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Lecture G89.2228 4a f(X) of special interest: Normal Distribution Are These Random Variables Normally Distributed? Probability Statements and the Normal Distribution Covariance: An important bivariate moment Covariance and. correlation 1 G89.2228 Lect 4a A Density of Special Interest: the Normal Distribution The facts about expectations have been developed without specifying the exact nature of the distribution of X f(X) can take many different forms In some cases its form is not known There is one form of f(X) that is of special interest: the normal distribution The familiar bell shaped distribution so often observed in nature A distribution that repeatedly emerges in mathematical statistics Central Limit Theorem shows that sums (and averages) of random variables are normally distributed 2 G89.2228 Lect 4a The Normal density A family of distributions that are indexed by two parameters 2 and , the mean and variance 2 is the index of location, and is the index of spread Family of normal curves 0.8 0.7 0.6 0.5 f(X) 0.4 0.3 0.2 0.1 0 0 1 2 0.5 1.5 -2.5 -0.5 -1.5 -0.1 2.5 -3 -2 -1 3 Normal(0,1) Normal(-.5,.25) Series1 Series2 ( X ) 2 1 2 2 f (X ) = e 2 X 3 G89.2228 Lect 4a Normal distributions Why do they appear in nature so often? Linear transformation of X~N( 2 2 , ) [X distributed as N( , )] does not change form 2 If Y=a+bX then Y~N[( +a),(b2 )] If height is normal in inches, it is normal in centimeters If self-esteem is normal using one scale, it will usually be normal with a highly correlated scale Empirical operation of Central limit theorem 4 G89.2228 Lect 4a Central Limit Theorem Sums of random variables will be normally distributed as the number of things summed gets large If the distribution of random variables Wi is symmetric, large may be as little as N=10 Averages are simply linear transformed sums: (1/n)( X) Many processes in nature are additive Height is the sum of annual growths Many psychological measures are additive Educational achievement as sum of correct test responses 5 G89.2228 Lect 4a Are these random variables normally distributed? Sum five coin flips (H=1, T=0) Sum of fifty coin flips Annual salaries of professors For X~N( 1, 2) and Y~N( 2, 2), 1 2 X+Y 2 For X~N( , ), X2 2 2 For X~N( 1, ) and Y~N( 2, ), X2+Y2 2 For Xi~N( , ) for all i=1,2,...,500, Xi2 Reaction times to memory trials Errors in smell identification test Sum of 10 attitude strength items 6 G89.2228 Lect 4a Probability statements using the Normal Distribution The distribution of normally distributed random variables, such as sample means, is well known and often presented in tables as N(0,1). Tables can be used by transforming variables with other normal distributions to the form of N(0,1). 2 2 If X~N( , ) and if and are known,then Z = (X- )/ has N(0,1) distribution This transformation is one-to-one, allowing one to reconstruct X from Z: X= + Z 7 G89.2228 Lect 4a Computing Probabilities from N(0,1) Distribution Tables of N(0,1) allow to us ask the probability of sampling Z~N(0,1) in the range (-1, 1). Pr(-1 Z 1) = .68 If X~N(-.5,.52) and we want to ask about Pr(-1.5 X 0) we transform to Z and compute 0 ( .5) 1.5 ( .5) Pr( 1.5 X 0) = Pr Z .5 .5 = Pr[ 2 Z 1] = .4772 + .3413 = .8185 8 G89.2228 Lect 4a One Table Fits All Transformation makes it unnecessary to have all variations of normal curves tabled. The standard normal table describes probability in terms of number of sd's from mean. Family of normal curves 0.8 0.7 0.6 0.5 f(X) 0.4 0.3 0.2 0.1 0 0 1 2 0.5 1.5 -2.5 -0.5 -1.5 -0.1 2.5 -3 -2 -1 3 Normal(0,1) Normal(-.5,.25) Series1 Series2 X 9 G89.2228 Lect 4a Assessing Non-independence: One More Expectation