Chapter 3 - Measurements, Mistakes, and Misunderstandings
Thursday, September 05, 2013
4:36 PM
Simple Measure Do Not Exist
Consider finding out if people exercise?
Words can be a problem:
(1) Deliberate Bias
When surveys are conducts for particular caus
Intro to Probability and
Statistics Review: Exam 1
Things covered in this
session:
Seeing Through Statistics chapter 1-10,
which include
Calculating mean, variance, and standard deviation
Which graph is the best to convey information
Experiments, observat
Exam 2 Review
Jason Wilson, Ph.D
Biola University
Course
map
Data
Collectio
n
Variables
(Ch 3)
Observation
al Study
(Ch 4-5)
Experiment
(Ch 5-6)
Survey
Statistic
s
Descriptiv
e
Statistics
Measures of
center
(Ch 7)
Measures of
spread
(Ch 7)
Graphs (Ch 9)
D
Intro to Probability and
Statistics Review
Exam #2
Topics covered on Exam 2
Correlation Coefficient
Probability
Coincidence
o
Expected value
o
Law of small numbers
o
Confusion of the inverse
Central Limit Theorem
Confidence Intervals
Things to know
Correl
Introduction to Probability
and Statistics
Exam 3 Review
Jason Wilson, Ph.D
Biola University
1
Course
map
Data
Collectio
n
Variables
(Ch 3)
Observation
al Study
(Ch 4-5)
Experiment
(Ch 5-6)
Survey
Statistic
s
Descriptiv
e
Statistics
Measures of
center
(Ch
Section 5.1
What is Probability?
(1) A random phenomenon is one in which the outcome is unpredictable.
The sample space of a random phenomenon is the set of all possible outcomes.
An event is a collection of one or more outcomes of a random phenomenon.
A
Section 8.1
Estimating When Is Known
(1) A point estimate of a parameter is a specific numerical value used to estimate
the parameter. This value may or may not be equal to the true value of the
parameter.
Example: The sample mean x can be used as a point
Section 2.1
I.
Frequency Distributions and Histograms
Frequency Tables
A. A frequency table partitions data into classes or intervals of equal width and shows how
many data values are in each class. The classes or intervals are constructed so that each da
Section 7.1
Graphs of Normal Probability Distributions
(1) Because a continuous random variable can assume infinitely many possible values, its distribution is represented by a curve, called the density curve. A density curve must satisfy the following co
Section 6.1
Introduction to Random Variabls and Probability Distributions
(1) A random variable is a quantitative variable whose values are results of a random process.
A discrete random variable is one whose possible values are finite or countably
infini
Introduction to Probability
and Statistics
Exam 1 Review
Jason Wilson, Ph.D
Biola University
1
Course
map
Data
Collectio
n
Variables
(Ch 3)
Observation
al Study
(Ch 4-5)
Experiment
(Ch 5-6)
Survey
Statistic
s
Descriptiv
e
Statistics
Measures of
center
(Ch
Hyunji Helen Jeong
Statistics helps us make sense of the world. Statistics are used as a way to bring meaning
to our data; it gives meaning of the life on earth and the universe beyond. Statistics is integrated
in our everyday life to see if what we think
Helen Jeong
Reading Reflection Ch. 21
TR 4:30-5:45
11/05/13
Chapter twenty-one talks about the role of confidence intervals in research. Thinking
that this is another chapter talking about confidence intervals, I thought this chapter would be
much of a re
Chapter 5 - Experiments and Observational Studies
Tuesday, September 10, 2013
4:40 PM
Explanatory Variables vs. Response Variables
Explanatory Variable: the one that attempts to explain or cause the differences
Response Variable: the outcome variable
E
Chapter 7 - Summarizing and Displaying Measurement Data
Thursday, September 12, 2013
4:41 PM
Turn Data into Information
Central Tendencies: mean (average), median, and mode
Outliers: one or two scores that removed are far from the rest of the data
Vari
Chapter 11 - Relationships Can Be Deceiving
Thursday, September 26, 2013
4:40 PM
What The Outlier Can Do
Looking at the two scatterplots with the outliers, will the outliers strengthen or weaken
the correlations?
Cause or Correlation? #1
A strong correl
Chapter 16 - Understanding Probability and Long-Term
Expectations
Tuesday, October 01, 2013
4:36 PM
Probability, what's that?
Although we will be studying three different types of probability, in general, probability
measures the likelihood that an ever
Chapter 18 - When Intuition Differs from Relative Frequency
Tuesday, October 22, 2013
4:41 PM
Coincidences
How many of you traveled somewhere very far away and ran into someone that you
thought you never would have?
This would be an example of what we c
Chapter 19 - The Diversity of Samples from the Same Population
Thursday, October 24, 2013
4:53 PM
Sample Proportions
A sample proportion is simply a proportion that is found from a sample.
Ex) Say we selected 25 random tree samples to test for disease.
Chapter 20 - Estimating Proportions with Confidence
Tuesday, October 29, 2013
4:33 PM
Confidence Intervals
In chapter 19, we discussed finding probabilities if we know something about the
population. As I had mentioned then, it seems backwards; it is. In
Chapter 22 - Rejecting Chance - Testing Hypotheses in Research
Tuesday, November 05, 2013
4:41 PM
Using Data to Make Decisions
Relative Risks need to be over 1.0 to conclude a higher risk in a group. Look at Case
Study 5.3 on page 399.
Remember the mean
Helen Jeong
Reading Reflection Ch.1 and Ch. 2
TR 4:30-5:45
09/05/13
Before studying, I start off with a prayer. When reading chapter one, I asked God to
reveal to me more about Him through this class and this book. After reading the whole chapter, I
took
Helen Jeong
Reading Reflection Ch.3 and Ch. 4
TR 4:30-5:45
09/10/13
Chapter three was very interesting in that I came to realize how wording can be a huge
problem in statistics. I knew that wording was very important but I didnt realize that it could
make
Section 3.1
Measures of Central Tendency: Mode, Median, and Mean
(1) Mode
The mode of a data set is the value that occurs most frequently.
(2) Median
The median is the central value of an ordered distribution.
(3) Mean
Mean =
Sum of all entries
Number of