How do we check for independence?
Submitted by gfj100 on Wed, 11/11/2009 - 10:10
Recall that two events are independent when neither event influences the other. That is, knowing
that one event has alr
Examples
Submitted by gfj100 on Wed, 11/11/2009 - 10:07
Example 1
The probability of a student getting an A in this course is 0.25 (Not True!) and the probability of
getting a B is 0.30 (again Not Tru
Conditional Probability
Submitted by gfj100 on Wed, 11/11/2009 - 10:09
In the lesson on Examining Relationships we found conditional distributions from two-way
tables [for example, to find the percent
General Probability Rules
Submitted by gfj100 on Tue, 11/10/2009 - 16:55
Rule 1: The probability of an impossible event is zero; the probability of a certain event is one.
Therefore, for any event A,
Basic Principles of Statistical Design of Experiments
Submitted by gfj100 on Tue, 11/10/2009 - 16:29
Example
A group of college students believe that regular consumption of a special Asian tea could b
Designing Experiments
Submitted by gfj100 on Tue, 11/10/2009 - 16:28
Example
Suppose some group claims that drinking caffeinated coffee causes hyperactivity college
students, ages 18 to 22. How would
Designing Samples
Submitted by gfj100 on Tue, 11/10/2009 - 16:27
Then entire group of individuals about which information is wanted is called the populations. It
ma be somewhat abstract. The part of t
Cautions about Correlation and Regression
Submitted by gfj100 on Fri, 10/30/2009 - 09:50
Influence Outliers
In most practical circumstances an outlier decreases the value of a correlation coefficient
omparing Two Quantitative Variables
Submitted by gfj100 on Fri, 10/30/2009 - 09:39
As we did when considering only one variable, we begin with a graphical display.
A scatterplot is the most useful dis
Comparing Two Categorical Variables
Submitted by gfj100 on Fri, 10/30/2009 - 09:27
Understand that categorical variables either exist naturally (e.g. a persons race, political party
affiliation, or cl
Finding Outliers Using IQR
Submitted by gfj100 on Fri, 10/30/2009 - 09:07
Some observations within our data set may fall outside the general scope of the remaining
observations. Such observations are
Spread (Variability)
Submitted by gfj100 on Fri, 10/30/2009 - 09:05
The word spread is used as a synonym for variability. Three simple measure of variability are:
Example of Calculating Range and Inte
Describing Distributions with Numbers
Submitted by gfj100 on Fri, 10/30/2009 - 09:01
Location
The word location is used as a synonym for the middle or center of a dataset. There are two
common ways to
The distribution of a variable shows its pattern of variation, as given by the values of the
variables and their frequencies. The following data set, SAT_DATA.XLS,
or SAT_DATA.MTW (data from College B
Interpreting Confidence Intervals
Submitted by gfj100 on Wed, 11/11/2009 - 13:43
The formula for confidence intervals remains the same:
Sample statistic Multiplier Standard error
In each of the scenar
Matched Pairs for Means
Submitted by gfj100 on Wed, 11/11/2009 - 13:42
Paired Data
Simply put, paired data involves taking two measurements on the same subjects, called repeated
sampling. Think of stu
Comparing Two Independent Proportions
Submitted by gfj100 on Wed, 11/11/2009 - 13:42
Example 3
In the same survey used for example 2, students were asked whether they think same sex
marriage should be
Comparing Two Independent Means - Unpooled and Pooled
Submitted by gfj100 on Wed, 11/11/2009 - 13:41
We determine whether to apply "pooled" or "unpooled" procedures by comparing the sample
standard de
General Ideas for Testing Hypotheses
Submitted by gfj100 on Wed, 11/11/2009 - 13:40
Step 0: Assumptions
1. The samples must be independent and random samples.
2. If two proportions, then the two group
Comparing Two Groups
Submitted by gfj100 on Wed, 11/11/2009 - 13:39
Previously we discussed testing means from one sample or paired data. But what about situations
where the data is not paired, such a
Errors, Practicality and Power in Hypothesis Testing
Submitted by gfj100 on Wed, 11/11/2009 - 13:16
Errors in Decision Making Type I and Type II
How do we determine whether to reject the null hypothes
Hypothesis Testing for a Mean
Submitted by gfj100 on Wed, 11/11/2009 - 13:16
Quantitative Response Variables and Means
We usually summarize a quantitative variable by examining the mean value. We
summ
Hypothesis Testing for a Proportion
Submitted by gfj100 on Wed, 11/11/2009 - 13:15
Ultimately we will measure statistics (e.g. sample proportions and sample means) and use them
to draw conclusions abo
Hypothesis Testing
Submitted by gfj100 on Wed, 11/11/2009 - 13:14
Previously we used confidence intervals to estimate some unknown population parameter. For
example, we constructed 1-proportion confid
Using Software To Calculate Confidence Intervals
Submitted by gfj100 on Wed, 11/11/2009 - 12:51
Consider again the Class Survey data set (Class_Survey.MTW or Class_Survey.XLS) that
consists of student
Constructing confidence intervals to estimate a population
mean
Submitted by gfj100 on Wed, 11/11/2009 - 12:50
Previously we considered confidence intervals for 1-proportion and our multiplier in our
Constructing confidence intervals to estimate a population
proportion
Submitted by gfj100 on Wed, 11/11/2009 - 12:45
NOTE: the following interval calculations for the proportion confidence interval is
Toward Statistical Inference
Submitted by gfj100 on Wed, 11/11/2009 - 12:44
Two designs for producing data are sampling and experimentation, both of which should employ
randomization. As we have alrea
Review of Sampling Distributions
Submitted by gfj100 on Wed, 11/11/2009 - 12:01
In later part of the last lesson we discussed finding the probability for a continuous random
variable that followed a n
Sampling Distribution of the Sample Mean, xbar
Submitted by gfj100 on Wed, 11/11/2009 - 12:00
The central limit theorem states that if a large enough sample is taken (typically n > 30) then
the sampli