## Colorado State University — Pueblo, Spring 2017 Math 156, Introduction to Statistics Course Schedule and Homework Assignments

Here is a link back to the course syllabus/policy page.

This schedule is will be changing very frequently, please check it at least every class day, and before starting work on any assignment (in case the content of the assignment has changed).

Below, we refer to the class text Lies, Damned Lies, or Statistics as LDLoS. The whole book is available here, although below there will be links to particular sections of the book that you are asked to read and in which you will find problems to do.

If you see the symbol below, it means that class was videoed and you can get a link by e-mailing me. Note that if you know ahead of time that you will miss a class, you should tell me and I will be sure to video that day for you.

Homework for a particular day is due that day, either in class or handed in at my office by 3pm.

#### Week 1

• :
• :
• Read LDLoS up to and including §1.3.2
• Some content we discussed, terms defined:
• graphs for categorical variables:
• bar charts
• pie charts
• graphs for a quantitative variables:
• a stem-and-leaf plot
• the most important such graph: a histogram
• Hand in BI1. This will be an unusual one: write down two or three things you were surprised about in the organization of this course. Be specific, mention types or numbers or formats of some assignments, etc.
• :
• Some content we discussed, terms defined:
• histograms
• variants: frequency and relative frequency
• bins [or classes] and their edge behavior
• shape: symmetric, skew, multimodal
• Quiz 1 today (on material covered on Monday and Wednesday this week)
• Hand in HW1: problems 1.{1, 2, 3} on this page of LDLoS.
• Hand in BI2 (on an idea from Wednesday's class or readings)
• Today [Friday] is the last day to add classes.

#### Week 4

• :
• Some content we discussed, terms defined:
• going over Quiz 3
• going over HW3
• independent and dependent variables [also called explanatory and response variables]
• deterministic and non-deterministic relationships between variables
• scatterplots; their shape, strength, and direction
• Hand in BI9 (on an idea from Friday's class or readings)
• Hand in ASE3. See above, here and here, for the required parts of an ASE (the second of those explanations above also has a list of a few sites you could go to in order to find materials for an ASE, although of course something you are interested in yourself would probably be much more fun). Please look for something which mentions variability, standard deviation, quartiles, and/or outliers, or which uses the five-number summary or boxplots
• :
• Read LDLoS §2.2 and §2.3
• Some content we discussed, terms defined:
• qualitative description of the association shown in a scatterplot
• shape,
• strength, and
• direction
• the [Pearson] correlation coefficient $r$ of bivariate data
• defining formula
• computing with electronic tools
• always satisfies $-1\le r\le 1$
• meaning of the size of $|r|$
• meaning of the sign of $r$
• independence of units
• Hand in BI10 (on an idea from Monday's class or readings)
• :
• Some content we discussed, terms defined:
• the idea of linear regression
• sketching the line of best fit
• one point the regression line should go through: $(\overline{x},\overline{y})$.
• the residuals of a regression line
• the least squares regression line [LSRL]: definition
• formulæ for the LSRL
• Hand in BI11 (on an idea from Wednesday's class or readings)
• Quiz 4 today [on material from last Friday to this Wednesday]

#### Week 5

• :
• Read LDLoS Chapter 3 Intro & §3.1 & §3.2
• Some content we discussed, terms defined:
• going over Quiz 4
• going over HW4
• Review of equations of lines — particularly their slope and $y$-intercept
• Repeating (from Friday) the basic definitions and facts for the LSRL
• Simpson's Paradox (which is in our textbook LDLoS here)
• Applications of the LSRL:
• interpolation
• interpretation in a problem context of the slope and $y$-intercept of an LSLR
• Hand in BI12 (on an idea from Friday's class or readings)
• :
• Some content we discussed, terms defined:
• bivariate outliers
• sensitivity of the correlation coefficient and LSRL to outliers
• correlation is not causation
• extrapolation
• Review for Test I. See this review sheet.
• Hand in BI13 (on an idea from Monday's class or readings)
• Hand in HW5: problems 3.{1, 2, 3} on this page of LDLoS.
• :
• Test I in class today. Make sure you are comfortable with the material outlined on this review sheet. Don't forget your calculator, or other favorite electronic device, if you use one!