Operator Very often we consider two random variables together height and weight reaction time and response errors depression and anxiety Subject 1 and a yoked control E[(X- x)(Y- y)] = Cov(X,Y) = is XY called the population covariance. Cov(X,Y) measures linear association between the variables It is an expectation that depends on the joint bivariate density of X and Y, f(X,Y). f(X,Y) says how likely are any pair of values of X and Y 10 G89.2228 Lect 4a Interpreting covariance as a parameter -,+ -,Y +,+ X +,- When X and Y tend to increase together, Cov(X,Y)>0 When high levels of X go with low levels of Y, Cov(X,Y)<0 When X and Y are independent, Cov(X,Y) = 0. Note that there are cases when Cov(X,Y) take the value zero when X and Y are related 11 nonlinearly. G89.2228 Lect 4a Correlation and Covariance Besides noticing its sign and whether it is zero, it is difficult to interpret the absolute magnitude of covariance Note that Cov(X,Y) is bounded by V(X) and V(Y): Cov( X , Y ) Max[V ( X ),V (Y )] If V(X) and V(Y) can be transformed so that both have variances equal to one, then the new covariance is bounded by -1 and +1 In this case the covariance = correlation, = Corr(X,Y) XY It has all the same properties of covariances just discussed, but is easier to interpret 12 G89.2228 Lect 4a Cov (X,Y) as an expectation operator For k1 and k2 as constants, there are facts closely parallel to facts for variances: Cov(k1+X, k2+Y) = Cov(X,Y) = XY Cov(k1X, k2Y) = k1*k2*Cov(X,Y) = k1*k2* XY Important special case: Let Y* = (1/ )Y and X* = (1/ )X Y X V(X*) = V(Y*) = 1.0 Cov(X*,Y*) = (1/ ) (1/ ) = Y X XY XY Cov (X*,Y*) is the population correlation for the variables X and Y, XY Since = (1/ ) (1/ ) XY Y X XY, = ( ) ( ) XY Y X XY 13 G89.2228 Lect 4a One Payoff for Studying Covariance We can generalize the rule for calculating the variance of a sum of two variables. For any X and Y, Var(X+Y) = V(X) + V(Y) +2Cov(X,Y) Var(X Y) = V(X) + V(Y) 2Cov(X,Y) More generally, Var(k1X+k2Y) = k12 2 + k22 2+2k1k2 X Y XY X 3 26 40 21 8 6 13 25 20 10 17.2 129.1 11.36 43.38 0.695 Y Mean Variance SD Cov ,Y ) (X Corr(X ) ,Y 5 18 15 16 1 6 15 12 9 11 10.8 30.18 5.493 X+ X-Y Y 8 44 55 37 9 12 28 37 29 21 28 246 15.68 -2 8 25 5 7 0 -2 13 11 -1 6.4 72.489 8.514 14 G89.2228 Lect 4a
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Lect04a.ppt
Path: NYU >> G89 >> 2228 Fall, 2008
Description: G89.2228 Lecture 4a f(X) of special interest: Normal Distribution Are These Random Variables Normally Distributed? Probability Statements and the Normal Distribution Covariance: An important bivariate moment Covariance and. correlation 1 G89.22...
Lect11a.ppt
Path: NYU >> G89 >> 2002 Fall, 2008
Description: G89.2228 Lecture 11a Example: Comparing variances ANOVA table ANOVA linear model ANOVA assumptions Data transformations Effect sizes and power G89.2228 Lect 11a 1 Comparing 3 or more means: Examples Okasaki reported that Asian-American stud...
Lect11a.ppt
Path: NYU >> G89 >> 2228 Fall, 2008
Description: G89.2228 Lecture 11a Example: Comparing variances ANOVA table ANOVA linear model ANOVA assumptions Data transformations Effect sizes and power G89.2228 Lect 11a 1 Comparing 3 or more means: Examples Okasaki reported that Asian-American stud...
CI for Proportions.xls
Path: NYU >> G89 >> 2002 Fall, 2008
Description: This spread sheet computes Fleiss\'s confidence bound for binomial proportion Input N # pos z(alpha) 20 5 1.96 phat LB(p) UB(p) Output 0.250 0.096 0.494 ...
CI for Proportions.xls
Path: NYU >> G89 >> 2228 Fall, 2008
Description: This spread sheet computes Fleiss\'s confidence bound for binomial proportion Input N # pos z(alpha) 20 5 1.96 phat LB(p) UB(p) Output 0.250 0.096 0.494 ...
