ࡱ>  6<bjbjWW @==&4  xxxxx8l0.t.......$/2~&.x&.xx;.qqqxx.q.qq+|-ev&,$-Q.0.J,%3%3$-%3x-q&.&.%L.%3 >: EC 278 - StatisticsPRIVATE  Fall 2013 M. LeClair Course Syllabus This course will familiarize the student with the essentials of statistical methods, including sampling properties, probabilities, statistical inference and hypothesis testing. The final 3 meetings will be devoted to the study of regression analysis an essential tool for the social sciences. Our primary concern will be to show how one can test the validity of a theory, and how much confidence we can have in those tests. Although much of what we do in this course may seem to focus on "mundane" questions, all that we cover is directly applicable to the most important theoretical questions in our any social science discipline. Course Objectives This is a first course in basic statistics. Students will be introduced to the fundamentals of hypothesis testing, sampling, probabilities, and the utilization of regression analysis to measure correlation (and possibly causation). By the end of the course, students should be able to: Design a theoretical experiment to test a hypothesis Transition this theoretical experiment into a workable empirical model Calculate and analyze descriptive statistics that measure the strength of a model Provide an analysis of the findings, and how they can be utilized in the development and analysis of public policy Learning Outcomes The Economics Department has established the following learning outcomes: By the end of the semester, students in principles of economics should be able to: Use theory to describe economic events Demonstrate use of quantitative skills Use models to evaluate public policy or economic theory In addition to the above, upper-division economics students should be able to: Formulate and empirically testable hypothesis Acquire data for analysis and use of software appropriate to the task The Department conducts periodic review of student outcomes. As part of that process, you may be asked to turn in multiple copies of some assignments. Text Anderson, Sweeney and Williams, Essentials of Statistics for Business and Economics, Thompson-Southwestern ASSIGNED READINGS: Week Chapter(s) Topics 1 1 Introduction to the use of data and statistics in economics in the social sciences. Review of random variables and linear functions 2 2 Summarizing data use of tabular and graphical methods 3 3 Summarizing data numerical methods 4 4 Introduction to probability 5 5 Discrete probability distributions 6 ******** Mid-Term 1 7 6 Continuous probability distributions Review for first exam 8 7 Sampling theory and the Central Limit Theorem 9 8 Confidence intervals/sample size/degree of certainty 10 ******** Mid-Term 2 11 9 Hypothesis Testing: One-tail versus two-tail tests. Type I and type II errors. 