Permutation Test for the Two Sample Problem we wish to compare results for two groups of experimental units the first group could be some subjects who have been given a treatment, whereas the second g
1
Wilcoxon Rank-Sum Test, also known as the Mann-Whitney test Rank the data. That is replace, the data values by their ranks, from smallest to largest. For example, the pH samples are: Group 1: Group
1
One-Way Analysis of Variance (ANOVA)
One-Way Analysis of Variance (ANOVA) is a method for comparing the means of a populations. This kind of problem arises in two different settings 1. When a indepe
Subsequent Inferences for one-way ANOVA if the overall F test does not show significant differences among the groups, no further inferences are required if the overall test does show a significant dif
1
Assessing Normality of a Sample normal quantile plots can be used to assess whether the data could have come from a normal distribution these plots are also called QQ or normal scores plots the sort
1
Two-Way Analysis of Variance - no interaction
Example: Tests were conducted to assess the effects of two factors, engine type, and propellant type, on propellant burn rate in fired missiles. Three e
Residual Analysis for two-way ANOVA The twoway model with K replicates, including interaction, is Yijk = ij + ijk = + i + j + ij + ijk with i = 1, . . . , I, j = 1, . . . , J, k = 1, . . . , K. In car
Randomized Block Example A farmer wishes to compare the growth times of four different varieties of daffodil under a range of different conditions. She decides to use a randomized block design where s
Subsequent Inferences for two-way ANOVA the kinds of inferences to be made after the F tests of a two-way ANOVA depend on the results if none of the F tests lead to rejection of the null hypothesis, t
ECON 3600
Assignment 1
Due on October 3, 2016 (in class)
Total points: 20
1. (4 points)
Army 1, of country 1, must decide whether to attack army 2, of country 2, which is
currently occupying an island
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
A
B
Atlantic Power Company
C
D
E
Statement Print Date:
Customer Name:
F
Smith
John
Hours Used Hourly Rate
0
5
10
Comparing two means, paired experiment
many studies are comparative they compare outcomes from one group with outcomes from another (e.g. two different medical treatments) in the matched-pairs design
Hypothesis Testing basic ingredients of a hypothesis test are 1. the null hypothesis, denoted Ho 2. the alternative hypothesis, denoted Ha 3. the test statistic 4. the the data 5. the conclusion the h
American Economic Association
Common Knowledge Author(s): John Geanakoplos Reviewed work(s): Source: The Journal of Economic Perspectives, Vol. 6, No. 4 (Autumn, 1992), pp. 53-82 Published by: America
ONE SAMPLE T-INTERVAL (95% CI) USING MINITAB MTB > DATA> DATA> MTB > set c1 2.5 3.1 2.2 1.5 2.9 end Onet C1.
One-Sample T: C1 Variable C1 N 5 Mean 2.440 StDev 0.631 SE Mean 0.282 95% CI (1.657, 3.223)
Hypothesis Testing for one sample using t-distribution. Data is the car speed data used in the teaching notes (data set on course web site) Hypothesis Testing using MINITAB
MTB > Onet 'speed'; SUBC> T
1 Statistics 2080 - practice midterm questions 1. Independent random samples were drawn from two normal populations assumed to have the same standard deviation, resulting in the following summary stat
Computer Code for Pooled-t tests. Uses soil pH example from class MINITAB
R Code (using built-in function t.test)
> # pooled t-test used in notes > > # Clear the workspace > rm(list=ls() > > Loc1 = c(
1 1. Independent random samples were taken from two populations of policemen with blood lead concentration measured in each sample member. One sample of 26 policemen subjected to constant inhalation o
Econ2216 (2012): Carbon Social Cost Benefit Project Groups - If you are listed in a group other than the one you have been meeting with OR if you are not in a group or are in a group of 6 and have not
Introduction, 1 sample t-test and t-interval Central Limit Theorem Let X1 , X2 , . . . , Xn be a random sample from a distribution with mean and variance 2 .Then if n is sufficiently large (Rule of th
Confidence Intervals A confidence interval provides a simple summary of how precisely a parameter, denoted , is estimated. In many situations, a (1 - )100% confidence interval is of the form ^ ( - s t
1
Discrete Probability Distributions
1.1
Random Variables
A random variable is a rule assigning a number to an outcome. For example,
the sum of rolling two dice.
(Recall) A discrete random variable