Week 7 Notes Thus, the range (interval) that contains the true value of the unknown population parameter (say the mean) is Where Z is the standard value of the random variable; and is the level of sig
Lecture 7
Advanced Stats
4/28/12
In the case of simple linear regression, the dependent variable
Y is assumed to be a function of only one independent
variable, X.
In the case of multiple regression,
Lecture 6
4/26/12
Regression:
The word regression was first used in 1885 by Sir Francis
Galton in the context of his analysis of the relationship
between the heights of fathers and sons.
He called it
Lecture 2
1/19/12
Keywords that will guide us in identifying the Type II hypothesis we
have set up:
As a claim
Research
Decision-making
*Always state claim as your Ho.
*State the expectation of the r
Lecture 3
1/24/12
Steps involved in hypothesis testing:
1.
Identify keyword or phrase
2.
Set up hypothesis
a.
Either as claim, research, or decision.
b.
Claim: Ho = claim
c.
Research: Ha = expectation
Lecture 4
1/26/12
Sample Standard Deviation
Population standard deviation is not given or not known. In its
place sample standard deviation will be given
When sample standard deviation is not known,
Lecture 5 - Chapter 10 notes
2/14/12
Hypothesis tests involving the difference between 2 population
means (M1-M2) and difference between 2 population
proportions (P1-P2)
Confidence interval estimation
Advanced Stats Lecture Notes 1
1-12-12
A hypothesis consists of 2 statements:
1. Null hypothesis Ho
2.
Alternative hypothesis Ha
In hypothesis testing like a criminal trial, 2 types of errors can
occu
Have you been sued
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Lecture 11
5/1/12
Meaning of the estimated R^2:
The estimated value of R indicates as to what percentage of the
variation in Y is explained by X in the estimated regression
equation.
Significance of t
Lecture 10
Advanced Stats
Simple regression involves building theoretical models,
collecting samples, estimating the model
The estimated model can be used for point forecasts or interval
forecasts
Mod
Week 6 Notes A point estimator is a formula that allows us to draw inference about a population parameter (say, the population mean) by providing us with an estimate of the value of the parameter. It
Week 5 Notes Conditional Probability s The probability of a particular event occurring, given that another event has occurred : P(A|B); P(B|A). s Conditional Probability shows that the two events are
Week 4 Notes Permutations Another method of counting the number of experimental outcomes when n items are to be selected from a set of N objects, where the order of selection matters. where: N! = N(N
Week 3 Notes Measures of Location: Mean, Median, Mode, Percentiles, Quartiles Measures of Dispersion/Spread/Variability Range, Variance, Standard Deviation, Coefficient of Variation Measures of associ
Lecture 8 Notes Demonstration: The mean of the means is equal to the population mean. The variance of the sample mean is smaller than the variance of the population. Example 1 The amount of soda in a
Lecture 7 Notes The purpose of statistical inference is to obtain information about a population using sample data. A population is the set of all the elements of interest. Statistical values computed
Lecture 6 Notes s Solving for the Stockout Probability s Step 1: Formulate the question in a mathematical format s Step 2: Convert x to the standard normal distribution ( that is,
standardize the rand
Lecture 3 Notes Probability .-is a numerical measureof the Likelihood of occurrence of something Experiment: is a process that has well-defined outcomes. The set of all outcomes in an experiment is Ca
Lecture 2 Notes Mode is the most frequent value in the data. It is the value that occurs MOST FREQUENTLY in the data. That is, it is the value with the highest frequency. After Computing the measures
Lecture 8
Advanced Stats Notes
3/29/12
It is a convention to use larger sample variance as the
numerator in computing the test statistic: F
Because of the convention, F-Test is ALWAYS an upper-tailed
Lecture 9
4/12/12
Analysis of Variance (ANOVA)
We will study only 1 factor of ANOVA
We will test whether 3 or more population means are equal or
different
1.
Ho: M1=M2=M3
2.
Ha: At least 1 of the Ms i