12 14 Multiple Regression and hypothesis testing - Violations of the Standard assumptions behind regression analysis 13 ******** Special topics in regression 14 ******** Final Exam COMPUTER WORK The computer work may be done on any statistical package you prefer (Excel is widely available on campus). The regression exercise must be done in Stata, which is available in Donnarumma Hall in the Economics and Sociology lab. EVALUATION Each mid-term will comprise 20% of the semester grade. Homework assignments will also count for 20%. The semester project (see below) and the final will be weighted 10% and 30% respectively: Mid-term I 20% Mid-term 2 20% Final 30% Homeworks 20% Project 10% Marked improvement over the course of the semester will be taken into account in assigning final grades. SEMESTER PROJECT You will be conducting an applied experiment in statistics that involves data collection and analysis. Details of the course project will be provided in the second week of the course. OFFICE HOURS DM 255 - X2295 Monday 3-4 Wednesday 5:30-6:30 Thursday 8:50-9:20 and 12-12:30 Or by arrangement EC 278 LAB This is the lab section affiliated with EC 278, Economic Statistics. If you are taking the BS track in Economics, this lab is required. If you are taking the BA track, this lab section is optional. Requirements: As much of the work you are doing in this lab section is done during our class time, you must attend at least 13 of the 14 meetings (1 excused absence). Additional absences will result in a stepped reduction in your grade for the semester. If you get into a situation (e.g. medical) where multiple absences are likely, please come and see me. Proposed Assignments: During each meeting of the lab section, you will be provided with a worksheet to complete. Group work will be encouraged during the data analysis part of the lab. Students must, however, complete their own WeekTopicAssignment2Sampling and measures of central tendencyWS 1 Traffic flow at a Dunkin Donuts or other fast food outlet3Sampling and measures of dispersionWS 2 Traffic flow at a fast food outlet. Measures of dispersion in the number of customers4Probability distributions and sample means and standard deviationsWS 3 Estimating common probabilities. Winning (or not) in Las Vegas5Bayes Theorem and advanced probabilitiesWS 4 - Quality control and the statistics of parts failure6Probability distributions discrete and continuousWS 5 Distinguishing between discrete and continuous distributions7The z and t distributions and hypothesis testingWS 6 Raw data and the use of the t- and z-stats. Daily price data8Central Limit Theorem testing central tendency in large samplesWS 7 Increasingly sample size and central tendency. The mean, median and mode under the CLT. Experiments with Dice9Sampling and confidence intervalsWS 8 Currency values and the normal value of the U.S. Dollar9Hypothesis Testing one- and two-tail testsWS 9 -Climate data and temperature trends. One- and two-tail tests of mean temperatures10Fundamentals of Stata WS 10 Stata exercise. Data entry and analysis11Working with data sets in Stata manual entry and importing of dataWS 11 Entering data into Stata manually and downloading of spreadsheets12Simple regression models in StataWS 12 Running a regression model on data from