#### Week 6

• :
• Yes, we do have class today, even though it is the federal holiday commemorating the birthday of George Washington (who was actually born on February 22nd, 1732), although this holiday is often casually referred to as "Presidents' Day."
• Test I post-mortem.
• Hand in ASE4. Please try to find something which mentions or uses scatterplots, correlation or the correlation coefficient, or maybe even [linear] regression
• :
• Read LDLoS Introduction to Part 2, Introduction to Chapter 4, and §4.1
• Some content we discussed, terms defined:
• the idea of randomness
• sample spaces, outcomes, events
• the idea of probability, a probability model
• complement of a subset [event], notation $E^c$, translation into English: not
• probability rule for complements
• Hand in BI14. This is a special one: please write a paragraph about how you think Test I went for you. Are you perfectly content with how it turned out? If not, what do you think was the cause of the trouble? And what can you do next time to make things better?
• Hand in Test I revisions, if you like.
• :
• Some content we discussed, terms defined:
• intersection of sets [events], notation $A\cap B$, translation into English: and
• union of sets [events], notation $A\cup B$, translation into English: or
• disjoint events, notation $\emptyset$ for the empty set
• finishing the definition of a probability model
• Venn diagrams — how to fill in numbers correctly
• Hand in BI15 (on an idea from Wednesday's class or readings)
• Hand in HW6: problems 4.{1, 2, 3} on this page of LDLoS. [NOTE: due to network problems, this assignment was not posted until late Thursday afternoon. Therefore, if you hand it in on Monday, that will not be considered late!]

#### Week 7

• :
• Hand in HW6 [details above], if you did not do so on Friday
• Hand in BI16 (on an idea from Friday's class or readings)
• ASE5 is not due today -- in fact, no ASE is due this week; if you did one before seeing this notice, save it and use it in the future.
• Some content we discussed, terms defined:
• more on the ideas of sample spaces, events, and probability models
• finite probability models, such as [fair] coins and [fair] dice
• :
• Some content we discussed, terms defined:
• mutually exclusive is a synonym of disjoint
• the general rule for computing $P(A\cup B)$, whether or not the events $A$ and $B$ are disjoint
• starting conditional probability, including its formal definition, computing examples, etc.
• two events being independent
• Hand in BI17 (on an idea from Monday's class or readings)
• :
• Some content we discussed, terms defined:
• more examples of turning statements in English into formulæ with events, and computing their probabilities.
• more discussion of the difference (they're completely different!) between disjoint and independent, and the different uses they have
• very start of the idea of a random variables [RVs]
• Hand in BI18 (on an idea from Wednesday's class or readings)
• Hand in HW7: problems 4.{4, 5, 6} starting on this page of LDLoS; if you want a little extra time, this could come in on Monday without any penalty
• Quiz 5 was handed out today — if you didn't pick up a copy in class, e-mail your instructor and you will get a PDF by return email.

#### Week 8

• :
• :
• Reread LDLoS §4.3.1, §4.3.2, & §4.3.3
• Some content we discussed, terms defined:
• mostly working through recent terms/ideas even more
• discussion of what makes an RV either discrete or continuous
• Hand in BI20 (on an idea from Monday's class or readings)
• :
• Read LDLoS §4.3.4 & §4.3.5
• Some content we discussed, terms defined:
• [probability] density functions for continuous RVs
• the uniform distribution on an interval $[x_{min},x_{max}]$
• the Normal distribution with mean $\mu$ and standard deviation $\sigma$
• the standard Normal distribution
• Hand in BI21 (on an idea from Wednesday's class or readings)
• Quiz 6 today [on material from last Friday to this Wednesday]
• No homework due today: it will instead be due on Monday

