\r\n\tThis is a one semester module. The class will usually meet once per week with three hours per session with a 1520 minute break.
\r\n\tThe lecture is scheduled on Tuesday, 14 pm, in SDE1 SR7.
\r\n\tAfter the first half session, we will occasionally move to SDE1 CR4 for the lab sessions.
\n\t\t\t\tWeek Dates  \n\t\t\t\tLecture 
\n\t\t\t\t1 Jan 13  \n\t\t\t\tNo Class (Due to MUP Intensive Workshop) 
\n\t\t\t\t1 Jan 20  \n\t\t\t\tNo Class (Due to MUP Intensive Workshop) 
\n\t\t\t\t2 Jan 27  \n\t\t\t\tIntroduction and Expectations: Introduction to statistics and its application to urban planning 
\n\t\t\t\t3 Jan 28 \n\t\t\t\t(Make up, 710 pm @ SR10)  \n\t\t\t\tDescriptive Statistics: Sample and population; Central tendency (mean/median/mode); Dispersion (variance, standard deviation) 
\n\t\t\t\t4 Feb 3  \n\t\t\t\tProbability I: Introduction to probability and probability distribution; Random events; Bayes’s Rule; Binomial/Normal/Poisson distribution \n\t\t\t\t

\n\t\t\t\t5 Feb 9 \n\t\t\t\t(Make up, 710 pm @ SR14)  \n\t\t\t\tProbability II: Interpretation and application of the normal probability distribution; Population distribution vs. sampling distribution; Z score \n\t\t\t\t

\n\t\t\t\t6 Feb 10  \n\t\t\t\tStatistical Inference: Differentiation of a sample and a population; Confidence interval; Significance tests \n\t\t\t\t

\n\t\t\t\tFeb 21Mar 1  \n\t\t\t\tMID SEMESTER BREAK 
\n\t\t\t\t7 Mar 3  \n\t\t\t\tResearch Design: Potential topics; Research process; Data collection; Data organization \n\t\t\t\t

\n\t\t\t\t8 Mar 10  \n\t\t\t\tHypotheses Concerning a Single Population: Logic of hypothesis testing; Definition of research/null hypotheses; Type I and Type II errors \n\t\t\t\t

\n\t\t\t\t9 Mar 17  \n\t\t\t\tHypotheses Comparing Two Populations: Inferences for two population means; Comparing proportions from independent samples \n\t\t\t\t

\n\t\t\t\t10 Mar 24  \n\t\t\t\tAdditional Hypothesis Tests: Oneway ANOVA (Analysis of Variance); Fdistribution; Association between categorical variables \n\t\t\t\t

\n\t\t\t\t11 Mar 31 \n\t\t\t\t(2:155:15 PM, Move to SDE Mezz for the 2nd half)  \n\t\t\t\tLinear Regression I: Describing the relation between two variables; Introduction to simple, linear regression analysis \n\t\t\t\t

\n\t\t\t\t12 Apr 7  \n\t\t\t\tLinear Regression II: Interpretation of a coefficient of regression and correlation; Multiple regressions; Recognition of the limitations of regressions \n\t\t\t\t