Lec12-2x3ANOVAeffectsize.xls
Path: NYU >> G89 >> 2002 Fall, 2008
Description: 2x3 ANOVA Effect Size Calculation Spreadsheet Enter Guesses for cells in red and effects are calculated. SUMMARY A1 Mean A2 Mean Total Mean B1 0.500 0.500 0.500 B2 0.500 0.500 0.500 B3 0.500 0.200 0.350 Total 0.500 0.400 0.450 Deviation Dev^2 0.0500...
Lec12-2x3ANOVAeffectsize.xls
Path: NYU >> G89 >> 2228 Fall, 2008
Description: 2x3 ANOVA Effect Size Calculation Spreadsheet Enter Guesses for cells in red and effects are calculated. SUMMARY A1 Mean A2 Mean Total Mean B1 0.500 0.500 0.500 B2 0.500 0.500 0.500 B3 0.500 0.200 0.350 Total 0.500 0.400 0.450 Deviation Dev^2 0.0500...
Lect14b.ppt
Path: NYU >> G89 >> 2002 Fall, 2008
Description: G89.2228 Lecture 14b Within subjects contrasts Types of Within-subject contrasts Individual vs pooled contrasts Example Between subject effects in repeated measures design Mapping the repeated measures contrasts on to the mixed model ANOVA 1 G...
Lect14b.ppt
Path: NYU >> G89 >> 2228 Fall, 2008
Description: G89.2228 Lecture 14b Within subjects contrasts Types of Within-subject contrasts Individual vs pooled contrasts Example Between subject effects in repeated measures design Mapping the repeated measures contrasts on to the mixed model ANOVA 1 G...
EX02.doc
Path: NYU >> G89 >> 2002 Fall, 2008
Description: G89.2228 Intermediate Statistics Fall 2001 Exercise #2 1. Due September 26, 2001 You have been assigned a random sample of 20 CESD scores on women who had experienced a miscarriage approximately two weeks earlier. Enter these data into a computer so...
EX02.doc
Path: NYU >> G89 >> 2228 Fall, 2008
Description: G89.2228 Intermediate Statistics Fall 2001 Exercise #2 1. Due September 26, 2001 You have been assigned a random sample of 20 CESD scores on women who had experienced a miscarriage approximately two weeks earlier. Enter these data into a computer so...
EX07.doc
Path: NYU >> G89 >> 2002 Fall, 2008
Description: G89.2228 Intermediate Statistics Fall 2001 Exercise #7: Power analysis Due October 31, 2001 For all of these questions, write a sentence or describing the answer, and the method used to compute the result. If the method is an approximation, make tha...
EX07.doc
Path: NYU >> G89 >> 2228 Fall, 2008
Description: G89.2228 Intermediate Statistics Fall 2001 Exercise #7: Power analysis Due October 31, 2001 For all of these questions, write a sentence or describing the answer, and the method used to compute the result. If the method is an approximation, make tha...
Lect13a.ppt
Path: NYU >> G89 >> 2002 Fall, 2008
Description: G89.2228 Lecture 13a Power for 2 way ANOVA Random effects Expected MS Mixed models Special case: one entry per cell 1 G89.2228 Lect 13a Effect sizes and power Cohens f (Howells is the square ) root of the effect variance divided by within c...
Lect13a.ppt
Path: NYU >> G89 >> 2228 Fall, 2008
Description: G89.2228 Lecture 13a Power for 2 way ANOVA Random effects Expected MS Mixed models Special case: one entry per cell 1 G89.2228 Lect 13a Effect sizes and power Cohens f (Howells is the square ) root of the effect variance divided by within c...
APA taskforce report.doc
Path: NYU >> G89 >> 2002 Fall, 2008
Description: Task Force on Statistical Inference Initial Report http:/www.apa.org/science/tfsi.html Board of Scientific Affairs American Psychological Association This report is the result of the initial 2-day meeting of the Task Force on Statistical Inference h...
APA taskforce report.doc
Path: NYU >> G89 >> 2228 Fall, 2008
Description: Task Force on Statistical Inference Initial Report http:/www.apa.org/science/tfsi.html Board of Scientific Affairs American Psychological Association This report is the result of the initial 2-day meeting of the Task Force on Statistical Inference h...
EX10.doc
Path: NYU >> G89 >> 2002 Fall, 2008
Description: G89.2228 Intermediate Statistics Fall 2001 Exercise #10 1. Due December 5, 2001 In Exercise 9 you examined the association between so-called positive symptoms and two explanatory variables, homelessness and drug use. Suppose that a reviewer of the a...
