149
Lecture 15:
CHAPTER 6: HYPOTHESIS TESTING
In Section 6.1, I described a method for testing a hypothesis about a
population mean, based on a large sample. Recall the null and
alternative hypothesis:
Null and alternative hypotheses:
A null hypothesis is
52
Lecture 5:
CHAPTER 2: PROBABILITY
Random Variables (Section 2.4, page 88)
Definition:
A numerical characteristic whose value depends on the outcome of a
chance experiment is called a random variable. A random variable
is discrete if its possible values
163
Lecture 17
CHAPTER 6: HYPOTHESIS TESTING
Small-Sample Tests for the Difference Between
Two Means Contd (Section 6.7, page 430)
When the Populations Have Equal Variances
Suppose that a srs of size n1 is drawn from a normal population with
unknown mean
201
Lecture 20:
SAS!
Lets first start off with some basic data input with SAS. Open your
SAS Stats program.
SAS CODE: (columns)
data one;
input id x;
cards;
1
2
3
4
5
6
7
8
9
10
run;
23
43
66
31
28
73
92
19
33
55
proc print;
run;
SAS OUTPUT:
Obs
id
x
1
2
215
Lecture 21:
MORE SAS
Example: A sample of 10 diesel trucks were run both hot and cold to
estimate the difference in fuel economy. The results, in mi/gal, are
presented in the following table. (From in-sue Emissions from
Heavy-Duty Diesel Vehicles, J.
1. Economics is the social science that studies the choices that individuals, businesses,
governments, and the entire societies make as they cope with scarcity.
2.
3. Goods and services are the objects that people value and produce to satisfy human wants
Module 5
I hope you are starting to notice the trend in how things are going. This module is
divided into 2 sections: A. Monopoly (Chapter 13) and B. Monopolistic Competition
(Chapter 14). Once again, the following is the "to do list" and again I have not
Microeconomics Module 3 Answers
1. A rent ceiling is a government regulation that makes it illegal to charge a rent higher than a
specified level.
Without a rent ceiling, the rent in the housing market is $450 per unit per month.
When the rent ceiling is
Module 6
2. The market for batteries has a small number of independent firms.
Each firm's actions influence the profits of the other firms.
The market for batteries is an oligopoly.
It has a small number of firms competing and a natural barrier preventing
Module 5 Assignment
1. A single-price monopoly is a firm that must sell each unit of its output for the same price to all its
customers.
A price-discriminating monopoly sells different units of a good or service for different prices.
When a firm price dis
Award: 0 out of 5.00 points
MC Qu. 07-05
There are six employees at a coffee house. Two employees are to be selected at random to attend a Fair
Trade coffee convention. What is the total number of samples of 2 that can be selected from this population?
01
238
Lecture 23:
CHAPTER 10: STATISTICAL QUALITY
CONTROL
Control Charts for Variables Contd (Section
10.2, page 757)
Recall: Control charts used for continuous variables are called
variables control charts. ( X chart, R chart, and the S chart.)
Control cha
227
Lecture 22:
CHAPTER 10: STATISTICAL QUALITY
CONTROL
Control Charts for Variables (Section 10.2, page
757)
Recall: Control charts used for continuous variables are called
variables control charts. ( X chart, R chart, and the S chart.)
Control charts us
189
Lecture 19:
CHAPTER 7: CORRELATION AND SIMPLE
LINEAR REGRESSION
The Least-Squares Line (Section 7.2, page 517)
Last class, we took a look at regression analysis which uses
information about x to draw some type of conclusion concerning y .
The linear m
12
Lecture 2:
CHAPTER 1: SAMPLING AND DESCRIPTIVE
STATISTICS
Graphical Summaries (Section 1.3, page 25)
Stem-and-Leaf Plots
Most of us already know what a histogram looks like:
A histogram tells us how many observations fall into a
particular class, but w
26
Lecture 3:
CHAPTER 2: PROBABILITY
A chance experiment, also called a random experiment, is
simply an activity or situation whose outcomes, to some
degree, depend on chance. To decide whether a given
activity qualifies as a chance experiment, ask yourse
38
Lecture 4:
CHAPTER 2: PROBABILITY
Counting Methods (Section 2.2, page 62)
Permutations:
In how many ways can you order the letters A, B, C?
Five lifeguards are available for duty one Saturday
afternoon. There are three lifeguard stations. In how many
w
62
Lecture 6:
CHAPTER 2: PROBABILITY
Random Variables Contd (Section 2.4, page 88)
Recall: Last class we started setting up discrete random
variables and we also worked with continuous random variables,
lets continue with both:
Example: Two cards are draw
72
Lecture 7:
CHAPTER 4: COMMONLY USED
DISTRIBUTIONS
The Binomial Distribution Contd (Section 4.2,
page 202)
THE BINOMIAL DISTRIBUTION (discrete)
Recall: p(x) = proportion of batches with x Ss (successes)
Summary for Binomial Distribution:
If a total of n
79
Lecture 8:
CHAPTER 4: COMMONLY USED
DISTRIBUTIONS
The Normal Distribution (Section 4.5, page 240)
Definition
A continuous variable x is said to have a normal distribution with
parameters and , where and 0 , if the
density function of x is
f ( x)
2
1
e
86
Lecture 9:
CHAPTER 4: COMMONLY USED
DISTRIBUTIONS
The Normal Distribution- Contd (Section 4.5, page
240)
Recall: Last class we focused on applications with the use of the
Normal Distribution. Now lets take a look at the mean and variance
for a Normal R
95
Lecture 10:
CHAPTER 4: COMMONLY USED
DISTRIBUTIONS
The Exponential Distribution Contd (Section
4.7, page 261)
Recall: Last class we introduced the Exponential distribution:
Definition
A variable X is said to have an exponential distribution with
parame
105
Lecture 11:
CHAPTER 4: COMMONLY USED
DISTRIBUTIONS
The Central Limit Theorem (Section 4.11, page
289)
The Central Limit Theorem is by far the most important result in
statistics. Many commonly used statistical methods rely on this
theorem for their va
115
Lecture 12:
CHAPTER 5: CONFIDENCE INTERVALS
Large-Sample Confidence Intervals for a
Population Mean Contd (Section 5.1, page 323)
Recall: Last class, we took a look at the most common confidence
intervals:
Summary
Let X 1 ,., X n be a large (n 30) ran
127
Lecture 13:
CHAPTER 5: CONFIDENCE INTERVALS
Small-Sample Confidence Intervals for a
Population Mean Contd (Section 5.3, page 321)
Recall: Last class we introduced the students t-distribution which is
used when the population is approximately normal an
139
Lecture 14:
CHAPTER 6: HYPOTHESIS TESTING
Example: Consider the population of weights (in kg) of all newborn
babies in Canada for a particular year. In this case, the Population
Mean is the average weight of all newborns in the population. An
investig