STATS 1000MELB - Statistical Practice I

Melbourne Campus - Semester 1 - 2024

Statistical ideas and methods are essential tools in virtually all areas that rely on data to make decisions and reach conclusions. This includes diverse fields such as medicine, science, technology, government, commerce and manufacturing. In broad terms, statistics is about getting information from data. This includes both the important question of how to obtain suitable data for a given purpose and also how best to extract the information, often in the presence of random variability. This course provides an introduction to the contemporary application of statistics to a wide range of real world situations. It has a strong practical focus using the statistical package R to analyse real data. Topics covered are: organisation, description and presentation of data; design of experiments and surveys; random variables, probability distributions, the binomial distribution and the normal distribution; statistical inference, tests of significance, confidence intervals; inference for means and proportions, one-sample tests, two independent samples, paired data, t-tests, contingency tables; analysis of variance; linear regression, least squares estimation, residuals and transformations, inference for regression coefficients, prediction.

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Course Details

Course Code	STATS 1000MELB
Course	Statistical Practice I
Coordinating Unit	Mathematical Sciences
Term	Semester 1
Level	Undergraduate
Location/s	Melbourne Campus
Units	3
Contact	Up to 3 hours per week
Available for Study Abroad and Exchange	Y
Incompatible	MATHS 2107, STATS 1004, STATS 1005, ECON 1008, STATS 1504
Assumed Knowledge	SACE Stage 2 Mathematical Methods
Restrictions	Available only to 最新糖心Vlog of Adelaide College Melbourne Campus students
Assessment	Assignments, online quizzes and tasks, ongoing assessment, exam

Course Staff

Course Coordinator: Dr Adam - Benjamin Rohrlach

Course Timetable

The full timetable of all activities for this course can be accessed from .

Learning Outcomes

Course Learning Outcomes

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Learning & Teaching Activities

Learning & Teaching Modes

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Workload

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Learning Activities Summary

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Assessment must encourage and reinforce learning.
Assessment must enable robust and fair judgements about student performance.
Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
Assessment must maintain academic standards.

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Assessment Detail

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Submission

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Course Grading

Grades for your performance in this course will be awarded in accordance with the following scheme:

M10 (Coursework Mark Scheme)
Grade	Mark	Description
FNS		Fail No Submission
F	1-49	Fail
P	50-64	Pass
C	65-74	Credit
D	75-84	Distinction
HD	85-100	High Distinction
CN		Continuing
NFE		No Formal Examination
RP		Result Pending

Further details of the grades/results can be obtained from Examinations.

Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

Final results for this course will be made available through .

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Maintained by:	Course Outlines Administrator

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