Statistical Design and Analysis
Lecture 1:
Introduction to Statistics
Stephen Bush
School of Mathematical and Physical Sciences
1
Why Statistics?
Statistics is all about DATA
Collecting DATA
Describing DATA summarizing, visualizing
Analyzing DATA
Dat

SDA 33116- Lecture 1
Data
Data: A set of measurements (variables) taken on a set of individual units (cases) that can
be used to yield conclusions/make comparisons.
Dataset: a way of presenting data comprising of variables measured in cases.
(Columns=va

Lecture 2
Experiments and Observational Studies
Association (correlation): Two variables are associated if values of one variable tend to be
related to values of the other variable. Association does not imply cause.
Causation: Two variables are causally a

Statistics Lecture 6
Introducing Hypothesis Tests
Statistical Test: Uses data from a sample to assess a claim about a population. Framed with two
competing hypothesis
Null Hypothesis (H0): Claims that there is no effect or difference
Alternative Hypothe

Lecture 12
Linear Regression
Inference for Slope
1. State Hypothesis
H0: Slope =0 variable x gives no information about variable y
HA: Slope does not equal 0. Knowing x gives some information about y.
2. Calculate Test Statistic
Slope y=a +bx.
Test st

Lecture 5
Sampling Distributions
Statistical Inference: The process of drawing conclusions about the entire population based on
information in a sample.
Parameter: Number that describes some aspect of a population
Statistic: A number that is computer fr

Statistics: Lecture 3
One Quantitative Variable
Data Visualisation
1. Dotplot: Each case is represented by a dot and dots are stacked. Identifies outlier cases.
2. Histogram: Quantitative data with numeric x-axis. The height of each bar corresponds to the

Statistics Lecture 10
Chi- Square goodness of fit
Chi Sqaure goodness of fit : Single Categorical Variable
Testing proportion for several categories
H0 : specifies a proportion for each category
HA: At least one proportion is wrong
Observed Counts: actual

Lecture 11
Analysis of Variance (ANOVA)
Analysis of variance is used to test for a difference in means between groups by comparing the
variability between groups to the variability within groups.
1. State hypothesis:
Ho = all means are equal 1 = 2 = 3 = 4

Statistics Lecture 9
Determining Statistical Significance
Formal Decisions
Reject H0
The sample would be extreme if H0 were true
The results are statistically significant
There is evidence for HA
Small p value <0.05
Do not reject H0
The sample would not b

Autumn 2014- Main Exam
STUDENT NUMBER:
iUTS
II
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SURNAME:
UNIVERSnY OF TECHNOLOGY, SYDNEY
OTHER NAMES:
This paper and all materials issued must be returned at the end of the examination.
They are not to be rernpvetffrom the exam centre.
Exa

Lecture 4
Two Quantitative Variables
Direction of Association
Positive Association: Values of one variable tend to be higher when values of the other variable
are higher
Negative Association: Values of one variable tend to be lower when values of the ot