Course Schedule Note: Be sure to hit the Reload or Refresh button before viewing this page!

Note: This version of the schedule is not yet finalized. Use it as a guide, but be aware that it is subject to change.

Jan. 15 – Introduction to Course Goals, Objective, Logistics, and Resources

Introduction to Course

Overview of STA110C: the course goals and objectives.
Become familiar with course logistics: requirements, grading policies, schedule.
Printed course resources: text, How to Think Straight, JMP-IN.

Introduction to Computing Resources

Where are the public computing clusters?
What is the class Home page used for?
What is the class News group used for?
What is JMP-IN?
How do I access the Homepage, Newsgroup, and JMP-IN?
How do I get help with computing problems?
Assignment: Log-in to a terminal, access Homepage, post to Newsgroup, and use JMP-IN to find the mean of 10 numbers.

Jan. 20, 22 – Systematic Data Collection- Systematic Empiricism and Experimental Design

What is systematic empiricism, and why is falsifiability important?
Why is systematic empiricism a useful and necessary adjunct to "common sense" and testimonials?
Introduction to experimental design.
What are independent variables vs. dependent variables?
What are experimental and observational studies, and what are the advantages and disadvantages of each?
What data collection procedures give you the most information?
Know what a simple random sample is, why it is important, and the best ways to obtain one.
Become familiar with different sampling strategies as exemplified by the Gallup Poll and the Current Population Survey.
Distinguish between chance error and bias, and know the characteristics of each.
What are experimental and control groups?
What do the following terms mean: placebo, randomized, confounding, double blind, sample, and population?
What is the difference between association and causation?
Assignment: Read chapters 1, 2, 19, and 22 in Freedman, Pisani, and Purves (FPP), pp. 9-36 in How to Think Straight About Psychology (HTS), and do Homework 1.

Jan. 27, 29 – Descriptive Statistics: Graphing and Describing Data Distributions

What are operationism, and essentialism?
Learn what it means to control for a variable, and what a control variable is.
Learn the scales of measurement classification schemes: nominal vs. ordinal vs. interval vs. ratio; qualitative vs. quantitative; discrete vs. continuous* and how JMP-IN classifies each.
Introduction to histograms (ignore details in text!).
What are the major measures of central tendency, and what are the advantages of each?
What are the major measures of variability, and what are the advantages of each?
Learn to compute the Range, Semi-Interquartile Range, and Standard Deviation (SD).
Assignment: Read chapters 3 (skip pp. 31-41) and 4 of FPP, pp. 37-72 in HTS, and do Homework 2.

*Not in text.

Feb. 3, 5 – The SD, the Normal Curve, and Percentiles

Quiz 1, Feb. 3
Understand the properties of the SD.
Normal approximation to data distributions.
Specify areas under the normal curve using Table in back of text.
Learn what z-scores are and how to calculate them.
Calculate and interpret percentiles.
Assignment: Read chapters 5 and 7 (skip ch. 6) in FPP and do Homework 3.

Feb. 10, 12 – Correlation and Regression

Create scatterplots.
Define and understand association.
Calculate and interpret correlation coefficients (r).
Recognize factors that can result in misleading correlation coefficients.
Know the difference between correlation and causation.
Become familiar with the third variable problem (confounding variable), the directionality problem, and the possible effects of selection bias on correlation.
Assignment: Read chapters 8 and 9 of FPP, chapter 5 of HTS and do HW 4.

Feb. 17-19 – Predicting Values of Y Based on Known Values of X

Quiz 2, Feb. 17
Write the equation for a line and determine the slope and intercept.
Calculate and interpret linear regression equations.
Plot and interpret regression lines.
Identify residuals.
Understand the proper use of regression and the regression fallacy.
Learn to calculate and interpret the RMS error.
Assignment: Read chapters 10 – 12 of FPP and do Homework 5.

Feb. 24th -- Midterm

Feb. 26, Probability Introduced

Define frequency theory of probability.
Introduction of the box model.
Understand the difference in drawing with replacement and without replacement.
Define and calculate conditional probabilities.
Learn to recognize when and how to apply the multiplication rule.
Identify when two events are independent and understand what that means.
Identify when two events are mutually exclusive and understand what that means.
Learn to recognize when and how to apply the addition rule.
Assignment: Read chapters 13, 14 and 15 of FPP, chapter 10 of HTS.

March 3, 5 – Probability Continued

Learn Bayes Theorem and when to apply it.
Know when and how to apply the binomial formula.
Know the Law of Averages.
Learn what a sampling distribution is.
Become familiar with the box model for the sum of draws.
Compute and interpret the expected value (EV) and the standard error (SE) for a chance process.
Learn how and when to use the normal curve approximation to calculate probabilities.
Learn how to calculate the SD for a box with only two numbers and why you would want to.
Distinguish frequency histograms from probability histograms.
Assignment: Read chapters 16 – 18 of FPP, and do Homework 6.

March 10, 12 – Sampling and Chance Errors in Estimating Population Percentages

Quiz 3, March 10
Know what affects the size of errors in estimating population percentages.
Calculate and interpret the expected value and standard error for percentages.
Calculate confidence intervals for percentages.
Learn how to correctly interpret confidence intervals.
Know what affects the size of errors in estimating population means.
Calculate and interpret the expected value and standard error for means.
Become familiar with the Central Limit Theorem and know when to apply it.
Calculate confidence intervals for means.
Know when the sampling distribution of means will be approximately normal.
What is the difference between SD and SD+?
Assignment: Read chapters 20, 21, and 23 in FPP and do Homework 7.

March 24, 26 – Chance Errors in Estimating Means, Introduction to Hypothesis Testing, and the Single-Mean Hypothesis test.

Learn to set up and distinguish the null hypothesis and the alternative hypothesis.
Learn what a test statistic is.
Calculate and interpret the observed significance level (p-value) of a test statistic.
Understand the logic of hypothesis testing.
Know when to reject the null hypothesis and when to retain it.
Know how to carry out and interpret a single mean hypothesis test.
Know when to use the t-test and when to use the z-test.
Learn how to obtain, use, and interpret degrees of freedom.
Understand the following: p-value, alpha, observed value of test statistic, critical value of test statistic.
Recognize that comparing p-value to alpha is equivalent to comparing the observed value of the test statistic to the critical value of the test statistic.
Understand Type I and Type II* errors in hypothesis testing.
Understand the concept of statistical power* and how it relates to alpha, sample size, and study design.
Understand the following limitations to significance testing: arbitrary cut-off, data snooping, statistical versus real-world significance, interpretability depends on quality of study design, irrelevance of non-significance from low-power studies.
Assignment: Read chapters 26, 29 in FPP and do Homework 8.

March 31, April 2 – Testing for the Difference Between Means and the Chi-Square Test

Quiz 4, March 31
Be able to calculate and interpret the standard error for a difference.
Learn how to do a hypothesis test for the difference between means drawn from independent samples.
Know how to recognize and analyze the difference in means for two dependent samples.
Know when and how to use the chi-square test for goodness of fit..
Know when and how to use the chi-square test for independence.
Assignment: Read chapter 27, 28 in FPP and do Homework 9.

April 7, 9 – One Way Analysis of Variance (ANOVA)

Reserve Readings
Homework 10.

April 14, 16 -- Two-Way Anova

Quiz 5, April 14.
Reserve Readings.
Homework 11.

April 21, 23 -- Multiple Regression

Reserve Readings.
Homework 12.

April 28 Project Presentations

Final Exam: Wednesday, May 6, 1998, 9 am - noon