#### Week 9

• :
• Some content we discussed, terms defined:
• standardizing a non-standard Normal RV
• the 68-95-99.7 Rule for Normal RVs
• using electronic tools to compute Normal probabilities.
• Hand in BI22 (on an idea from Friday's class or readings)
• No ASE due today — in fact, none due this week. Although there will be one due after Spring Break, so if you think you will be unable to work at all over the break, it might make sense to start that ASE now — maybe just going as far as finding a source and, if you are worried about whether it will make a good ASE, asking your instructor.
• Hand in HW8: problems 4.{7, 8, 9, 10} starting on this page of LDLoS
• :
• Review for Test II. See this review sheet.
• Hand in HW9, which is just problem 4.11 on this page of LDLoS
• Hand in BI23 (on an idea from Monday's class or readings)
• :
• Test II in class today. Make sure you are comfortable with the material outlined on this review sheet. Don't forget your calculator, or other favorite electronic device, if you use one!
• Today [Friday] is the last day to withdraw (with a W) from classes.

#### Week 10

• Spring Break! No classes, of course.

#### Week 11

• :
• Test II post-mortem.
• ASE6 was postponed to Wednesday, to give you more time to concentrate on thinking through Test II and doing excellent re-dos.
• :
• Read LDLoS Introduction to Chapter 5, and §5.1
• Some content we discussed, terms defined:
• population parameter
• representative
• bias, against which our strongest weapon is randomness
• voluntary sample bias
• simple random sample [SRS]
• Hand in BI24. This is a special one: please write a paragraph about how you think Test II went for you. Are you perfectly content with how it turned out? If not, what do you think was the cause of the trouble? And what can you do next time to make things better? Do you think the ideas you talked about in BI14 for test improvement were effective -- were you actually able to use them?
• Hand in ASE6. Please try to find something which mentions or uses Normal distributions [which is sometimes called a "bell[-shaped] curve"], uniformly distributed, or maybe even some article which talks about the uses of randomness or random numbers in modern science or computers ‐ e.g., sometimes this is called "using Monte Carlo methods." For this ASE only, and only if you talk about one of these last few topics, you may write a brief summary of something which is mostly an educational source, and which therefore does not have live data, variables, population, etc. Contact your instructor if you have any concerns about what you you intend to do.
• :
• Some content we discussed, terms defined:
• sample statistic
• The Law of Large Numbers [LoLNs]
• general strategies in simple surveys:
1. get as big a sample as possible
• e.g., to take advantage of the LoLNs
2. pick a good statistic
• e.g., the LoLNs says that $\overline{x}$ is a good statistic for $\mu$
• also, make sure survey questions are not misleading
3. use randomness
• always aim for the [nearly impossible] SRS
• wording effects
• always, for heaven's sake, avoid voluntary samples
• observational studies vs experiments [and relationship to inferences about causality]
• control group
• confounding
• lurking variable
• placebo effect, placebo
The British doctor Ben Goldacre has written and spoken in very informative and entertaining ways about the placebo effect. His books are and some good talks of his you can find online are
• Hand in BI25 (on an idea from Wednesday's class or readings)
• Hand in Test II revisions, if you like.
• No Quiz or HW homework due today. But keep an eye out for what is due and what will be happening in class on Monday.

#### Week 12

• :
• Some content we discussed, terms defined:
• blind, double-blind
• finalizing discussion of the gold standard for studies involving human subjects: a randomized, [placebo-]controlled trial, [RCT]
• starting experimental ethics — some examples of what not to do:
• the Nazi doctors
• the Tuskegee and Guatemalan Syphilis Experiments
• the Stanford Prison Experiment
• the Milgram "Obedience to Authority" Experiment
• Hand in BI26 (on an idea from Friday's class or readings)
• :
• Some content we discussed, terms defined:
• One checklist of ethical guidelines would be
1. always get informed consent (Caution: this is less obvious than it seems!)
2. do no harm to the test subjects
3. always get independent oversight, which often consists of the IRB and/or the FDA
4. preserve test subjects' confidentiality by default and only break it with their prior permission.
• Hand in BI27 (on an idea from Monday's class or readings)
• :
• Reread LDLoS §5.3 and read LDLoS Introduction to Part 3, LDLoS Introduction to Chapter 6, and §6.1
• Some content we discussed, terms defined:
• the Central Limit Theorem [CLT]
• Hand in BI28 (on an idea from Wednesday's class or readings)
• Hand in HW10: problems 5.{1, 2, 3, 4} starting on this page of LDLoS
• Quiz 7 today [on any new material since Spring Break]

