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
Descri
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
Smal
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. S
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: A
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 nu
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 o
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
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 tha
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 n
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
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
Chapter 1
Individual units are called cases and data is stored in a data set.
Categorical variables divide the cases into groups.
Quantitative variables variable that measures a numerical quantity for
ACST201 Financial Modelling
Week 01 tutorial material
S1 2016
Week 01 Tutorial Material
1. If I invest a sum of money in a bank account oering 10% per annum compounded monthly, what is my eective annu
ACST201 FAQ
General
1. Where can I find information about consultation hours?
The details are on the iLearn.
2. What should I do if I have question to ask?
Please check the unit guide, announcements a
33116 Statistical Design and Analysis Computer Lab 3
Section 2.2: One Quantitative Variable: Shape and Centre
Question 1: Height of Students
The histogram and dotplot below both show the data for the
33116 Statistical Design and Analysis Computer Lab 7
Section 4.3: Determining Statistical Significance
Question 1: Analogy to Fire Alarms
As required by law, UTS has fire alarms throughout the campus.
Section 1.3: Experiments and Observational Studies
Question 1: Association, Causation, and Confounding Variables
An association is described. In each case, indicate
a) Whether the statement implies ca
33116 Statistical Design and Analysis Tutorial 3
Critique Task
Instructions: Your tutor will handout Cover Sheets with the Critique Questions on the reverse. Discuss your
articles with the Critique Qu
33116 Statistical Design and Analysis Tutorial 4
Question 1
Here are three regressions using data from the BodyFat file. The variables being measured are Bodyfat (in
per cent), abdomen circumference (
33116 Computer Lab 1
33116 Statistical Design and Analysis Computer Lab 1
Section 1.1: The Structure of Data
Question 1: 2011 Hollywood Movies
Here is a small part of a dataset that includes informati
33116StatisticalDesignandAnalysisTutorial1
Question 1
Suppose that we have information about kidney cancer.
a) If the values in the data set are rates of kidney cancer death, then what are
the cases?
33116 Statistical Design and Analysis Tutorial 2
Question 1
Think of two variables that are associated but not causally associated. See here
http:/tylervigen.com/spurious-correlations
Ice cream sales
33116 Statistical Design and Analysis Computer Lab 4
Section 2.5: Two Quantitative Variables: Scatterplot and Correlation
Question 1
In each case below, do you expect a positive or negative associatio
Autumn 2014- Main Exam
STUDENT NUMBER:
iUTS
II
.<
J.
l I I I
I
SURNAME:
UNIVERSnY OF TECHNOLOGY, SYDNEY
OTHER NAMES:
This paper and all materials issued must be returned at the end of the examination
Statistical Design and Analysis
Mid Semester Revision Class
Stephen Bush
School of Mathematical and Physical Sciences
Unit A
Essential Synthesis
The Big Picture
Population
Sampling
Sample
Statistical