Syllabus for Statistics 101-106 (Fall 98)

The primary textbook for this course is

Introduction to the Practice of Statistics, 3rd edition
      by David S. Moore and George P. McCabe.  

The accompanying  Minitab Manual  by Michael Evans
is recommended as a gentle introduction to Minitab.

In the list that follows, references to section Y of chapter X of the textbook are given as M&M §X.Y.

Most Tuesday lectures will be based on a single Chapter of M&M.
Students should expect to read about a Chapter each week.

The notes are all in Adobe Acrobat pdf format. You will need version 3.0, or later, of the Acrobat Reader (free from Adobe) to read the pdf files.

Plan for Pollard lectures (all in 220 Dunham Lab)

• THURSDAY 3 SEPTEMBER
  Introduction and overview.
  Description of Thursday Sections by Section leaders.
  Following the lecture, students who have not already signed up for a Section
  should add their names to signup lists, in a Section that is not already filled.
  Homework sheet 0 assigned (to get you started); due Thursday 10 September.

1. TUESDAY 8 SEPTEMBER
   Read M&M Chapter 1.
   Graphical display of data: dotplots, histograms, stemplots, and boxplots.
   Numerical summaries: center (mean, median) and spread (standard deviation, interquartile range).
   Standardization and rescaling.
   Smooth approximations to histograms: densities, normal approximation, normal quantile/probability plots.
   Thursday: Homework sheet 1 assigned; due Thursday 17 September.
   Notes for the lecture, and extra picture showing distributions for final exam and classwork in Yale grades data.

2. TUESDAY 15 SEPTEMBER
   Read M&M § 2.1 through M&M § 2.4, and M&M § 2.7.
   Skip M&M § 2.5 (maybe discussion of logarithmic transformation in Sections).
   Postpone M&M § 2.6
   Association between two (or more) variables.
   Scatterplots: smoothing (maybe)
   Linear association, correlation.
   Least squares fit of a straight line. Relationship between slope of least squares line and correlation.
   Interpretation of r².
   Traps and difficulties: outliers, influential points, lurking variables.
   Thursday: Homework sheet 2 assigned; due Thursday 24 September.
   Notes for the lecture.

3. TUESDAY 22 SEPTEMBER
   Read M&M § 3.1 and M&M § 3.2, but skip bit about tables of random digits (use Minitab).
   Read M&M § 3.3 and M&M § 3.4.
   A little bit about experimental design: randomization (some Sections might cover more; also see Lecture 7).
   Sampling: simple random samples, and complex sampling methods.
   Comparison between sampling and full enumeration.
   Sampling variability.
   Thursday: Homework sheet 3 assigned; due Thursday 1 October.
   Notes for the lecture.
   New Haven age distribution, as downloaded from the Census web site.
   Plan for Census 2000.
   The recent court order regarding the challenge to the plan for Census 2000.

4. TUESDAY 29 SEPTEMBER
   Read M&M Chapter 4 only if you want to (or if prescribed in Section).

   I find the M&M treatment of probability disappointing.
   I will write and distribute notes covering much the same material,
   but with more emphasis on conditional probabilities,
   and using some of the ideas from M&M§ 2.6 as illustration.

   Probability and randomness.
   Conditional probabilites.
   Bayes's rule.
   Random variables. Discrete and continuous distributions.
   Means and variances.
   Thursday: Homework sheet 4 assigned; due Thursday 8 October.
   Notes for the lecture, and more.

5. TUESDAY 6 OCTOBER
   Read M&M § 5.1, but ignore two starred parts at the end.
   Read M&M § 5.2. Skip M&M § 5.3.
   Sampling distributions of counts, proportions and averages.
   Binomial distribution.
   Normal approximations.
   Thursday: Homework sheet 5 assigned; due Thursday 15 October.
   Notes for the lecture. Example of a Minitab macro. Chapter from the Minitab manual regarding the use of simple (=global) macros.

6. TUESDAY 13 OCTOBER
   Read M&M Chapter 6.
   Section leaders will decide how much emphasis to place on M&M § 6.3.
   Read M&M § 8.2 (probably need to read M&M § 8.1 as well).
   Confidence intervals and significance tests for a single normal. Power functions.
   Comparison of two normals.
   Comparison of two proportions via normal approximation with estimated variances.
   Thursday: Homework sheet 6 assigned; due ???.
   Notes for the lecture.

7. TUESDAY 20 OCTOBER
   Read M&M § 7.1 and § 7.2, ignoring starred parts.
   Reread M&M § 3.2.
   The effects of estimated variances on normal approximations.
   t-distributions.
   Comparison of two means: pooling of estimates of variances, or paired observations.
   No homework sheet 7 from DBP this week. Some Sections have postponed sheet 6.
   Notes for the lecture.

8. TUESDAY 27 OCTOBER
   Read M&M Chapter 9.
   Read supplemental notes on chi-square.
   Chi square approximations and tests, with two-way tables as an example.
   Thursday: Homework sheet 8 assigned; due Thursday 5 November.
   Notes for the lecture.

9. TUESDAY 3 NOVEMBER
   Read M&M § 10.1 and § 10.2 up to page 686.
   Inference for simple linear regression: normal theory.
   Fighting your way through computer output.
   Thursday: Homework sheet 9 assigned; due Thursday 12 November.
   Notes for the lecture. A picture from Scientific American showing the lean of the Tower over time.

10. TUESDAY 10 NOVEMBER
    Read M&M Chapter 11.
    Multiple regression.
    Thursday: Homework sheet 10 assigned; due Thursday 19 November.
    Notes for the lecture.
    

11. TUESDAY 17 NOVEMBER
    Read M&M Chapters 2 and 11 again.
    Section leaders will decide how much of Chapters 12 and 13 to cover formally.
    They will assign the readings, and possibly even take over the Tuesday lecture. (Details to be announced.)
    Variations on regression: explanatory categorical variables.
    Traps, blunders, pitfalls, diagnostics.
    Thursday: Homework sheet 11 assigned; due Thursday 3 December.
    Notes for the lecture.

12. TUESDAY 1 DECEMBER
    Pulling it all together. A big example.
    Notes for the lecture.

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