Economic Report of the President13Applications of regression analysis in StataWS 13 Estimation of model from WS 12 corrected for autocorrelation14Presenting empirical results in economicsWS 14 Presenting data from WS 12 and WS 13 --------------------------------------------------------------------------------------------------- Worksheet #1 Traffic flow at a fast-food outlet (7 Points) --------------------------------------------------------------------------------------------------- Introduction: One of the most common problems in successfully operating a business is accurately measuring the timing of demand. In the fast food environment, whether it is at McDonalds, Dunkin Donuts or Starbucks, too little staff equals customer frustration. Too much staff results in wasted money. Our first assignment is to examine traffic flow at a fast food outlet in this case Einsteins Bagels in the Barone Campus Center, and calculate our measures of central tendency (mean, median and mode) and our measures of dispersion (variance, standard deviation and coefficient of variation). Precisely, we will: Measure the number of customers who join the line at Einsteins at five minute intervals at varying times during the day Calculate the means listed above for the data collected. The sample will be split according to high-traffic and low-traffic hours Make an argument for the ideal staffing levels, based upon what we found Each student will be assigned a 5 minute time period to observe between now and the next time we meet. You must bring you results with you at our next meeting. Reporting: Mean____________________ Median___________________ Mode_____________________ Variance__________________ Standard Deviation_________ Coefficient of Variation_____ Please include your work on the attached sheet. Is there a difference in required staffing? What does your data tell you? Name______________________ Work: -------------------------------------------------------------------------------- Worksheet #2 Winning (or not) in Las Vegas (7 Points) -------------------------------------------------------------------------------- Introduction: Las Vegas (or Mohegan Sun) casino type games provide a fruitful (and amusing) way of examining probabilities. The game of craps, for instance, is won or lost depending upon the roll of a pair of dice. The formula for winning, however, is complex. From the wiki: A come-out roll of 2, 3 or 12 is called "craps" or "crapping out", and anyone betting the Pass line loses. A come-out roll of 7 or 11 is a "natural", and the Pass line wins. The other possible numbers are the point numbers: 4, 5, 6, 8, 9, and 10. If the shooter rolls one of these numbers on the come-out roll, this establishes the "point" - to "pass" or "win", the point number must be rolled again before a seven. The dealer flips a button to the "On" side and moves it to the point number signifying the second phase of the round. If the shooter "hits" the point value again (any value of the dice that sum to the point will do; the shooter doesn't have to