EX10.doc
Path: NYU >> G89 >> 2228 Fall, 2008
Description: G89.2228 Intermediate Statistics Fall 2001 Exercise #10 1. Due December 5, 2001 In Exercise 9 you examined the association between so-called positive symptoms and two explanatory variables, homelessness and drug use. Suppose that a reviewer of the a...
Lect10b.ppt
Path: NYU >> G89 >> 2002 Fall, 2008
Description: G89.2228 Lecture 10b Example: Recognition Memory Regression: Expected Y given X Variance accounted for 1 G89.2228 Lect 10b Example: Recognition for Studied Words Suppose we ask students if they recognize certain words as having been on a study ...
Lect10b.ppt
Path: NYU >> G89 >> 2228 Fall, 2008
Description: G89.2228 Lecture 10b Example: Recognition Memory Regression: Expected Y given X Variance accounted for 1 G89.2228 Lect 10b Example: Recognition for Studied Words Suppose we ask students if they recognize certain words as having been on a study ...
EX05.doc
Path: NYU >> G89 >> 2002 Fall, 2008
Description: G89.2228IntermediateStatistics Fall2001 Exercise#5 DueOct.17,2001 Onthecomputersandavailablefromtheinstructorsaredatafromthestudyofwomenwhohad experiencedamiscarriage. Thesewomenwererecruitedfroman upperManhattanmedical centerfollowingtheirmiscar...
EX05.doc
Path: NYU >> G89 >> 2228 Fall, 2008
Description: G89.2228IntermediateStatistics Fall2001 Exercise#5 DueOct.17,2001 Onthecomputersandavailablefromtheinstructorsaredatafromthestudyofwomenwhohad experiencedamiscarriage. Thesewomenwererecruitedfroman upperManhattanmedical centerfollowingtheirmiscar...
Abelson.pdf
Path: NYU >> G89 >> 2002 Fall, 2008
Description: ...
Abelson.pdf
Path: NYU >> G89 >> 2228 Fall, 2008
Description: ...
EX01.doc
Path: NYU >> G89 >> 2002 Fall, 2008
Description: Intermediate Statistics G89.2228 1. Exercise Set 1 Due 9/12/01 In class on 9/05/01 you were given two sets of CES-D scores from women who had experienced a miscarriage in the past two weeks. Each data set had 10 observations. Compute for each set o...
EX01.doc
Path: NYU >> G89 >> 2228 Fall, 2008
Description: Intermediate Statistics G89.2228 1. Exercise Set 1 Due 9/12/01 In class on 9/05/01 you were given two sets of CES-D scores from women who had experienced a miscarriage in the past two weeks. Each data set had 10 observations. Compute for each set o...
EX04.doc
Path: NYU >> G89 >> 2002 Fall, 2008
Description: G89.2228 Intermediate Statistics Fall 2001 Exercise #4 1. Answer Exercises 5.2 and 5.3 from Howell text. 2. In Exercise 5.2, are the events you win the grand prize and your brother wins second prize independent? Why or why not? 3. 4. Answer 5.26 from...
EX04.doc
Path: NYU >> G89 >> 2228 Fall, 2008
Description: G89.2228 Intermediate Statistics Fall 2001 Exercise #4 1. Answer Exercises 5.2 and 5.3 from Howell text. 2. In Exercise 5.2, are the events you win the grand prize and your brother wins second prize independent? Why or why not? 3. 4. Answer 5.26 from...
elizaug05.xls
Path: N.C. State >> ARE >> 495 Fall, 2008
Description: Elizabeth Hg zero 80 75 70 65 60 55 50 45 ng/m3 40 35 30 25 20 15 10 5 0 7/30/05 8/6/05 8/13/05 8/20/05 8/27/05 9/3/05 9/3/05 Elizabeth part Hg 100 95 90 85 80 75 70 65 60 pg/m3 55 50 45 40 35 30 25 20 15 10 5 0 7/30/05 8/6/05 8/13/05 8/20/05 8/27/...
