COMM 291 Application of Statistics in Business (JanApr 2014)
ASSIGNMENT 2 Submit On-line to Connect
Due 1:00 pm, Wednesday, February 5, 2014
Instructions and Advice:
This assignment comprises four questions: All four questions use data from the
accompanyi
PRACTICE QUESTIONS FOR
THE MIDTERM EXAM
Part A.
Midterm Exam 2013
Midterm Exam 2012
Midterm Exam 2011
Midterm Exam 2010
Questions, Answers and Explanations
Part B.
Past Years Midterm Exams
Questions, Answers and Explanations
1
Part A. Midterm Exam 2013
No
COMM 291 Application of Statistics in Business (JanApr 2014)
ASSIGNMENT 4 Submit On-line to Connect
Due 1:00 pm, Wednesday, March 12, 2014
Instructions and Advice:
IMPORTANT! Submit your solutions as a PDF (not as a Word or Excel file).
The assignment con
COMM 291
FINAL EXAM
SOLUTIONS
Visit www.BeatYourCourse.com for all your tutoring needs
BYC IS NOT AFFILIATED WITH UBC
Practice(Question(1A
Binary
Categorical
Nominal
Ordinal
Quantitative
Identifier
X
Postal0Code
Liberal0Party
Application0Denied
Size08
Siz
COMM 291 REVIEW SESSION
BY KENNY WU
T ABLE OF C ONTENTS
I.
II.
III.
IV.
V.
VI.
VII.
VIII.
IX.
X.
XI.
Data & Variables
Surveys & Sampling
Displaying Categorical Data
Displaying Quantitative Data
Correlation and Regression
Probability
The Normal Model
Sampl
COMM 291 REVIEW SESSION
BY KENNY WU
T ABLE OF C ONTENTS
I.
II.
III.
IV.
V.
VI.
VII.
Condensed Pre-Midterm Material
Testing Hypotheses for Means
Comparing Two Means
Comparing Two Proportions
Goodness of Fit Tests
Linear Regression Relationships
Multiple Re
SD
Mean
1.6
Between
25 and
30
35
Right
Lef
Probability
0.99822195 or
99.82%
SD
Mean
8
Lef Side
200
And
185
Right Side
215
Right
Lef
Probability
0.06079272 or
6.08%
SD
Mean
100
Right Side
500
725
Right
Probability
0.01222447 or
1.22%
SD
Mean
0.4
Lef Side
2
SD
Mean
1.6
Between
25 and
30
35
Right
Lef
Probability
0.99822195 or
99.82%
SD
Mean
8
Lef Side
200
And
Right Side
215
185
Right
Lef
Probability
0.06079272 or
6.08%
SD
Mean
28
Right Side
120
155.8
Right
Probability
0.10052401
SD
Mean
0.4
Lef Side
0.08
-1.4
0.30854
0.6915
69.15%
area to the left of a point
x, mean,sd, 1
or with true
given x -finding prob
area to right
precentage
0.9088
like the table just on excel:
to find the distribution under curve:
0.1151
given z - find prob
unstandardize
11.8679
given p
COMM291 - Chapter 2 - Data
2.1 What Are Data?
Data are the things given for us to turn into information.
- on its own, data can be very messy, you should sort it to at context in a data table
- The rows of data table correspond to individual cases (record
COMM291 - Chapter 10 - Testing Hypotheses about Proportions
10.1 Hypotheses
- this is something that is supposed in order to draw a conclusion or inference for proof of the
point in question
- When looking at hypothesis we have 2
- The null hypothesis is
COMM291 - Chapter 3 - Surveys and Sampling
3.1 Three Ideas of Sampling
Idea 1: Examine a Part of the Whole
- since it is not practical for most to interview whole population of a population, most interview a
sample selected from the population
- a sample
COMM291 - Chapter 9 - Sampling Distributions and Confidence Intervals for Proportions
9.1 Simulations
- a simulation is basically just pretending to test a random sample
- a simulation can help understand how sample proportions are due to random sampling
COMM291 - Chapter 4 - Displaying and Describing Categorical Data
4.1 The Three Rules of Data Analysis
1. Make a Picture
- to display your data will help you see things you may not see in a table of numbers and will
help plan approach
2. Make a picture
3.
COMM291 - Chapter 6 - Correlation and Linear Regression
6.1 Looking at Scatterplots
- When looking at scatterplots what do you see?
- First you might say the direction of the association is important
- upper left to lower right is negative
- bottom left t
COMM291 - Chapter 5 - Displaying and Describing Quantitative Data
5.1 Displaying Distributions
- distribution gives the possible values of a variable and the frequency/relative frequency of
each value
Histograms
- histogram plots the bin counts as the hei
COMM291 - Chapter 7 - Randomness and Probability
7.1 Random Phenomena and Probability
- with random phenomena, we cant predict the individual outcomes but we can hope to
understand characteristics of their long-run behaviour
- ex. we don't know how many p
COMMERCE 291 Lecture Notes 2014 Jonathan Berkowitz
Not to be copied, used, or revised without explicit written permission from the copyright owner.
Summary of Lectures 13, 14, and 15
Setting the stage for statistical inference:
We previously defined (in C
COMMERCE 291 Lecture Notes Jonathan Berkowitz (copyright, 2014)
Summary of Lectures 11 and 12
In Lecture 9 (textbook: Chapter 9) we discussed a set of rules for computing the mean,
the variance and the standard deviation of combinations of random variable
COMMERCE 291 Lecture Notes Jonathan Berkowitz (copyright, 2014)
Summary of Lectures 9 and 10
Chapter 8. Randomness and Probability
We only need two concepts from Chapter 8. What is meant by random and what is
meant by probability?
Random individual outcom
You will always get the same conclusion from a normal hypothesis test
and a CI hypothesis test if you use the same significance level. If not, you
may get different conclusions.
Previously, this
question was at the
1% significance
level, and in that
case
COMMERCE 291 Lecture Notes Jonathan Berkowitz (copyright, 2014)
Summary of Lectures 9 and 10
Chapter 8. Randomness and Probability
We only need two concepts from Chapter 8. What is meant by random and what is
meant by probability?
Random individual outcom
Statistics Made Simple
CI for Proportions
P-hat
0.35
Q-hat
0.65
N
# Success
Confidence
100
35
95%
Z-Stat
# Side
P-value
0.0476969601
Standard Error
Z*
Lower Bound
Upper Bound
1.9599639845
0.25652
0.44348
CI for Means
X-bar
43.04
S
26.66383
N
DF
Confidence
COMM 291 Application of Statistics in Business (JanApr 2014)
ASSIGNMENT 5 Submit On-line to Connect
Due 1:00 pm, Wednesday, March 26, 2014
Instructions and Advice:
IMPORTANT! Submit your solutions as a PDF (NOT as a Word or Excel file).
The assignment con
Stat note compilation
Variable a characteristic recorded about an individual
Data specific values of a variable
Observations another word for data
Data table an arrangement of data in rows and columns; also called a
spreadsheet
Record a row in a spreadshe
COMM291 - Chapter 8 - Random Variables and Probability Models
8.1 Expected Value of a Random Variable - 212
- a random variable is called an RV because its value is based upon outcome of a random
event
- if we can list all the outcomes, this is called a d