Descriptive Statistics
Statistic: Summary of data (measure of events)
Field of statistics: collecting, analysing of data measured with uncertainty
Graphs
Categorical
Individual placed into one of several categories
Quantitative
Numerical values, measured
Probability
3.1
Lectures 1-2: Probability
Randomness and probability
Probability models
Probability rules
Assigning probabilities to outcomes
Independence
Sections 4.1-4.2 of Moore et al.
3.2
Randomness and probability
A phenomenon is random if indiv
MATH1041 Course Pack - Part C
This part of the course pack includes copies (and solutions to) some of the assessment
tasks for the MATH1041 course in previous semesters.
1 Some Past Mid-Semester Tests
3
2 Mid-semester test solutions
23
3 Past Exam Papers
Lectures 1-2:
Transformations and
Relationships Between Variables
1.1
Lectures 1-2: summary
This lecture, we will learn about the role of transformation in statistics,
and introduce some ideas that are useful for studying the relationship
between two quan
THE UNIVERSITY OF NEW SOUTH WALES
SCHOOL OF MATHEMATICS AND STATISTICS
Semester 2, 2014
MATH1041
STATISTICS FOR LIFE
AND SOCIAL SCIENCES
(1) TIME ALLOWED 2 hours
(2) TOTAL NUMBER OF QUESTIONS 4
(3) ANSWER ALL QUESTIONS
(4) THE QUESTIONS ARE OF EQUAL VALUE
MATH1041 - Week 12 Computer Test Information
In Week 12, there is a computer test that will be held in your Computer Lab Class. You must attempt the
test in the tutorial in which you are formally enrolled. This is the timetabled MATH1041 computer class
in
MATH1041
Statistics for the Life and Social Sciences
Semester 1, 2013
Assignment
Submission date: The start of your lab, week 12.
Please submit to your lab demonstrator.
Assignment length: No more than three singlesided A4 pages plus this cover sheet (to
Least-Squares Regression
0.1
Lectures 3-4: Least-Squares
Regression
Introduction
Least squares regression
Using the Least-Squares Line for Prediction
Connection Between Regression and Correlation
Measuring the Strength of a Regression: r2
0.2
Data an
Review Questions for Progress Exam 1
1. Microorganisms can impact on many areas of the food production and processing. What are
these areas?
2. What knowledge and skills does one need to have in order to be a competent food
microbiologist?
3. How would yo
Statistics for Life&Soc Science 1041 Assignment
Question1
A. (I) The parameter is
= the mean increase in heart rate after sprint.
And, the confident interval can be used to calculate the average different.
(II) The evidence that the average increase in my
1. Which hypothesis to use?
(A) Measured response (scalar / continuous)
STAT171 2016
2016
(B) Counted response (discrete variable)
Topic 12
12 = Last lecture
2. Inference and assumptions
Beware: this is Draft 4, and there may be typos
Independence of obse
COURSE OUTLINE
MATH1041
STATISTICS FOR LIFE
AND SOCIAL SCIENCES
Semester 1, 2016
Cricos Provider Code: 00098G Copyright 2016 -School of Mathematics and Statistics, UNSW Australia
Chapter 1
MATH1041 Course Outline
Welcome to MATH1041 Statistics for the Lif
COURSE OUTLINE
MATH1041
STATISTICS FOR LIFE
AND SOCIAL SCIENCES
Course Outline
Semester 2, 2015
Cricos Provider Code: 00098G Copyright 2015 -School of Mathematics and Statistics, UNSW
Chapter 1
MATH1041 Course Outline
Welcome to MATH1041 Statistics for th
Random variables
1.1
Lectures 1-2: Random variables
Random variables dened
Discrete random variables
The binomial distribution
Continuous random variables
Section 4.3 of Moore et al.
1.2
Random variables dened
A Random Variable is a variable whose val
Descriptive statistics
1.1
Course aims
This course provides an introduction to statistics: the study of collecting, analysing, and interpreting data.
Statistics plays a fundamental role in quantitative research (research
involving data). Some examples of
Means and variances
of random variables
1.26
Lectures 3-4: Means and variances
of random variables
The mean of a random variable
Rules for means
The variance of a random variable
Rules for variances of random variables
Other rules for means and varia
Copying comma separated values into Excel and R easily
This document will show how to copy the comma separated values from the graphic below into the software
packages Excel and R/RStudio. The easiest way to do this is via R/RStudio. Excel however, requir
Saving a graph made in Excel/R/Rstudio to a le
To save a graph made in either Excel, R or Rstudio. Follow the suggested instructions below.
1
RStudio
RStudio has the easiest way to save a PDFs.
Save File as PDF
Click the Export button at the top of the pl
Final exam information
2 hours, 4 questions, all questions equal value.
Please use a dierent exam booklet for each question!
You will be provided with formula sheets and statistical tables.
A skeleton exam showing the length and the formula sheet is
ava
III)In)III'IIIIIEIIIII
THE UNIVERSITY OF NEW SOUTH WALES
SCHOOL OF MATHEMATICS AND STATISTICS
Semester 2, 2012
MATH1041
STATISTICS FOR LIFE
AND SOCIAL SCIENCES
1) TIME ALLOWED — 2 hours
(
(2) TOTAL NUMBER OF QUESTIONS — 4
(3) ANSWER ALL QUESTIONS
(4) THE
THE UNIVERSITY OF NEW SOUTH WALES
SCHOOL OF MATHEMATICS AND STATISTICS
Semester 1, 2013
MATH1041
STATISTICS FOR LIFE
AND SOCIAL SCIENCES
(1) TIME ALLOWED — 2 hours
(2) TOTAL NUMBER OF QUESTIONS — 4
(3) ANSWER ALL QUESTIONS
(4) THE QUESTIONS ARE OF EQUAL V
THE UNIVERSITY OF NEW SOUTH WALES
SCHOOL OF MATHEMATICS AND STATISTICS
Semester 2, 2011
MATH1041
STATISTICS FOR LIFE
AND SOCIAL SCIENCES
(I) TIME ALLOWED 2 hours
(2) TOTAL NUMBER OF QUESTIONS - 4
(3) ANSWER ALL QUESTIONS
(4) THE QUESTIONS ARE OF EQUAL VAL
Welcome to MATH 1041:
Statistics for Life and Social
Sciences
0.1
General information
Lecturing and administration sta
Course Authority:
(Lecturer)
Justin Wishart
RC-1030
j.wishart@unsw.edu.au
Administration
First Year Oce
RC-3072
fy.MathsStats@unsw.edu.a
Design of experiments
1.1
Lectures 1-2: Design of experiments
Ways to obtain data
Observational studies vs experiments
Principles of experimental design
Types of experiments
Cautions about experiments
Chapter 3 Introduction and Section 3.1 of Moore e
Sampling designs
and toward statistical inference
2.2
Lectures 3-4: Sampling designs and
towards inference
Sampling designs (Section 3.2 of Moore et al.)
Introduction
The simple random sample (SRS)
Other sampling designs
Cautions about sample surveys
General Probability Rules
3.26
Lectures 3-4: General Probability
Rules
We will meet some useful probability rules, and the important idea of
conditional probability.
More addition rules
Conditional probability dened
Conditional probability and independ