elizaug05.xls
Path: N.C. State >> AS >> 495 Fall, 2008
Description: Elizabeth Hg zero 80 75 70 65 60 55 50 45 ng/m3 40 35 30 25 20 15 10 5 0 7/30/05 8/6/05 8/13/05 8/20/05 8/27/05 9/3/05 9/3/05 Elizabeth part Hg 100 95 90 85 80 75 70 65 60 pg/m3 55 50 45 40 35 30 25 20 15 10 5 0 7/30/05 8/6/05 8/13/05 8/20/05 8/27/...
elizaug05.xls
Path: N.C. State >> ST >> 495 Fall, 2008
Description: Elizabeth Hg zero 80 75 70 65 60 55 50 45 ng/m3 40 35 30 25 20 15 10 5 0 7/30/05 8/6/05 8/13/05 8/20/05 8/27/05 9/3/05 9/3/05 Elizabeth part Hg 100 95 90 85 80 75 70 65 60 pg/m3 55 50 45 40 35 30 25 20 15 10 5 0 7/30/05 8/6/05 8/13/05 8/20/05 8/27/...
EmissionsFieldDescriptions.xls
Path: N.C. State >> ARE >> 495 Fall, 2008
Description: Field Name date_ id event_id latitude longitude fips state county country type SCC area fuel_moisture_10hr fuel_moisture_1khr consumption_flaming consumption_smoldering consumption_residual consumption_duff heat pm25 pm10 pm co co2 ch4 nmhc nox nh3 s...
EmissionsFieldDescriptions.xls
Path: N.C. State >> AS >> 495 Fall, 2008
Description: Field Name date_ id event_id latitude longitude fips state county country type SCC area fuel_moisture_10hr fuel_moisture_1khr consumption_flaming consumption_smoldering consumption_residual consumption_duff heat pm25 pm10 pm co co2 ch4 nmhc nox nh3 s...
EmissionsFieldDescriptions.xls
Path: N.C. State >> ST >> 495 Fall, 2008
Description: Field Name date_ id event_id latitude longitude fips state county country type SCC area fuel_moisture_10hr fuel_moisture_1khr consumption_flaming consumption_smoldering consumption_residual consumption_duff heat pm25 pm10 pm co co2 ch4 nmhc nox nh3 s...
lecture11.pdf
Path: N.C. State >> ARE >> 495 Fall, 2008
Description: Final Project Report William F. Hunt, Jr. Outline Executive Summary Introduction/Background Objectives Methods and Analysis Conclusions and Recommendations Executive Summary Briefly describe what you found. Dr. Ellis Cowling - turn significa...
lecture11.pdf
Path: N.C. State >> AS >> 495 Fall, 2008
Description: Final Project Report William F. Hunt, Jr. Outline Executive Summary Introduction/Background Objectives Methods and Analysis Conclusions and Recommendations Executive Summary Briefly describe what you found. Dr. Ellis Cowling - turn significa...
lecture11.pdf
Path: N.C. State >> ST >> 495 Fall, 2008
Description: Final Project Report William F. Hunt, Jr. Outline Executive Summary Introduction/Background Objectives Methods and Analysis Conclusions and Recommendations Executive Summary Briefly describe what you found. Dr. Ellis Cowling - turn significa...
Emissions_Data.xls
Path: N.C. State >> ARE >> 495 Fall, 2008
Description: Carbon Monoxide (CO) National Emission Trends (thousand short tons) Source Category 1970 1975 1980 1985 1990 1991 FUEL COMB. ELEC. UTIL. 237 276 322 291 363 349 FUEL COMB. INDUSTRIAL 770 763 750 670 879 920 FUEL COMB. OTHER 3,625 3,441 6,230 7,525 4,...
Emissions_Data.xls
Path: N.C. State >> AS >> 495 Fall, 2008
Description: Carbon Monoxide (CO) National Emission Trends (thousand short tons) Source Category 1970 1975 1980 1985 1990 1991 FUEL COMB. ELEC. UTIL. 237 276 322 291 363 349 FUEL COMB. INDUSTRIAL 770 763 750 670 879 920 FUEL COMB. OTHER 3,625 3,441 6,230 7,525 4,...
