Lecture 1 Workshop (week beginning 11 March, 2013)
Business and Economic Statistics B
Question 1
Which of the following would we term binary data?
(a)
Whether a woman in Australia worked full time last financial year, or
otherwise
(b)
The number of hours
ECMT1020: Introduction to Econometrics
Sample solutions for Assignment 1
Question 1. This question is worth ten points.
During the lectures, we have discussed three things that can be called a mean. Explain carefully what
and x
the differences are betwee
Lecture 2 Workshop (week beginning 18 March, 2013)
Computer Workshop
Business and Economic Statistics B
Question 1
Which of the following would we term categorical data?
(a) How many magazines were purchased in Australia last month
(b) Most widely read m
ECMT1020: Student Requests
Adam J. Smith
June 12, 2013
Quite a few students emailed me with questions or topics they wanted me to cover in the
nal lecture. Given time constraints I could not answer them all in two hours, so I will address
the rest here.
A
Question 1 (10 points)
The top graph below shows the distribution of the random variable X. The median of X is -5,
the mean of X is 5 , the mode of X is -10 and the variance of X is 25. On the lower graph,
draw the distribution for the sample mean of X (
ECMT1020 Written Assignment
Due 2pm Friday June 7, 2013
Instructions
In order to complete this assignment, you will need the data set Film data.xls.
This assignment must be done alone and is worth 10% of your final mark.
You will be marked on the corre
Lecture 6 Workshop (week beginning 22 April, 2013)
Business and Economic Statistics B
Questions 1 3 are based on the following EXCEL output.
For the following regression model:
Yi = 0 + 1X1i + 2X2i + 3X3i +
the estimated regression results (below) were o
ECMT 1020
Lecture 10
Time Series Analysis
Topics covered
1. Introduction to Time Series
2. Time Series Forecasting
3. Moving averages
4. Exponential Smoothing
5. Seasonal Indices
References
Black 16.1, 16.2, 16.4
Excel file: Lecture 10.xls
Must read
Bl
Lecture 11 Workshop (week beginning 27 May, 2013)
Computer Workshop
Business and Economic Statistics B
Question 1
(a)
Which non-parametric test is an alternative to the t test for two independent
samples?
(b)
Which non-parametric test is an alternative t
Question 1 (10 points)
The top graph below shows the distribution of the random variable X. The median of X is -5,
the mean of X is 5 , the mode of X is -10 and the variance of X is 25. On the lower graph,
draw the distribution for the sample mean of X (
Mann-Whitney U Test
Two-Tail Test
Mann-Whitney U Test
One Tail Test
Urban
Rural
$2,110
$2,050
2655
2800
2710
2975
Alternative Hypothesis:
Not Identical
2540
2075
0.05
2200
2,520
Level of Significance =
n1 =
2175
2585
$1,950
$2,760
2480
2630
Alternative Hy
utorial T 1Workshop Wednesday6 thJanuary
ECMT 1020 - Business and Economic Statistics B
Aim: To extend the notion of hypothesis testing to proportions
Instructions: 1. Complete the "Learning the Concepts" questions BEFORE attending your workshop. (The q
ECMT1020: Revision Lecture
Adam James Smith
Presented 7 June 2013
Exam Tips
Requests
Time Series
ANOVA
Non-Parametric Statistics
Table of contents
1
Exam Tips
2
Requests
3
Time Series
4
ANOVA
5
Non-Parametric Statistics
Adam James Smith
ECMT1020 Revision
ECMT1020
Chapter 11
Time Series Analysis
Dr Boris Choy for ECMT1020
Dr Boris Choy
ECMT1020: Chapter 11
1
Topics covered
1. Introduction to Time Series
2. Time Series Forecasting
3. Moving averages
4. Exponential Smoothing
5. Seasonal Indices
References
Question 1
5 out of 5 points
The bivariate distribution of the random variables X and Y is shown in the following table.
Compute the covariance between X and Y.
X
X
Tot
=
=
al
Selected0
1
Answer:
0.1
0
Y=
0.4 0.1
0.5
0
Answers:
0
Y=
0.2 0.3
0.0 0.5
1
9
To
Question 1
That the starting salaries of new accounting graduates would differ according to geographic regions of
Australia seems logical. A random selection of accounting firms is taken from three geographic regions, and
each is asked to state the starti
STUDENT ID: _
SURNAME: _
GIVEN NAMES: _
ECMT 1020 Introductory Econometrics
Mid Semester Examination
Semester 1, May 2015
Time allowed: 90 minutes.
