  Continuous Assessment  UNKNOWN  20 %  OnGoing  1,2,3,4,5,6 
End of Semester / Year Assessment
Title  Type  Form  Percent  Week  Learning Outcomes Assessed  

1  Final Exam  Final Exam  UNKNOWN  80 %  End of Term  1,2,3,4,5,6 
Full Time Mode Workload
Type  Location  Description  Hours  Frequency  Avg Workload 

Lecture  Not Specified  Lecture  2  Weekly  2.00 
Tutorial  Not Specified  Tutorial  2  Weekly  2.00 
Part Time Mode Workload
Type  Location  Description  Hours  Frequency  Avg Workload 

Lecture  Not Specified  Lecture  2  Weekly  2.00 
Tutorial  Not Specified  Tutorial  2  Weekly  2.00 
Module Resources
Authors 
Title 
Publishers 
Year 
Allan Bluman 
Elementary Statistics: A Step by Step Approach 8th Edition 
McGraw Hill 
2012 
























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