#### Week 13

• :
• Hand in ASE7, which is a special one: read this article and any other sources you find on the same subject which are useful (such as the research report in the Proceedings of the National Academy of Sciences to which there is a link in that first article), and then do as detailed an ASE as you can on this topic, containing all the usual parts. Also include a section in this ASE discussing the ethics of this study. Use the ethical criteria we discussed in class and which are in the readings from last week. As a consequence, this ASE will probably be a fair bit longer than usual.
• Some content we discussed, terms defined:
• general idea of a confidence interval for the mean of a quantitative RV
• Hand in BI29 (on an idea from Friday's class or readings)
• :
• Some content we discussed, terms defined:
• formulæ for confidence intervals for means
• the meaning of the confidence level of a confidence interval
• Hand in BI30 (on an idea from Monday's class or readings)
• :
• Quiz 8 [on material from last Friday to this Wednesday] handed out today, due Monday
• Some content we discussed, terms defined:
• a bit more on the CLT and CIs
• general idea of a hypothesis test for the mean of a quantitative RV
• Hand in HW11: problems 6.{1, 2, 3} starting on this page of LDLoS. Or, if you like, it may be handed in on Monday.
• Hand in BI31 (on an idea from Wednesday's class or readings)

#### Week 14

• :
• No ASE due today. Next week, though, after Test III....
• Quiz 8 due today.
• Hand in HW11 due today, if you didn't hand it in last Friday.
• Some content we discussed, terms defined:
• formulæ for hypothesis tests for means
• the meaning of the $p$-value of a hypothesis test
• Hand in BI32 (on an idea from Friday's class or readings)
• :
• Quiz 9 today [on material from last Friday to this Monday]
• Some content we discussed, terms defined:
• type I error
• caution for hypothesis testing, particularly about interpreting the $p$-value
• Hand in HW12: problems 6.{4, 5, 6} starting on this page of LDLoS
• Hand in BI33 (on an idea from Monday's class or readings)
• :
• Going over lots of recent homeworks, ASEs, and quizzes.
• Hand in BI34 (on an idea from Wednesday's class or readings)
• Review for Test III. See this review sheet.

#### Week 15

• :
• :
• Hand in ASE8. Three options for this one:
1. Find one about a confidence interval for a population mean or average (same thing). It can help to look for the phrase "margin of error," sometimes called "sampling error" in the press. Be careful not to get a source which is about a confidence interval for a percentage (like election data often is, for example), since that is not a CI for a mean (means are not percentages).
2. Find one which is about a hypothesis test, as we have done in this class. Look for "$p$-value", "null/alternative hypothesis," other other such term[s].
3. Otherwise, you can just do a "free-range" ASE: pick a topic that interests you, a nice article or webpage or whatever, which has a clear bit of statistical content, and write up an ASE as we've been doing all semester. [So be sure to clearly talk about the population, variable[s], parameter[s], sample, methods, etc.] If you go this route, please make sure you find a one with rather a lot of interesting statistical content for which you can show off all of your knowledge. Then make sure you do show it off!
• Test III post-mortem.
• :
• Hand in Test III revisions, if you like.
• Review for Final Exam. See this review sheet.
• Hand in BI35, a special one: what do you intend to do for the next few days to enable you to do the best you possibly can on the final exam for this class? Be specific!