exactly repeat the value combination of the come-out roll) before rolling a seven, the Pass line wins and a new round starts, usually with the dice staying with the current shooter. If the shooter rolls any seven before repeating the point number (a "seven-out"), the Pass line loses and the dice pass to a new shooter for the next round. Got it? Your assignment is to determine the chances of winning a round of craps. This is not easily done, so here is some guidance: Calculate the chance of winning on the first throw (getting either a 7 or 11 on the dice) Calculate the chance of winning on each subsequent throw if you didnt win on the first throw. Note that the chances of rolling a 2 or a 12 are substantially lower than those of rolling a 5 or a 6. You must take this into account. Reporting: Chance of winning on first throw________ Chance of winning on subsequent throws (up to 5)______ So, should you play craps? Name______________________________ _____________________________________________________________ Worksheet #3 Derivation of Bayes Theorem (7 points) _________________________________________________ Introduction: Suppose you work for a manufacturer that is making washing machines. In order to keep costs down and engage in Just in Time manufacturing, you use two different suppliers of gaskets. Supplier A has provided your business with 40,000 gaskets, and supplier B has shipped you 30,000 gaskets. It is known that supplier As gaskets have a lower failure rate (2.5%) than supplier B (3.25%). When a gasket fails on a machine, what is the probability that it came from supplier A? Completion: You are encouraged to work together to figure this one out. Reporting: Probability that part came from supplier A___________ Name__________________________ _____________________________________________________________ Worksheet #4 Discrete versus Continuous Distributions (7 points) _________________________________________________ Introduction: One of the more difficult topics in statistics is distinguishing between discrete and continuous distributions. Discrete distributions can only take on a limited number of known values. For instance, the sum of a pair of dice can total all whole numbers between 2 and 12. Hence, it is a discrete distribution. Conversely, if we are looking at a sample of heights of individuals, 5 11 is a possible outcome, but so is 5 11.5, and so forth. There is technically no limit to the degree to which one could reduce the increments between observations. This difference is important, because it determines the means by which the average, variance and standard deviation are calculated. Process: You need to partner with someone to carry out this lab. Conduct the following experiments with the materials provided. Repeat each experiment 10 times. Calculate the mean, variance and standard deviation in each case, and identify the distribution as continuous or discrete: Flip a coin six times and record the number of heads Record the time it takes you to conduct each of the trials in the experiment