Emissions_Data.xls
Path: N.C. State >> ST >> 495 Fall, 2008
Description: Carbon Monoxide (CO) National Emission Trends (thousand short tons) Source Category 1970 1975 1980 1985 1990 1991 FUEL COMB. ELEC. UTIL. 237 276 322 291 363 349 FUEL COMB. INDUSTRIAL 770 763 750 670 879 920 FUEL COMB. OTHER 3,625 3,441 6,230 7,525 4,...
lecture06.pdf
Path: N.C. State >> ARE >> 495 Fall, 2008
Description: Initial Homework Project Briefing Are NCSU Students, Faculty or Alumni More Likely to Drive a Red Car? Briefing Outline Background and Objectives Data Methods and Analysis Conclusions and Recommendations Background and Objective Describe the proble...
lecture06.pdf
Path: N.C. State >> AS >> 495 Fall, 2008
Description: Initial Homework Project Briefing Are NCSU Students, Faculty or Alumni More Likely to Drive a Red Car? Briefing Outline Background and Objectives Data Methods and Analysis Conclusions and Recommendations Background and Objective Describe the proble...
lecture06.pdf
Path: N.C. State >> ST >> 495 Fall, 2008
Description: Initial Homework Project Briefing Are NCSU Students, Faculty or Alumni More Likely to Drive a Red Car? Briefing Outline Background and Objectives Data Methods and Analysis Conclusions and Recommendations Background and Objective Describe the proble...
elizjun05.xls
Path: N.C. State >> ARE >> 495 Fall, 2008
Description: Elizabeth Hg zero 37.5 35 32.5 30 27.5 25 22.5 ng/m3 20 17.5 15 12.5 10 7.5 5 2.5 0 5/28/05 6/4/05 6/11/05 6/18/05 6/25/05 7/2/05 7/2/05 Elizabeth part Hg 100 95 90 85 80 75 70 65 60 pg/m3 55 50 45 40 35 30 25 20 15 10 5 0 5/28/05 6/4/05 6/11/...
elizjun05.xls
Path: N.C. State >> AS >> 495 Fall, 2008
Description: Elizabeth Hg zero 37.5 35 32.5 30 27.5 25 22.5 ng/m3 20 17.5 15 12.5 10 7.5 5 2.5 0 5/28/05 6/4/05 6/11/05 6/18/05 6/25/05 7/2/05 7/2/05 Elizabeth part Hg 100 95 90 85 80 75 70 65 60 pg/m3 55 50 45 40 35 30 25 20 15 10 5 0 5/28/05 6/4/05 6/11/...
elizjun05.xls
Path: N.C. State >> ST >> 495 Fall, 2008
Description: Elizabeth Hg zero 37.5 35 32.5 30 27.5 25 22.5 ng/m3 20 17.5 15 12.5 10 7.5 5 2.5 0 5/28/05 6/4/05 6/11/05 6/18/05 6/25/05 7/2/05 7/2/05 Elizabeth part Hg 100 95 90 85 80 75 70 65 60 pg/m3 55 50 45 40 35 30 25 20 15 10 5 0 5/28/05 6/4/05 6/11/...
CA_Lead_Data_2006.xls
Path: N.C. State >> ARE >> 495 Fall, 2008
Description: County Name Alameda Alpine Amador Berkely City Butte Calaveras Colusa Contra Costa Del Norte El Dorado Fresno Glenn Humboldt Imperial Inyo Kern Kings Lake Lassen Long Beach City Los Angeles Madera Marin Mariposa Mendocino Merced Modoc Mono Monterey N...
CA_Lead_Data_2006.xls
Path: N.C. State >> AS >> 495 Fall, 2008
Description: County Name Alameda Alpine Amador Berkely City Butte Calaveras Colusa Contra Costa Del Norte El Dorado Fresno Glenn Humboldt Imperial Inyo Kern Kings Lake Lassen Long Beach City Los Angeles Madera Marin Mariposa Mendocino Merced Modoc Mono Monterey N...
