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STAT10050 – Course Outline
Lecture
Topic
Code
Chapter
Utts &
Heckard
Topic
Learning Goals
1
A
1
Introduction and
Motivation
1
B
2.1, 2.2, 5
Statistical
Concepts:
Samples and
Populations,
Variability, Bias
in Questions and
Bias in Sampling,
Types of
Variables and
Data
The students will know the
following: the difference between
sample and population; spread in
data set; how to word questions
correctly in questionnaire; how to
avoid mistakes in sampling; the
different types of variables and
data.
2/3
C
5
Collecting Data
1: Sampling and
surveys
The students will discover the
different types of sampling. They
will also know how to carry out
surveys in a correct manner, and
identify when there is misleading
information from surveys in the
newspapers.
2/3
D
6
Collecting Data
2: Experiments
and
Observational
Studies
The students should identify the
difference between
observational studies and
experimental studies, and the
various different methods used
in each of these.
4/5
E
2
Summarising
Data 1 Numerical
Summary
Measures –
Mean, Median,
Mode, Trimmed
Means, Quartiles,
Percentiles,
Range, Variance,
Standard
Deviation, Interquartile Range
The students will know how to,
calculate these quantities, and be
able to use them to make
statements about a data set.
STAT10050 – Course Outline
5/6
F
2
Summarising
Data 2 Graphical
Techniques for
Displaying Data –
Stem and Leaf
Plots,
Histograms, Box
Plots
The students will know how to,
construct these various graphical
techniques, and display data
visually. They will be able to
identify when each is used.
6
G
7
Probability
Concepts:
Probability of
Events,
Probability for
Discrete and
Continuous
Random
Variables
(probability
distribution
function,
probability
density function)
The students will familiarise
themselves with different axioms
of probability. They will know the
difference between discrete and
Continuous Random Variables, and
how to calculate their respective
probabilities.
7
I
9
Sampling
Distributions and
the Central Limit
Theorem.
The students will discover how to
form a distribution, and the
different issues with small and
large sample.
8 – Reading week
H
8
Particular
Probability
Distributions:
Bernoulli,
Binomial,
Geometric,
Negative
Binomial and
Normal
Distributions.
The students will discover how to,
identify the different distributions,
and calculate their respective
probabilities.
STAT10050 – Course Outline
9/10
J
10, 11
Margin of Error,
Confidence
Interval
Estimation for
population mean
and proportion
using a single
sample.
The students will discover how to
calculate these quantities. They
will also know how to interpret
them.
11/12
K
12,13
Hypothesis
testing: Principle
of a Hypothesis
Test, Errors in
Hypothesis
Testing, P-values,
Tests for
population means
and proportions
in a single sample
The students will know the
following: different steps and
errors involved in Hypothesis
Testing; how to calculate P-values
from the statistical tables; when to
use the t-Distribution or normal
Distribution function, how to
calculate the t or z statistic; how to
carry out the Tests for population
means and proportions in a single
sample.
12
L
Summary