above. Roll a pair of dice and record the sum Fly a paper airplane, and record the distance it flies. Experiment/TrialCoin FlipTime Conducting Coin FlipDice RollAirplane Distance12345678910 Reporting: Coin Flip: Mean_________ Variance__________ Standard Deviation _________ Time: Mean_________ Variance__________ Standard Deviation _________ Dice Toss: Mean_________ Variance__________ Standard Deviation _________ Airplane Mean_________ Variance__________ Standard Deviation _________ Name___________________________   ()5DEm ѽѐrccWcWcWcWcKW>hR[5@OJQJ^Jh:nF@OJQJ^JhrQs@OJQJ^JhrQsh:nF@OJQJ^JhR[h:nF@OJQJ^JhR[hR[@OJQJ^J$hrQsh:nF@CJOJQJ^JaJ3jhrQsh:nF@CJOJQJU^JaJ'hrQsh:nF@CJOJQJ^JaJ0jhrQsh:nF@CJOJQJU^JaJ*hrQsh:nF5@CJOJQJ\^JaJ)45EFn o - t 9 : L M  0*$7$8$H$gd  & F 0d*$gd  0d*$gd  Hd*$gd  d*$gd  d 8 9 : K L M '>?P׿xiWH8hrQsh:nF5@OJQJ^JhrQshrQs@OJQJ^J"hrQshrQs56@OJQJ^JhrQsh:nF@OJQJ^JhrQshrQs5@OJQJ^Jh3b:5@OJQJ^JhR[hR[@OJQJ^JhhR[@OJQJ^JhhR[5@OJQJ^JhR[@OJQJ^JhM-@OJQJ^Jh|i@OJQJ^JhrQs@OJQJ^JhR[hR[5@OJQJ^JM 9qr56?R Hd*$gd  0d*$gd  0*$7$8$H$^gd  0*$7$8$H$^gd  & F 0*$7$8$H$gd  & F 0*$7$8$H$gd  0*$7$8$H$gd PQSWXYcdjkmst>ABEFGkmnsɺyjyyjyjy^h:nF@OJQJ^JhrQshxF@OJQJ^Jh`/@OJQJ^Jh'b@OJQJ^JhrQs@OJQJ^JhrQs>*@OJQJ^JhrQsh:nF>*@OJQJ^JhrQsh:nF@OJQJ^Jh3b:@OJQJ^Jh3b:>*@OJQJ^JhrQsh:nF5@OJQJ^JhrQs5@OJQJ^J$RSkl@AlmST 0d*$gd  #$%7ERSTU[]^%;vʻ֯ʻֻ֯ʣʔւ"hrQsh:nF5@OJQJ\^JhrQsh`/@OJQJ^Jhr@OJQJ^Jh:nF@OJQJ^JhrQshxF@OJQJ^Jh`/@OJQJ^JhrQsh:nF@OJQJ^JhrQsh3b:@OJQJ^Jh3b:@OJQJ^J3ilm Hd*$gd  00d*$^`0gd  0d*$gd =[_klm}789Eȹȹyjhrhr@OJQJ^Jh @OJQJ^Jhr5@OJQJ^Jhr@OJQJ^Jh:nF@OJQJ^JhrQshxF@OJQJ^JhrQsh3b:@OJQJ^Jh3b:@OJQJ^Jh`/@OJQJ^JhrQsh:nF@OJQJ^Jhrh:nF5@OJQJ^J'm~89FGVWcx 0*$7$8$H$gd  H*$7$8$H$gd  Hd*$gd  0d*$gd EFGUVWѮpcVVJ;Jhkhk@OJQJ^Jhk@OJQJ^Jhk5@OJQJ^JhRo55@OJQJ^J!hRo55@CJOJQJ^JaJhRo5@OJQJ^Jh3b:@OJQJ^J)h3b:h3b:56@OJQJ^JaJh#h3b:h3b:@OJQJ^JaJh h3b:5@OJQJ^JaJh&h3b:h3b:5@OJQJ^JaJhh`/@OJQJ^Jhrh:nF@OJQJ^J 0d$*$Ifgd; 0d*$gd 2sNkdQ$$IflF $x x x t06    44 lapyt; 0d$*$Ifgd;2Xrtu=>$%hjkl&'񝂝h}E@OJQJ^Jh;hp@OJQJ^Jh;hk@OJQJ^Jh;h-@OJQJ^Jh;hf@OJQJ^Jh_/@OJQJ^Jh;h@P@OJQJ^Jh8@OJQJ^Jh;hRo5@OJQJ^J2stv`NN< 0d$*$Ifgd_/ 0d$*$Ifgd;kd$$IflF $x x x t06    44 lapyt;>`NNN 0d$*$Ifgd;kd}$$IflF $x x x t06    44 lapyt;`NNN 0d$*$Ifgd;kd$$IflF $x x x t06    44 lapyt;%i`NNN 0d$*$Ifgd;kd$$IflF $x x x t06    44 lapyt;ijl`NNN 0d$*$Ifgd;kd?$$IflF $x x x t06    44 lapyt;'`NNN 0d$*$Ifgd;kd$$IflF $x x x t06    44 lapyt;`NNN 0d$*$Ifgd;kdk$$IflF $x x x t06    44 lapyt;34! " k p !!X!]!!!!!!!6"g"r"s""""徲k'h_/h_/5@CJOJQJ^JaJ!hU25@CJOJQJ^JaJ!h_/5@CJOJQJ^JaJ!ha 5@CJOJQJ^JaJh_/@OJQJ^JhRo5@OJQJ^JhR@OJQJ^Jh;h@P@OJQJ^Jh;hRo5@OJQJ^Jh@OJQJ^J$4`NNN 0d$*$Ifgd;kd$$IflF $x x x t06    44 lapyt;`NNNN 0d$*$Ifgd;kd$$IflF $x x x t06    44 lapyt;" l `NNN 0d$*$Ifgd;kd-$$IflF $x x x t06    44 lapyt;l m p `NNN 0d$*$Ifgd;kd$$IflF $x x x t06    44 lapyt; !Y!`NNN 0d$*$Ifgd;kdY$$IflF $x x x t06    44 lapyt;Y!Z!]!!!`NNN 0d$*$Ifgd;kd$$IflF $x x x t06    44 lapyt;!!!!!!!!!!`SSSSSSSS 0d*$gd kd$$IflF $x x x t06    44 lapyt; !!!!!!!!!!!!!!!!!!!!!!6"s""""$ 0d*$a$gda 0d*$gd ""4'>'@'t'u'v'(((j(l(((((ͼn]L]<,ha @CJOJQJ^JaJhU2@CJOJQJ^JaJ!h5@CJOJQJ^JaJ!hU25@CJOJQJ^JaJ'hU2hU25@CJOJQJ^JaJh_/@CJOJQJ^JaJhU2hU25@OJQJ^JhU25@OJQJ^Jh_/5@OJQJ^J!h_/5@CJOJQJ^JaJ'h_/h_/5@CJOJQJ^JaJh_/@OJQJ^J$h_/h_/@CJOJQJ^JaJ"$ $G%H%%H&&&3'4'?'