CA_Lead_Data_2006.xls
Path: N.C. State >> ST >> 495 Fall, 2008
Description: County Name Alameda Alpine Amador Berkely City Butte Calaveras Colusa Contra Costa Del Norte El Dorado Fresno Glenn Humboldt Imperial Inyo Kern Kings Lake Lassen Long Beach City Los Angeles Madera Marin Mariposa Mendocino Merced Modoc Mono Monterey N...
lecture09.ppt
Path: N.C. State >> ARE >> 495 Fall, 2008
Description: Interim Results Briefing William F. Hunt, Jr. Three Projects Exploratory Analysis of PM Fine Organic Carbon & Gaseous Volatile Organic Compound Data. Assessing Urban Growth Land Use Patterns and Air Quality Trends in the Phoenix and RaleighDurham ...
lecture09.ppt
Path: N.C. State >> AS >> 495 Fall, 2008
Description: Interim Results Briefing William F. Hunt, Jr. Three Projects Exploratory Analysis of PM Fine Organic Carbon & Gaseous Volatile Organic Compound Data. Assessing Urban Growth Land Use Patterns and Air Quality Trends in the Phoenix and RaleighDurham ...
lecture09.ppt
Path: N.C. State >> ST >> 495 Fall, 2008
Description: Interim Results Briefing William F. Hunt, Jr. Three Projects Exploratory Analysis of PM Fine Organic Carbon & Gaseous Volatile Organic Compound Data. Assessing Urban Growth Land Use Patterns and Air Quality Trends in the Phoenix and RaleighDurham ...
o3data_2002.xls
Path: N.C. State >> ARE >> 495 Fall, 2008
Description: 8-Hour ozone averages (every day maximum) in 2002 in NC County Site Name AIRS Code Exceedance days Valid Days 4/1/2002 4/2/2002 4/3/2002 4/4/2002 4/5/2002 4/6/2002 4/7/2002 4/8/2002 4/9/2002 4/10/2002 4/11/2002 4/12/2002 4/13/2002 4/14/2002 4/15/2002...
o3data_2002.xls
Path: N.C. State >> AS >> 495 Fall, 2008
Description: 8-Hour ozone averages (every day maximum) in 2002 in NC County Site Name AIRS Code Exceedance days Valid Days 4/1/2002 4/2/2002 4/3/2002 4/4/2002 4/5/2002 4/6/2002 4/7/2002 4/8/2002 4/9/2002 4/10/2002 4/11/2002 4/12/2002 4/13/2002 4/14/2002 4/15/2002...
o3data_2002.xls
Path: N.C. State >> ST >> 495 Fall, 2008
Description: 8-Hour ozone averages (every day maximum) in 2002 in NC County Site Name AIRS Code Exceedance days Valid Days 4/1/2002 4/2/2002 4/3/2002 4/4/2002 4/5/2002 4/6/2002 4/7/2002 4/8/2002 4/9/2002 4/10/2002 4/11/2002 4/12/2002 4/13/2002 4/14/2002 4/15/2002...
lecture07.ppt
Path: N.C. State >> ARE >> 495 Fall, 2008
Description: How Are Environmental Data Used? Jr. William F. Hunt, Visiting Senior Scientist, North Carolina State University Former Director, Emissions, Monitoring and Analysis Division, U. S. EPA Dr. Kimberly Weems Assistant Professor A Data Users Perspective...
lecture07.ppt
Path: N.C. State >> AS >> 495 Fall, 2008
Description: How Are Environmental Data Used? Jr. William F. Hunt, Visiting Senior Scientist, North Carolina State University Former Director, Emissions, Monitoring and Analysis Division, U. S. EPA Dr. Kimberly Weems Assistant Professor A Data Users Perspective...
lecture07.ppt
Path: N.C. State >> ST >> 495 Fall, 2008
Description: How Are Environmental Data Used? Jr. William F. Hunt, Visiting Senior Scientist, North Carolina State University Former Director, Emissions, Monitoring and Analysis Division, U. S. EPA Dr. Kimberly Weems Assistant Professor A Data Users Perspective...
o3data_2004.xls
Path: N.C. State >> ARE >> 495 Fall, 2008
Description: 8-Hour ozone averages (every day maximum) in 2004 in NC Site Name Taylorsville Waggin Trail Linville Falls Park Creek Lenoir Bent Camden Cherry GrovePittsboro Wade County Alexander Alexander Avery Buncombe Caldwell Camden Caswell Chatham Cumberland A...
o3data_2004.xls
Path: N.C. State >> AS >> 495 Fall, 2008
Description: 8-Hour ozone averages (every day maximum) in 2004 in NC Site Name Taylorsville Waggin Trail Linville Falls Park Creek Lenoir Bent Camden Cherry GrovePittsboro Wade County Alexander Alexander Avery Buncombe Caldwell Camden Caswell Chatham Cumberland A...
