Chi-Square Goodness of Fit Test
This lesson explains how to conduct a chi-square goodness of fit test. The
test is applied when you have one categorical variable from a single
population. It is used to determine whether sample data are consistent with a
h
How to Test the Equality of Variance /
Standard Deviation
We have seen how knowing if the variance of two populations are
equivalent plays a roll in determining what kind of a two-sample t-test we
perform.
Recall:
If 1 2
o We combine the two sample stand
Two-Way ANOVA with replication
The two-way analysis of variance is an extension to the one-way analysis of variance.
There are two independent variables (hence the name two-way).
Assumptions
The populations from which the samples were obtained must be nor
One-Way ANOVA
In statistics, one-way analysis of variance (abbreviated one-way ANOVA) is a technique used to compare
means of two or more samples (using the F distribution). This technique can be used only for numerical
data.
The ANOVA tests the null hypo
Multiple Linear Regression
We continue our study of regression analysis by considering
situations involving two or more independent variables. This subject
area, called multiple regression analysis, enables us to consider more
factors and thus obtain b
Chi-Square Test of Homogeneity
This lesson explains how to conduct a chi-square test of homogeneity. The
test is applied to a single categorical variable from two different populations.
It is used to determine whether frequency counts are distributed iden
Recap of Lecture 2
Recap of Lecture 2 with additional notes:
We want to estimate the population mean test score based on the data
70, 75, 74, 84, 80, 90, 83, 72, 68, 59, 60, 83,
78, 92, 77, 69, 75, 77, 73, 82, 82, 75, 74, 66, 67
We need to see if we can a
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half-ashamed of them. I respect what has been done. I respect the_
tention and the effort and the result. Accept my thanks. _
I [did think that I would write a letter to Hugo. sill the ti
Subject 2 Qualitative and Quantitative Data
STAT 213, Winter 2017
Instructor: Dr. Bingrui (Cindy) Sun
Department of Mathematics and Statistics
University of Calgary
Outline
2.1 Simple Random Sample
2.2 Qualitative/Categorical Data
2.3 Quantitative Data: C
Subject 7 One Sample Hypothesis Test
STAT 213, Winter 2017
Instructor: Dr. Bingrui (Cindy) Sun
Department of Mathematics and Statistics
University of Calgary
Outline
7.1 Hypothesis Test for Using the Z statistic, Type I error,
and PValues
7.2 Hypothesis T
Subject 6 One Sample Confidence Interval
Estimation
STAT 213, Winter 2017
Instructor: Dr. Bingrui (Cindy) Sun
Department of Mathematics and Statistics
University of Calgary
Outline
6.1 Confidence Interval for a Population Mean (): Normal (Z)
Statistic
6.2
Subject 1 Events and Probability
STAT 213 Winter 2017
Instructor: Dr. Bingrui (Cindy) Sun
Department of Mathematics and Statistics
University of Calgary
Outline
1.1 Experiment, Event, Sample Space, and Probability
1.2 Union and Interaction, Complementary
Subject 3 Discrete Random Variables
STAT 213, Winter 2017
Instructor: Dr. Bingrui (Cindy) Sun
Department of Mathematics and Statistics
University of Calgary
Outline
3.1 Probability Distributions for Discrete Random Variables
3.2 Expected Values of Discret
Subject 4 The Continuous Uniform and
Normal Distributions
STAT 213, Winter 2017
Instructor: Dr. Bingrui (Cindy) Sun
Department of Mathematics and Statistics
University of Calgary
Outline
4.1 The Uniform Distribution
4.2 The Normal Distribution
A continuou
Subject 8 Simple Linear Regression
STAT 213, Winter 2017
Instructor: Dr. Bingrui (Cindy) Sun
Department of Mathematics and Statistics
University of Calgary
Outline
8.1 Scatter-Plots, Correlation, Least Squares Method, Model
Parameters Interpretation
8.2 A
Subject 5 Sampling Distributions
STAT 213, Winter 2017
Instructor: Dr. Bingrui (Cindy) Sun
Department of Mathematics and Statistics
University of Calgary
Outline
5.1 Sampling Distribution of X
5.2 The Central Limit Theorem
A parameter is a numerical descr
Technical Support Document
Calculating Percentiles
You can use Minitab's Calculator (Calc > Calculator) to calculate percentiles of data. The example below
shows the specific calculations Minitab uses to determine the value of the percentile:
Suppose you
Hardeep Malhi
W2017STAT213L01L03
Assignment 2 is due on Friday, February 03, 2017 at 12:00pm.
The number of attempts available for each question is noted beside the question. If you are having trouble figuring out your error,
you should consult the textbo
Hardeep Malhi
W2017STAT213L01L03
Assignment 1 is due on Friday, January 27, 2017 at 12:00pm.
The number of attempts available for each question is noted beside the question. If you are having trouble figuring out your error,
you should consult the textboo
Page 0112 2
Long answer questions
(1a) You are the manager of an affordable light-bulb company. An average lifetime of a
100 Watts incandescent light bulb is 400 hours. Your testing department tested the
lifetime of 100 light bulbs to nd out that the samp
!
Practice questions for midterm #1!
1
Disclaimer: Just because a topic is not asked on these practice questions does not mean it will
not be on the midterm. It will take you longer than 50 minutes to do all of these questions but it
is a very good review
Q 7.20
The number of pizzas delivered to university students each month is a random
variable with the following probability distribution.
x
P(x)
0
0.1
1
0.3
2
0.4
3
0.2
a. Find the probability that a student has received delivery of two or more pizzas
thi
Chapters 4 and 5 Managing Technology and International
Technology is used in managing our operations. Data is collected, analyzed, and used to
make decisions moving the organization forward. Although there is an abundant amount
of data collected, sometime