Logo

STA 101 Course Webpage - Lecture Schedule

Lecture Schedule

Date Topics Covered Background Reading
05/14 Introduction, Purpose of Statistics, Populations, Parameters, Statistics, Sample,
Scientific Method
Section 1 - Data Collection
05/15Sampling techniques Overview, Designed Experiments, Principles of good experimental design, Randomization in designed experiments, Blind and double blind experiments
Chapter 1
05/16Observational Studies, benefits of observational studies, sampling techniques in observational studies, types of bias in observational studies
Chapter 2
Section 2 - Summarizing Data
05/19 Introduction to descriptive statistics, distributions, types of data, techniques for summarizing quantitative data.
Chapters 3 and 4
05/20 Describing plots, mean, standard deviation, IQR, 5 number summary, box plots. Chapters 3 and 4
05/21 Strategies for summarizing categorical data, pie charts, bar charts, cross-tabulating data, strategies for summarizing bivariate data, scatter plots, linear correlation. Chapters 7 and 8
Section 3 - Probability
05/22 Introduction to probability, definition, random variables, distribution of random variables, calculating probabilities for simple random variables, "or" and probability. Chapter 14
05/23 "and" and probability, "or" and probability revisited, independence, multiplication rule. Chapter 13
05/26Memorial Day -- no class. Enjoy the break.
05/27 Introduction to probability for continuous random variables, standardizing values, the normal distribution. Chapter 5
05/28 Calculating probabilities for normal random variables, finding percentiles for normal random variables, examples Chapter 5
Section 4 - Inference on the Mean of a Population
05/29 Introduction to analysis, writing statistical hypotheses, p-values, steps to hypothesis testing. Chapter 26
05/30statistical significance, practical significance, sampling distributions, standard errors, central limit theorem Chapter 26
06/02 Errors in hypothesis testing, review for the exam Chapter 26
06/03 Midterm Exam 1 - Covering material in Sections 1-3
06/04 Constructing confidence intervals, confidence levels, margin of error Chapter 21
06/05 Steps to inference with confidence intervals, duality of confidence intervals and hypothesis tests, introduction to t procedures. Chapter 26
06/06 T-test, t confidence intervals, robustness, steps to hypothesis testing using the t distribution Chapter 26
06/09 Introduction to analysis of proportions, sampling distribution of p-hat, hypothesis testing and confidence intervals for proportions. Hypothesis testing and confidence intervals in general. Chapter 21
06/10 No Class
Section 5 - Comparing Means of Several Populations
06/11 Comparing 2 sample means, writing hypotheses for 2 sample problems
Lecture Notes
06/12 Comparing 2 sample proportions, examples of two sample tests.
Lecture Notes
06/13 Introduction to ANOVA, the F-statistics, the ANOVA table, ANOVA hypotheses
Lecture Notes
Section 6 - Inference Using Regression
06/16 Final thoughts on ANOVA, Example, Introduction to Regression Methods, Review for Exam 2 Chapter 8
06/17 Midterm Exam 2 - Covers Sections 1-4
06/18 Example regression problem, residuals, r-squared, statistical inference in regression, review Exam 2 Chapter 10
06/19 Statistical inference in regression, t-testing for regression, the regression assumptions Chapter 10
06/20 Examples of regression problems, prediction intervals, Introduction to multiple linear regression Chapter 11
06/23 Introduction to the idea of multiple linear regression, course evaluations, review for Final Chapter 12
06/24 Reading Day
06/25 Final Exam 9-12