o3data_2004.xls
Path: N.C. State >> ST >> 495 Fall, 2008
Description: 8-Hour ozone averages (every day maximum) in 2004 in NC Site Name Taylorsville Waggin Trail Linville Falls Park Creek Lenoir Bent Camden Cherry GrovePittsboro Wade County Alexander Alexander Avery Buncombe Caldwell Camden Caswell Chatham Cumberland A...
ncstatelog.xls
Path: N.C. State >> ARE >> 495 Fall, 2008
Description: Date 5-Sep 5-Aug 5-Jul 5-Jun 5-May 5-Apr 5-Mar 5-Feb 5-Jan 4-Dec 4-Nov 4-Oct 4-Sep 4-Aug 4-Jul 4-Jun 4-May 4-Apr 4-Mar 4-Feb 4-Jan Date 9/05 8/05 7/05 6/05 5/05 4/05 3/05 2/05 1/05 12/04 11/04 10/04 9/04 8/04 7/04 6/04 5/04 4/04 3/04 Comments OK pi...
ncstatelog.xls
Path: N.C. State >> AS >> 495 Fall, 2008
Description: Date 5-Sep 5-Aug 5-Jul 5-Jun 5-May 5-Apr 5-Mar 5-Feb 5-Jan 4-Dec 4-Nov 4-Oct 4-Sep 4-Aug 4-Jul 4-Jun 4-May 4-Apr 4-Mar 4-Feb 4-Jan Date 9/05 8/05 7/05 6/05 5/05 4/05 3/05 2/05 1/05 12/04 11/04 10/04 9/04 8/04 7/04 6/04 5/04 4/04 3/04 Comments OK pi...
ncstatelog.xls
Path: N.C. State >> ST >> 495 Fall, 2008
Description: Date 5-Sep 5-Aug 5-Jul 5-Jun 5-May 5-Apr 5-Mar 5-Feb 5-Jan 4-Dec 4-Nov 4-Oct 4-Sep 4-Aug 4-Jul 4-Jun 4-May 4-Apr 4-Mar 4-Feb 4-Jan Date 9/05 8/05 7/05 6/05 5/05 4/05 3/05 2/05 1/05 12/04 11/04 10/04 9/04 8/04 7/04 6/04 5/04 4/04 3/04 Comments OK pi...
lecture11.ppt
Path: N.C. State >> ARE >> 495 Fall, 2008
Description: Final Project Report William F. Hunt, Jr. Outline Executive Summary Introduction/Background Objectives Methods and Analysis Conclusions and Recommendations Executive Summary Briefly describe what you found. Dr. Ellis Cowling - turn significant resu...
lecture11.ppt
Path: N.C. State >> AS >> 495 Fall, 2008
Description: Final Project Report William F. Hunt, Jr. Outline Executive Summary Introduction/Background Objectives Methods and Analysis Conclusions and Recommendations Executive Summary Briefly describe what you found. Dr. Ellis Cowling - turn significant resu...
lecture11.ppt
Path: N.C. State >> ST >> 495 Fall, 2008
Description: Final Project Report William F. Hunt, Jr. Outline Executive Summary Introduction/Background Objectives Methods and Analysis Conclusions and Recommendations Executive Summary Briefly describe what you found. Dr. Ellis Cowling - turn significant resu...
o3data_2000.xls
Path: N.C. State >> ARE >> 495 Fall, 2008
Description: Eight hour ozone averages (every day maximum) in 2000 in NC County Site AIRS Code Exceedance days 4/1/2000 4/2/2000 4/3/2000 4/4/2000 4/5/2000 4/6/2000 4/7/2000 4/8/2000 4/9/2000 4/10/2000 4/11/2000 4/12/2000 4/13/2000 4/14/2000 4/15/2000 4/16/2000 4...
o3data_2000.xls
Path: N.C. State >> AS >> 495 Fall, 2008
Description: Eight hour ozone averages (every day maximum) in 2000 in NC County Site AIRS Code Exceedance days 4/1/2000 4/2/2000 4/3/2000 4/4/2000 4/5/2000 4/6/2000 4/7/2000 4/8/2000 4/9/2000 4/10/2000 4/11/2000 4/12/2000 4/13/2000 4/14/2000 4/15/2000 4/16/2000 4...