\n\t\t\t\t13 Apr 14  \n\t\t\t\tFinal Thoughts and Project Presentation/Discussion 
\r\n\t\t\t\tWeek Dates  \r\n\t\t\t\tReading List 
\r\n\t\t\t\t2 Jan 27  \r\n\t\t\t\tIntroduction and Expectations: \r\n\t\t\t\t1. Sullivan Chapter 1 Data Collection; Chapter 2 Organizing and Summarizing Data \r\n\t\t\t\t2. Weiss Chapter 1 The Nature of Statistics \r\n\t\t\t\t2. Against All Odds #1 What is Statistics #2 Stemplots #3 Histograms 
\r\n\t\t\t\t3 Jan 28 \r\n\t\t\t\t(Makeup)  \r\n\t\t\t\tDescriptive Statistics: \r\n\t\t\t\t1. Sullivan Chapter 2 Organizing and Summarizing Data; Chapter 3 Numerically Summarizing Data \r\n\t\t\t\t2. Weiss Chapter 3 Descriptive Measures \r\n\t\t\t\t3. Against All Odds #4 Measures of Center #5 Boxplots #6 Standard Deviation 
\r\n\t\t\t\t4 Feb 3 \r\n\t\t\t\t  \r\n\t\t\t\tProbability I: \r\n\t\t\t\t1. Sullivan Chapter 5 Probability; Chapter 6 Discrete Probability Distributions \r\n\t\t\t\t2. Weiss Chapter 4 Probability Concepts; Chapter 5 Discrete Random Variables \r\n\t\t\t\t3. Against All Odds #13 TwoWay Tables #18 Introduction to Probability #19 Probability Models #20 Random Variables #21 Binomial Distributions 
\r\n\t\t\t\t5 Feb 9 \r\n\t\t\t\t(Makeup)  \r\n\t\t\t\tProbability II: \r\n\t\t\t\t1. Sullivan Chapter 7 The Normal Probability Distribution; Chapter 8 Sampling Distributions \r\n\t\t\t\t2. Weiss Chapter 6 The Normal Distribution \r\n\t\t\t\t3. Against All Odds #7 Normal Curves #8 Normal Calculations #9 Checking Assumption of Normality #22 Sampling Distribution 
\r\n\t\t\t\t6 Feb 10  \r\n\t\t\t\tStatistical Inference: \r\n\t\t\t\t1. Sullivan Chapter 9 Estimating the Value of a Parameter \r\n\t\t\t\t2. Weiss Chapter 7 The Sampling Distribution of the Sample Mean; Chapter 8 Confidence Intervals for One Population Mean \r\n\t\t\t\t3. Against All Odds #24 Confidence Intervals #25 Test of Significance 
\r\n\t\t\t\t7 Mar 3  \r\n\t\t\t\t Research Design: \r\n\t\t\t\t1. Sullivan Chapter 1 Data Collection; Chapter 2 Organizing and Summarizing Data \r\n\t\t\t\t2. Weiss Chapter 1 The Nature of Statistics; Chapter 2 Organizing Data \r\n\t\t\t\t3. Against All Odds #15 Designing Experiments #16 Census and Sampling #17 Samples and Surveys 
\r\n\t\t\t\t8 Mar 10 \r\n\t\t\t\t  \r\n\t\t\t\tHypotheses Concerning a Single Population: \r\n\t\t\t\t1. Sullivan Chapter 10 Hypothesis Tests Regarding a Parameter \r\n\t\t\t\t2. Weiss Chapter 9 Hypothesis Tests for One Population Mean \r\n\t\t\t\t3. Against All Odds #26 Small Sample Inference for One Mean 
\r\n\t\t\t\t9 Mar 17 \r\n\t\t\t\t  \r\n\t\t\t\tHypotheses Comparing Two Populations: \r\n\t\t\t\t1. Sullivan Chapter 11 Inferences on Two Samples \r\n\t\t\t\t2. Weiss Chapter 10 Inferences for Two Population Means \r\n\t\t\t\t3. Against All Odds #27 Comparing Two Means 
\r\n\t\t\t\t10 Mar 24 \r\n\t\t\t\t  \r\n\t\t\t\tAdditional Hypothesis Tests: \r\n\t\t\t\t1. Sullivan Chapter 12 Inferences on Categorical Data \r\n\t\t\t\tChapter 13 Comparing Three or More Means \r\n\t\t\t\t2. Weiss Chapter 13 ChiSqaure Procedures Chapter 16 Analysis of Variance (ANOVA) \r\n\t\t\t\t3. Against All Odds #29 Inference for TwoWay Tables #31 OneWay ANOVA 
\r\n\t\t\t\t11 Mar 31  \r\n\t\t\t\tLinear Regression I: \r\n\t\t\t\t1. Sullivan Chapter 4 Describing the Relation between Two Variables \r\n\t\t\t\t2. Weiss Chapter 14 Descriptive Measures in Regression and Correlation \r\n\t\t\t\t3. Against All Odds #10 Scatterplots #11 Fitting Lines to Data #12 Correlation 
\r\n\t\t\t\t12 Apr 7  \r\n\t\t\t\tLinear Regression II: \r\n\t\t\t\t1. Sullivan Chapter 14 Inference on the LeastSquare Regression Model and Multiple Regression \r\n\t\t\t\t2. Weiss Chapter 14 Descriptive Measures in Regression and Correlation; Chapter 15 Inferential Methods in Regression and Correlation \r\n\t\t\t\t3. Against All Odds #14 The Question of Causation #30 Inference for Regression 