@'Z'['v'w''''''''' 0d*$gd_/ & F 0d*$gd_/ 0d*$gd '((j(k(l(((((((((((((((((((((((( 0d*$gd_/((((((((((((((((((( ) )E)F))))$ 0d*$a$gd  0d*$gd_/( ) ) )9)D)E)F))))*+,....c0d0e0o0𰟓vlalREh@ z5@OJQJ^Jh,h,@OJQJ^Jh,5OJQJ^Jh,OJQJ^Jh,h,5OJQJ\^Jh,h,OJQJ^Jh,@OJQJ^J!h,5@CJOJQJ^JaJh,@CJOJQJ^JaJhr@CJOJQJ^JaJh?'@CJOJQJ^JaJha @CJOJQJ^JaJh @CJOJQJ^JaJ)))**.... /!/{///d0e0p0q000001 & F 0d*$gd, 0d*$^gd, 0d*$gd,o0p0q0000011X1Y1Z1111111ﾮrbrO;'hrhr5@CJOJQJ^JaJ$hrhr@CJOJQJ^JaJh,@CJOJQJ^JaJhr@CJOJQJ^JaJh?'@CJOJQJ^JaJhr@OJQJ^Jhh,5@OJQJ^Jhh5@OJQJ^Jh@OJQJ^Jh@ z5@OJQJ^Jh@ z@OJQJ^Jh,@OJQJ^Jh@ zh@ z5@OJQJ^J1Y1Z111111W3X333333344?4@4A4B4C4D4E4F4G4 0d*$gd,$ 0d*$a$gdr1133334?4U4\4z4{44/50525?57777ⷫ~kWF~7h?'h?'@OJQJ^J!h?'5@CJOJQJ^JaJ'h?'h?'5@CJOJQJ^JaJ$hrh?'@CJOJQJ^JaJh?'@CJOJQJ^JaJh-&h?'5@OJQJ^Jh-&5@OJQJ^Jh-&@OJQJ^Jh?'@OJQJ^Jhrhr@OJQJ^Jhrhr5@OJQJ^Jhr@OJQJ^J!hr5@CJOJQJ^JaJG4H4I4J4K4L4M4N4O4P4Q4R4S4T4U4{4|4444051525@5A5 0d*$gd?'$ 0d*$a$gd?' 0d*$gd,A5k7l7777799F99999 ::/:9:K: 0d$*$IfgdgH 0d*$^gd< & F 0d*$gd< & F 0d*$gd?' 0d*$gd,748t888F99::::;%<&<'<)<*<,<-<.</<1<2<5<6< h=s[^Jjh=s[Uh=s[jh=s[U^Jh<h-&@OJQJ^Jh-&@OJQJ^J!h<5@CJOJQJ^JaJhgHh<@OJQJ^Jh?'@OJQJ^Jh?'h?'@OJQJ^Jh<@OJQJ^JK:L:N:O:0 0d$*$IfgdgHkd $$Iflr${{{{| t0644 lap2ytgHO:P:Q:R: 0d$*$IfgdgHR:S:U:V:0 0d$*$IfgdgHkd $$Iflr${{{{| t0644 lap2ytgHV:W:X:Y: 0d$*$IfgdgHY:Z:\:]:0 0d$*$IfgdgHkd $$Iflr${{{{| t0644 lap2ytgH]:^:_:`: 0d$*$IfgdgH`:a:c:d:0 0d$*$IfgdgHkdC $$Iflr${{{{| t0644 lap2ytgHd:e:f:g: 0d$*$IfgdgHg:h:j:k:0 0d$*$IfgdgHkd $$Iflr${{{{| t0644 lap2ytgHk:l:m:n: 0d$*$IfgdgHn:o:q:r:0 0d$*$IfgdgHkd $$Iflr${{{{| t0644 lap2ytgHr:s:t:u: 0d$*$IfgdgHu:v:x:y:0 0d$*$IfgdgHkdk $$Iflr${{{{| t0644 lap2ytgHy:z:{:|: 0d$*$IfgdgH|:}:::0 0d$*$IfgdgHkd#$$Iflr${{{{| t0644 lap2ytgH:::: 0d$*$IfgdgH::::0 0d$*$IfgdgHkd$$Iflr${{{{| t0644 lap2ytgH:::: 0d$*$IfgdgH::::0 0d$*$IfgdgHkd$$Iflr${{{{| t0644 lap2ytgH:::: 0d$*$IfgdgH::::0## 0d*$gd,kdK$$Iflr${{{{| t0644 lap2ytgH:::::<;=;;;;;;;;;;;;;;;;;;;;; 0d*$gd< 0d*$gd,;;;;;;;;;;;;;;;;;;;;;&<(<)<+<,<-<dgd:nF 0d*$gd,-<.<0<1<3<4<5<6< 0d*$gd,gd:nF>00P:p:nF/ =!"#$% DpQD phoenix$$If!vh#vx :V l t065x pyt;$$If!vh#vx :V l t065x pyt;$$If!vh#vx :V l t065x pyt;$$If!vh#vx :V l t065x pyt;$$If!vh#vx :V l t065x pyt;$$If!vh#vx :V l t065x pyt;$$If!vh#vx :V l t065x pyt;$$If!vh#vx :V l t065x pyt;$$If!vh#vx :V l t065x pyt;$$If!vh#vx :V l t065x pyt;$$If!vh#vx :V l t065x pyt;$$If!vh#vx :V l t065x pyt;$$If!vh#vx :V l t065x pyt;$$If!vh#vx :V l t065x pyt;$$If!vh#vx :V l t065x pyt;$$If!vh#v{#v|:V l t065{5|p2ytgH$$If!vh#v{#v|:V l t065{5|p2ytgH$$If!vh#v{#v|:V l t065{5|p2ytgH$$If!vh#v{#v|:V l t065{5|p2ytgH$$If!vh#v{#v|:V l t065{5|p2ytgH$$If!vh#v{#v|:V l t065{5|p2ytgH$$If!vh#v{#v|:V l t065{5|p2ytgH$$If!vh#v{#v|:V l t065{5|p2ytgH$$If!vh#v{#v|:V l t065{5|p2ytgH$$If!vh#v{#v|:V l t065{5|p2ytgH$$If!vh#v{#v|:V l t065{5|p2ytgH^# 666666666vvvvvvvvv66666686666666666666666666666666666666666666666666666666hH6666666666666666666666666666666666666666666666666666666666666666662 0@P`p2( 0@P`p 0@P`p 0@P`p 0@P`p 0@P`p 0@P`p8XV~_HmH nH sH tH X`X Normal1$7$8$H$$CJOJQJ^J_HaJmH sH tH DA D Default Paragraph FontRi@R  Table Normal4 l4a (k (No List 8+@8  Endnote Text^J>*`> Endnote ReferenceH*:@:  Footnote Text^J@&`!