This examination paper consists of 16 pages.
Instructions
1.Write your name and student number at the top o
Tutorial5ComputerWorkshop
Wednesday20thJanuary,2010
ECMT 1020 - Business and Economic Statistics B
Aim: To extend the students from simple regression to multiple regression. To enable students to estimate a multiple regression model in EXCEL and interpret
ECMT1020 online quiz 1
Q1 Solve for the probabilities of the following binomial distribution problems by using the binomial
formula.
Round your answers to 4 decimal places.
a. If n = 11 and p = 0.20, find = .
b. If n = 6 and p = 0.52, find = .
c. If n = 9
Lecture 10 Workshop (week beginning 27 May, 2013)
Computer Workshop
Business and Economic Statistics B
Text references are to the second edition of Black et. al.
t
yt
1
5
2
3
3
4
4
6
5
4
6
6
7
7
Question 1
Compute the 3-point moving average for the time
Control Charts
1. Introduction
Review
A manufacturer produces bolts. He wishes to sell bolts having a mean diameter of 10cm. Diameters are
normally distributed with a standard deviation of 0.2cm.
A sample of 16 bolts produced a mean of 10.089cm. Does this
Some Extensions to and Some Difficulties in
the Multiple Regression Model (cont.)
5. Polynomial Regression
a. Types
First Order
Y = 0 + 1X +
Second Order
Y = 0 + 1X + 2X2 +
Third Order
Y = 0 + 1X + 2X2 + 3X3 +
kth Order
Y = 0 + 1X + 2X2 + 3X3 + + kXk +
Analysis of Variance (ANOVA)
1 The problem
(a) Introduction.
In a truly global market place, there should be little difference between the profitability of firms in different
countries
Profitability
Year Germany
Japan
US
1
8.86
8.48
15.24
2
10.56
10.40
12
Nonparametric Statistics
1 Introduction
The statistical methods we have used so far (except for one instance) are known as parametric methods.
These methods begin with an assumption about the probability distribution of the population. The
method that did
Variables
Dependent
Independent
y
X
Regression and Correlation
Observations
R Square
Standard Error
Adjusted R Square
Multiple R
10
0.9726
4.9303
0.9692
0.9862
Coefficients
Intercept
X
df
ANOVA
MS
F
p value
1
6901.7976 6901.7976 283.9338 0.0000
8
194.4621
71
Chapter 5 - Partial Differentiation
Economic agents are generally assumed to act rationally, that is, to make choices so that
outcomes are in some sense optimised. For example, consumers act to maximise utility,
firms make decisions to maximise profits
Applied Business Forecasting
and Planning
Simple Linear Regression
Simple Regression
Simple regression analysis is a statistical tool That
gives us the ability to estimate the mathematical
relationship between a dependent variable (usually
called y) and a
Matrices
1. Introduction
A matrix is a rectangular array of information
An example is a table. Black p487
Age
<30
30-50
>50
Gender
M F
32
25
18
5
17
3
A matrix is generally of numbers so the matrix here would be
32 25
18 5
17 3
Some other examples a
RecapWeek3Chapter57;ReviewofConfidenceIntervalandHypothesisTestinginUnivariateCase
ECMT 1020: Introduction to Econometrics
Lecture 4
Instructor: Kadir Atalay
Contact: [email protected]
School of Economics
The University of Sydney
Week 3 Recap
Rec
University of Sydney
School of Economics
ECMT 1020
Tutorial #10 Week 11
Q1
The Stata data set traffic.dta contains information on the number of vehicles counted
on two nearby highway intersections, as well as the number of accidents reported on the
sectio
University of Sydney
School of Economics
Semester 2, 2016
Tutorial #6 Week 7
ECMT 1020
Question 1 Indicator (Dummy) Variables : Use Earnings Data.
a) Consider the earnings data and create an indicator variable (dage) for whether or not a person
is more th
University of Sydney
School of Economics
ECMT 1020
Semester 1, 2016
Tutorial #3 Week 4
Kadir Atalay
Chapters 6-7-8
SOLUTIONS
Q1
For a random variable T that is T (30) distributed,
1.3
1.3
0.80. Using this
result, derive an 80% confidence interval for the
University of Sydney
School of Economics
ECMT 1020
Tutorial #9 Week 10
Q1
The output shows the result of regressing FDHO, expenditure on food consumed at home, on
EXP, total household expenditure, and SIZE, number of persons in the household, using the
US