Applications of the Central Limit Theorem
Reading for Sep 12 - 16: Sections 9.1 and 9.2
Read the Project Assignment and Rubric and start looking for a
suitable data set. (NOTE: You MAY use a data set from a project on
which you are working.)
Chapter 2 Hom
Experimental Design
STAT 6315
Professor Kaplan
19 & 22 Aug 2016
In an EXPERIMENTAL STUDY a researcher manipulates factors (or
explanatory variables) to create treatments, randomly assigns
subjects to treatments and then compares the response variables
acr
Foundational Vocabulary and Ideas
STAT 6315
Professor Kaplan
26 August 2016
What questions do you have?
Variable Type
Observational
Unit
Population
Sample
Parameter
Statistic
Sampling
Variability
Population
Distribution
Distribution of the
Sample
Sampling Distributions
Students did not
1. mention that Saturdays have the highest fatality rates
2. mention context explicitly when describing histograms and/or scatter plots.
3. describe the slope in predicted values or in the sense of average. In other
Margins of Error
Most of students did really well in recognizing the difference between observational study
and experimental study. There was only onestudent using parrot response. Most of them
were able to tie the reason to context.
For 2.34:
Most of the
Confidence Intervals
STAT 6315
Professor Kaplan
14 Sep 2016
What is the relationship between the margin of error, the sample size, and the confidence
level of a confidence interval?
How do we interpret the confidence level?
Creating Confidence Intervals f
STAT 6315
Statistical Methods for Researchers
Professor Jennifer Kaplan
Fall 2016
11 Aug 16
Outline for the Day
Overview of STAT 6315 and the Investigative
Cycle including a Brief Tour of eLC and the
syllabus
Dolphin Therapy Activity
Plan to work about
Gettysburg Address
(Random Sampling)
Professor Jennifer Kaplan
Fall 2016
15 Aug 16
Task: Estimate the mean word length for all of the
words in the Gettysburg address.
Part a: Make a guess
Parts b - f: Circle 10 words, and complete through part f.
Task: Es
Distributions of Random Variables
Gaussian Distributions
STAT 6315
Professor Kaplan
27 Jan 2016
Named distributions of Random Variables that we will see this semester.
Categorical
Bernoulli
Quantitative
Discrete
Continuous
Binomial
Uniform
Uniform
Gaussia
Sampling Variability
Tasks:
1. Bead Box Sampling
2. Add your Bead Box Sample results to the class dot plot
3. Create the dot plots for the price and weight for each of
the diamond samples
4. Calculate the mean of price and weight for each sample
of diamon
Binomial Random Variables
Issues from Homework 1: Chapter 4
1. Students described the distribution/skew of categorical variable
2. Students interpreted the mean from the boxplot instead of median
3. Students tend you use the range of the data rather than
STAT 4220
Lab 1 - Introduction to R
Acknowledgement: T. N. Sriram
Here, we will learn some of the basics of R software. To begin with, let us learn how to
access a data that is in a folder called K:/Course Data/4220/Lab; this will be referred to
as the wo
STAT 2000
Chapter 3: Association: Correlation and Regression
Response variable a variable that can be explained by, or is determined by, another variable.
When the two variables are quantitative, the response variable will be the y-variable, the
variable
STAT 2000
Chapter 6: Probability Distributions
6.1 Summarizing Possible Outcomes and Their Probabilities
A probability distribution tells you all possible values and how their probabilities are
distributed. A quick example, using eye color: 60% of people
STAT 2000
Chapter 8: Statistical Inference: Confidence Intervals _
A simplistic, intuitive way to think about statistical inference:
If I know whats in a box, I can predict what comes out of the box by sampling
randomly. This means that if I know the popu
STAT 2000
Chapter 7: Sampling Distributions_
7.1 How Sample Proportions Vary Around the Population Proportion
To learn more about the variability, we have to imagine. We dont know the value of the true
proportion of an event in the population. But it is i
STAT 2000
Chapter 9: Statistical Inference: Significance Tests About Hypotheses_
9.1 Steps for Performing a Significance Test (Hypothesis Test)
1.
2.
3.
4.
Hypotheses
Conditions for Model
Mechanics
Conclusions
9.2 Significance Tests (Hypothesis Tests) Abo
STAT 2000
Spring 2016
Ch. 5 and 6 Review Problems
Problem 5.1 A restaurant randomly selects 50 patrons from the previous month and records (1)
how long each patron waited for his/her food and (2) how much the patron tipped his/her
waiter/waitress.
Tip 20%
Step 1: Install Oracle VirtualBox and download the SAS University Edition vApp.
a. Download Oracle VirtualBox version 4.3.12 from the link below. Important: make sure you
download version 4.3.12. Also, make sure you download the appropriate version for yo
GEORGIA ASSET CERTIFICATION
Complete only one form per household; include assets of children.
Household Name: Chang
Development Name: Sugarloaf Trails Apartments
City: Duluth
1. Choose only ONE response:
a
I(we) do not have any family assets (as defined i
STAT 4360
Assignment 4
(Due 5:00pm, Monday, October 10, 2016)
Instruction:
Type your answers in a word .doc file and convert it into PDF file. You also need to
provide relevant SAS codes for each question in one .SAS file. Make sure your files
named as ST
Schedule for Lab 307, Statistics Building
Fall 2016
Sun. Time
Period
M,W,F Time
T,Th Time
Sunday
Monday
Tuesday
8/5/2016
Wednesday
Thursday
Friday
1
8:00-8:50 AM
8:00-9:15 AM
Closed
Open
Open
Open
Open
Open
2
9:05-9:55 AM 9:30-10:45 AM
Closed
4/6240 (Wern
10.2 comparing independent means
10.4 comparing dependent means
Independent: no obvious relationship between samples
Dependent: you have two measurements per person/case
Ex: before and after
Chapter 10: Comparing Two Groups_
10.1 Categorical Response: Com
STAT 2000
Chapter 8: Statistical Inference: Confidence Intervals _
A simplistic, intuitive way to think about statistical inference:
If I know whats in a box, I can predict what comes out of the box by sampling
randomly. This means that if I know the popu
STAT 2000
Chapter 11: Analyzing the Association Between Categorical Variables
In practice, the chi-squared statistic is used for a variety of hypotheses about categorical
variables. For example, we can test a hypothesis involving a single categorical vari
STAT 2000
Chapter 6: Probability Distributions
6.1 Summarizing Possible Outcomes and Their Probabilities
A probability distribution tells you all possible values and how their probabilities are
distributed. A quick example, using eye color: 60% of people
STAT 2000
Chapter 7: Sampling Distributions_
7.1 How Sample Proportions Vary Around the Population Proportion: Sampling Distribution of the
Sample Proportion
Sample is part of population
Mean proportion
Population
sample
P
P hat(> on top)
have multiple P
STAT 2000
Chapter 5: Probability in Our Daily Lives_
5.1 How Probability Quantifies Randomness
Probability allows us to make the jump from simply describing a sample to drawing conclusions,
or inferences, about the population. The purpose of this chapter
STAT 2000
Chapter 9: Statistical Inference: Significance Tests About Hypotheses_
9.1 Steps for Performing a Significance Test (Hypothesis Test)
1.
2.
3.
4.
Hypotheses
Conditions for Model
Mechanics
Conclusions
Statistical inference: 1.C.I. 2. Hypothesis t
9.3 Significance Tests (Hypothesis Tests) About Means
Make inference about population mean Mu using sampling distribution
Hypothesis Test Steps for a Single Mean
1. Hypotheses: difference is its about mu, not x-bar
H0 : = 0
null hypothesis
Ha : < 0
Ha : >