@ Footnote ReferenceH*TT TOC 1/ $ 0d*$]^`0HH TOC 2# $ d*$]^HH TOC 3# $ d*$]^HH TOC 4# $ d*$]^HH TOC 5# $ d*$]^HH TOC 6# $0d*$^`0@@ TOC 70d*$^`0HH TOC 8# $0d*$^`0HH TOC 9# $ 0d*$^`0L L Index 1# $ 0d*$^`0D D Index 2 $ d*$^D.D  TOA Heading $d*$."@. Caption^J:/: _Equation Captionjj Ro5 Table Grid7:V!0!@"@ < List Paragraph "^PK![Content_Types].xmlN0EH-J@%ǎǢ|ș$زULTB l,3;rØJB+$G]7O٭V$ !)O^rC$y@/yH*񄴽)޵߻UDb`}"qۋJחX^)I`nEp)liV[]1M<OP6r=zgbIguSebORD۫qu gZo~ٺlAplxpT0+[}`jzAV2Fi@qv֬5\|ʜ̭NleXdsjcs7f W+Ն7`g ȘJj|h(KD- dXiJ؇(x$( :;˹! I_TS 1?E??ZBΪmU/?~xY'y5g&΋/ɋ>GMGeD3Vq%'#q$8K)fw9:ĵ x}rxwr:\TZaG*y8IjbRc|XŻǿI u3KGnD1NIBs RuK>V.EL+M2#'fi ~V vl{u8zH *:(W☕ ~JTe\O*tHGHY}KNP*ݾ˦TѼ9/#A7qZ$*c?qUnwN%Oi4 =3N)cbJ uV4(Tn 7_?m-ٛ{UBwznʜ"Z xJZp; {/<P;,)''KQk5qpN8KGbe Sd̛\17 pa>SR! 3K4'+rzQ TTIIvt]Kc⫲K#v5+|D~O@%\w_nN[L9KqgVhn R!y+Un;*&/HrT >>\ t=.Tġ S; Z~!P9giCڧ!# B,;X=ۻ,I2UWV9$lk=Aj;{AP79|s*Y;̠[MCۿhf]o{oY=1kyVV5E8Vk+֜\80X4D)!!?*|fv u"xA@T_q64)kڬuV7 t '%;i9s9x,ڎ-45xd8?ǘd/Y|t &LILJ`& -Gt/PK! ѐ'theme/theme/_rels/themeManager.xml.relsM 0wooӺ&݈Э5 6?$Q ,.aic21h:qm@RN;d`o7gK(M&$R(.1r'JЊT8V"AȻHu}|$b{P8g/]QAsم(#L[PK-![Content_Types].xmlPK-!֧6 0_rels/.relsPK-!kytheme/theme/themeManager.xmlPK-!0C)theme/theme/theme1.xmlPK-! ѐ' theme/theme/_rels/themeManager.xml.relsPK] 64  PE"(o0176<!#%'),4=ACEHM Rmsil Y!!!"'()1G4A5K:O:R:V:Y:]:`:d:g:k:n:r:u:y:|::::::::;-<6< "$&(*+-./012356789:;<>?@BDFGIJKLMNOPQRSTUVWXYZ[\]^_`8@0(  B S  ? =Byw)})3%4&4(4)4+4,4-4.404143474  ((&4(4)4+4,4-4.40414347433334%4744%4&4&4(4,4-4.404143474ddgc]*"WLdGd7oj YZq >....()()))h^`OJQJo(hHh^`OJQJ^Jo(hHohp^p`OJQJo(hHh@ ^@ `OJQJo(hHh^`OJQJ^Jo(hHoh^`OJQJo(hHh^`OJQJo(hHh^`OJQJ^Jo(hHohP^P`OJQJo(hHh^`OJQJo(hHh^`OJQJ^Jo(hHohp^p`OJQJo(hHh@ ^@ `OJQJo(hHh^`OJQJ^Jo(hHoh^`OJQJo(hHh^`OJQJo(hHh^`OJQJ^Jo(hHohP^P`OJQJo(hHh^`OJQJo(hHh^`OJQJ^Jo(hHohp^p`OJQJo(hHh@ ^@ `OJQJo(hHh^`OJQJ^Jo(hHoh^`OJQJo(hHh^`OJQJo(hHh^`OJQJ^Jo(hHohP^P`OJQJo(hHh^`OJQJo(hHh^`OJQJ^Jo(hHohp^p`OJQJo(hHh@ ^@ `OJQJo(hHh^`OJQJ^Jo(hHoh^`OJQJo(hHh^`OJQJo(hHh^`OJQJ^Jo(hHohP^P`OJQJo(hHh^`OJQJo(hHh^`OJQJ^Jo(hHohp^p`OJQJo(hHh@ ^@ `OJQJo(hHh^`OJQJ^Jo(hHoh^`OJQJo(hHh^`OJQJo(hHh^`OJQJ^Jo(hHohP^P`OJQJo(hHdc]*Gd7og YZqWL WP List 0                                             10`/-0&.{1"-&Ro53b:<}E:nFxF@P.VR[=s[|ikrQs@ zu},=_/YRr M-'br2 -qU2/8gHa ?'f;pE&4(4@64@UnknownG*Ax Times New Roman5Symbol3. *Cx Arial?= *Cx Courier New;WingdingsA$BCambria Math")PRPR^, ^^, ^!)Pxx2 4 43Q)PP?:nF2!xx EC 278 - StatisticsMichael LeClairMleclair$      Oh+'0Hx    (08@EC 278 - StatisticsMichael LeClairNormal Mleclair2Microsoft Office Word@@(ܺ@(ܺ ^,՜.+,0 hp  Fairfield University^ 4 EC 278 - Statistics Title  !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`acdefghijlmnopqrstuvwxyz{|}~Root Entry FData b1TablekI3WordDocument@SummaryInformation(DocumentSummaryInformation8CompObjr  F Microsoft Word 97-2003 Document MSWordDocWord.Document.89q