| SES # | TOPICS | LECTURE NOTES |
|---|---|---|
| L1 | Introduction to Course | Introduce instructors; how the course is set up; describe "Peer Instruction" and expectations; divide into groups for recitations or labs. Give first assignment requesting areas of interest and the reading for next lecture on arguments. What is statistics? The three parts of statistics: collection, evaluation, and drawing conclusions. Discuss the schematic diagram for our study of statistics. (PDF) |
| L2 | What is an Argument? | Premise; conclusion; deductive vs. inductive; falsehoods and fallacies; discuss argument assignment and the link to quantitative reasoning. (PDF) |
| L3 | Measurement | Variable; indicator; observation; construct; validity; reliability; bias; ikert scale; qualitative; quantitative; discrete; continuous; nominal; ordinal; interval; ratio; indices. (PDF) |
| L4 | Research Design | Research design and its implications for analysis. Begin univariate data analysis segment. (PDF) |
| L5 | Frequency Distributions, Histograms, Stemplots, Boxplots, Measures of Dispersion | Summarizing and presenting univariate data; stem and leaf plots; frequency distributions; relative frequency; cumulative frequency; ogives; pareto plots; histograms; pie charts; boxplots. Mean; median; mode; the five number summary; variance and standard deviation; grouped data. (PDF) |
| L6 | Introduction to Probability | Basics of probability theory; general rules of probability. (PDF) |
| L7 | The Normal and Binomial Distributions | Characteristics of the normal distribution; z-scores; binomial probabilities. (PDF) |
| L8 | Sampling | Sampling and probability; bias in sampling; strategies of sampling - random, systematic, stratified, cluster, quota, self-selected, purposive; sampling in the U.S. census; sampling strengths and weaknesses; geographic aggregation; margin of error. (PDF) |
| L9 | Basics of Confidence Intervals and Tests of Significance | Introduction to inference; estimating a population mean; estimating a population standard deviation; the standard error; t distribution; estimating with confidence; how confidence intervals behave. (PDF) |
| L10 | Recap: CIs and Inference for Means | Review the theory of sampling distributions and confidence intervals for means. (PDF) |
| L11 | CIs and Inference for Proportions and Hypothesis Testing | Proportions: estimating for population, confidence intervals. (PDF) Hypothesis testing: The null and alternative hypotheses; hypothesis testing with samples; one and two tailed tests; determining sample size; p-Values. |
| L12 | Testing the Difference Between Two Groups | Issues with inference. Differences of means: independent and dependent samples, equal vs. unequal variances. (PDF) |
| L13 | Testing the Difference Between Two Groups (cont.) | Differences of proportions. Discuss mid-term and paper requirements. (PDF) |
| L14 | Review for Mid-term | Review of all major concepts to be covered on the mid-term exam. |
| L15 | Mid-term Exam | |
| L16 | Analyzing Categorical Data | Constructing contingency tables - 2 way; marginals; percentage difference; larger contingency tables; chi-square statistical significance. (PDF) Discuss final paper descriptive analysis due. |
| L17 | Scatterplots and Correlation | Exploring bivariate relationships; r. (PDF) |
| L18 | Introduction to Regression Analysis | Simple linear regression; terminology and interpretation; causation vs. association; predicted values; r square. (PDF) |
| L19 | Regression (cont.) | The assumptions of linear regression. (PDF) |
| L20 | Multiple Regression | Partial slopes, adjusted R2, and assumptions for multiple regression. (PDF) |
| L21 | Multiple Regression (cont.) | Constructing predictive models; SPSS output; regression output and data management. (PDF) |
| L22 | Spatial Data Analysis | GIS; GeoDa; spatial autocorrelation. |
| L23 | The Census | How the Census is conducted, organized, and used in practice. |
| L24 | Quiz | Regression quiz and Q&A on final paper. |
| L25 | Research Design and Regression Analysis | Example application of research involving regression technique applied to a contemporary urban topic. |
| L26 | Wrap-up | Review and wrap-up. Putting your QR skills to work. |