Stat 203: Statistical Methods
Lecture 12
Sep 29, 2014
Shannon Erdelyi
Department of Statistics,
UBC
Announcements
Assignment 1 released today
Solutions can be neatly hand-written or typed
Due Friday, October 10 at 1:00pm IN CLASS
Include the standard cove
[22 points] Part 1: Multiple Choice
Choose the most appropriate answer for each question.
1. There are three children aged 7, 8 and 9 in a room. If another 7-year-old enters the room, what
will happen to the mean and variance?
(a)
(b)
(c)
(d)
(e)
The
The
Assignment 1
STAT 203 - 103
Due: 1:00pm on Friday, October 10
Total Marks: 32
1. Data and context (3 marks): To investigate personality and self-perception, I surveyed 64
students enrolled in STAT 203
Statistical Inferencing yields Estimation Error
Estimation error is the difference between a factual population result and the result of a sample
taken from that population. Take the N=100 adults as discussed above for example. If we
measured the heights
Cluster Random Sample - Take the same example yet again, and this time randomly order the group
of 100 adults. Then, divide them into 4 equal groups (clusters) of 25 each. Then, number the groups 1,
2, 3, 4 and using a random number table select 2 of the
Quiz 2 Numerical descriptive statistics and sampling
1. The following marks are the test 1 marks for 10 randomly selected STA100 students:
67, 34, 98, 78, 76, 55, 80, 49, 91, 66. What is the mean mark for this sample?
a. 69.1
*b. 69.4
c. 62.2
d. 70.3
e. 7
What is bias?
Bias is the tendency of a sample to differ from its population is some systematic way. There are
3 types of bias:
1. Selection Bias - Exclusion of some part of the population.
2. Measurement or Response Bias - Sample measurements that system
Ways of Gathering Data
1. Census - Look at every object or individual in the population.
Advantages: We know everything exactly! (Factual information)
Disadvantages: It may require a lot of resources (time, money, effort); and it may be
impossible to acce
Population and Sample
Def. Population - The entire collection of elements about which information is desired.
Example: All students enrolled in Stat 141 OL this summer.
Def. Sample - A subset of the population of interest.
Example: A selection of only 10
STAT 203 Statistical Methods
2014/15 Term 1
Calendar description: Organizing, displaying and summarizing data. Inference estimation and
testing for elementary probability models.
Objectives: Detailed aims and objectives for this course will be found in a
Stat 203: Statistical Methods
Lecture 10
Sep 24, 2014
Shannon Erdelyi
Department of Statistics,
UBC
Announcements
No tutorials this week
TAs will hold office hours during tutorial times instead
Overview
Last Class:
5-Number Summary and Boxplots
This Class
Stat 203: Statistical Methods
Lecture 9
Sep 22, 2014
Shannon Erdelyi
Department of Statistics,
UBC
Announcements
No tutorials this week
TAs will hold office hours during tutorial times instead
Graphing calculator left here on Friday is in the main
office
Stat 203: Statistical Methods
Lecture 7
Sep 17, 2014
Shannon Erdelyi
Department of Statistics,
UBC
Announcements
WeBWork HW01 due Sunday, Sep 21 at 11:59 PM
Lecture slides
Will be updated after lectures with solutions to
exercises/examples
Will be posted
Stat 203: Statistical Methods
Lecture 6
Sep 15, 2014
Shannon Erdelyi
Department of Statistics,
UBC
Announcements
WeBWork HW01 due Sunday, Sep 21 at 11:59 PM
Tomorrow (Sep 16) is the last day to withdraw without a
W standing
Formal clicker questions will s
Stat 203: Sta)s)cal Methods
Lecture 5
Sep 12, 2014
Shannon Erdelyi
Department of Sta)s)cs, UBC
Announcements
Online homework posted at 2:00PM on Connect
WeBWork link in the naviga)on menu on the leJ
Due nex
Stat 203: Statistical Methods
Lecture 1
Sep 3, 2014
Shannon Erdelyi
Department of Statistics, UBC
Welcome to the Course
Instructor: Shannon Erdelyi
Email: [email protected]
Subject line: stat203
Class times: MWF 1-2 PM in ESB 1012
Office Hours: T
Stat 203: Statistical Methods
Lecture 3
Sep 8, 2014
Shannon Erdelyi
Department of Statistics, UBC
Announcements
Complete the beginning of term survey
Linguistics students: switch to tutorial section T1E (W 11-12) if
possible
Lecture slides will be post
Stat 203: Statistical Methods
Lecture 4
Sep 10, 2014
Shannon Erdelyi
Department of Statistics, UBC
Announcements
In-class activity on Friday
Bring paper, pen/pencil, calculator
Registered clicker list has been posted under Course
Information on Connect
Lecture 5: In-class Activity
Understanding Categorical Data
Nike is releasing a new shoe, and wants to team up with a leading beverage company to help market it.
Nike has narrowed it down to Coke and Pepsi. The c
Lecture 1: Statistics and Data
Recall the definition of Statistics: the science of collecting, organizing, summarizing, analyzing
and interpreting numerical information called data.
Three Major Roles of Statistics
1. Summarize and display information
2. I
Random Samples
The best way to create a representative sample is to use some form of random selection of
the sample.
A Random Sample is a sample of n elements from a population where every element in the
population has an equal chance of being selected to
STAT 203
Comparing Data
Distributions
Dr. Bruce Dunham
Department of
Statistics
UBC
Describing Data
Distributions
We have discussed displaying data
distributions for a quantitative variable.
Methods introduced include histograms,
stem-and-leaf plots, an
STAT 203
Standardizing,
Shifting, and Rescaling
Dr. Bruce Dunham
Department of
Statistics
UBC
Comparing Data Values
Sometimes we must compare data
sets that are very different.
E.g., athletes in the decathlon
score points for their performances
on each
STAT 203
The Normal Model
Dr. Bruce Dunham
Department of
Statistics
UBC
1. One ounce (oz) is 28.3 g. A sample of
20 handmade chocolate bars from a shop
have weights with standard deviation 0.22
oz. In squared grams, what is the variance
of the weights?
A.