Colorado State University — Pueblo, Fall 2016
Math 156, Introduction to Statistics, Section 1
[In Physical Space]
Course Schedule & Homework Assignments
Here is a link to the page of common
comments on graded 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 text Introduction to Statistics, hosted by
Saylor Academy, as SIS. The book was
originally written by Douglas S. Shafer and Zhiyi Zhang, both of the University
of North Carolina, and is released under a
Creative Commons
AttributionNonCommercialShareAlike 3.0 Unported
(CC BYNCSA 3.0 license.
Here
is an online version of this book, while here is a PDF of the full book
(and here is a local copy) and
here is a DOCx, either of which can be downloaded and saved, printed, or
searched.
If you see the symbol
below, it means that class was videoed and you can get a link by emailing 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.
When there is a reading assignment, please read the named section(s) before
that day.
Homework for a particular day is due that day, either in class or
handed in at my office by 3pm.
Week 1
 :
 A lot of bureaucracy and introductions.
 Read the course syllabus and policy page.
 HW0 Send me email (at
jonathan@poritz.net)
telling me:
 Your name.
 Your email address. (Please give me one that you actually check
fairly frequently, since I may use it to contact you during the
term.)
 Your year/program/major at CSUP.
 What you intend to do after CSUP, in so far as you have an idea.
 Past math classes you've had.
 The reason you are taking this course.
 Your favorite mathematical subject.
 Your favorite mathematical
result/theorem/technique/example/problem.
 Anything else you think I should know (disabilities, employment
or other things that take a lot of time, etc.).
 [Optional:] The name of a good book you have read
recently.
Please do this some time Monday. But as some direct incentive: I will
only enter your name into my gradebook and give you your Homework
Late Passes when I get this email, so you really need to
do this assignment as soon as possible. [By the way, just to be fair,
in case you are interested, here is a
version of such a selfintroductory email with information as I would
fill it out for myself.]
 Some content we discussed, terms defined:
 individuals, population, sample
 variables, measurements
 categorical [also called qualitative] and
quantitative
 some big picture discussion of what the whole subject of
statistics is about
 :
 Read SIS §1.1, SIS §1.2, SIS §1.3, SIS §2.1
 Some content we discussed, terms defined:
 parameter vs statistic
 data list and data frequency table
 graphs for categorical variables:
 graphs for a quantitative variables:
 a stemandleaf plot
 the main such graph: a histogram
 variants: frequency and relative frequency
 shape
 classes [or bins]
 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.
 :
 Read SIS §2.2
 Discussion of ASEs (see more below, next Monday). First is due soon!
 Some content we discussed, terms defined:
 the notation $\sum x$, or $\sum_{i=1}^n x_i$
 measure of central location [of some quantitative data]:
 [sample] mode
 sample mean $\overline{x}$ and population mean
$\mu$
 Quiz 1 today
 Hand in HW1: SIS §1.1: 16, SIS §1.3: 4, SIS §2.1: 4, 8, 14 [in 14, add: What kind of graphical representation(s) of this data can you make? Sketch it (them)!]
 Hand in BI2 (on an idea from Wednesday's class or readings)
 Today [Friday] is the last day to add classes.
Week 2
 :
 Reread SIS §2.2
 Hand in BI3 (on an idea from Friday's class or readings)
 Hand in ASE1: This first ASE is
quite simple and will likely be fairly short (1/2 a page?). Find
on a website, in a newspaper or magazine, or in a book (maybe a
textbook from another class) a passage (or graph) which uses one or
more of the terms we have worked with so far in this class (the
terms in bold above). What you are to hand in should have
the following parts:
 A statement of the source of your passage. This does
not have to be in any particular bibliographic format, but it
should have enough information so that I could find the passage
myself either in a library or on the Internet.
 Quote the passage or copy the graph. You might
want to cutandpaste into a word processor page, or print out or
copy the item and attach it to the rest of your ASE.
 Have an explanation of the quote or graph: identify what
are the variables, what type they are (categorical or quantitative),
methods (kind of graph; mean or skew or whatever) used.
 Give a critique of the method:
 Is an appropriate method being used (e.g., pie charts
only work for categorical variables where the total is 100% of
the data, etc.)?
 Are good rules used in display (correct terminology used,
graphs fully labelled, high enough resolution to show what is
interesting, etc.)?
 Do you have any concerns about the reliability of the data
— is there an explanation of where it came from, is it
reasonable to assume that it is accurate?
 etc.
Here is an example of the kind of thing we
are looking for. (The "critique" in this example is very friendly and
positive — which is actually unsurprising, since the source is a
famously careful and impartial research organization — while
yours may not be as positive (e.g., sometimes it is fun to find
a published statistic which is full of errors!).
 Some content we discussed, terms defined:
 examples of means, e.g., computing from data frequency
tables
 means are very sensitive to outliers [not a phrase used in
the book, but very important nonetheless]
 [sample] median $\widetilde{x}$
 shape of a histogram: symmetric, and
skewed right or left
 :
 Read SIS §2.3
 Some content we discussed, terms defined:
 the range, which is very sensitive to outliers
 the sample variance $s^2$ and
sample standard deviation $s$, unfortunately still very
sensitive to outliers
 the population variance $\sigma^2$ and
population standard deviation $\sigma$, unfortunately still
very sensitive to outliers
 how to compute variances and standard deviations with electronic
tools
 discussion of importance of variability in data; what it means
for the variance (standard deviation) to be 0.
 Many web pages describe how to use your favorite calculator to do
statistical computations. If you have a TI84, for example,
this
is a good reference for variance, standard deviation, and IQR. If you
have another calculator, just use your favorite search engine to look
for "compute standard deviation on a calculator name." You can
also find many smartphone apps, some probably free, on your favorite
app store. And finally, if you search for "online standard deviation
calculator," you will find many web pages which will do these kinds of
computations for you on whatever Internetconnected device you have.
 Hand in BI4 on something from Monday's class or something new
from the reading SIS §2.2
 :
 Read SIS §2.4
 Some content we discussed, terms defined:
 percentiles
 quartiles $Q_1, Q_2, Q_3$
 the fivenumber summary
 a boxplot (also called boxandwhisker plot)
 the interquartile range [IQR] — which is a measure of
the variability of a dataset which is
insensitive to outliers!
 This page (which we have seen before) explains how to compute IQRs on a
TI84, if that's your calculator. If you have a different
calculator, just use your favorite search engine to look for
"compute IQR on a calculator name" or "compute quartiles on a
calculator name." You can also find many smartphone apps,
some probably free, on your favorite app store. And finally, if you
search for "online IQR calculator" or "online quartile calculator"
you will find many web pages which will do these kinds of
computations for you on whatever Internetconnected device you have.
 Hand in HW2: SIS §2.2:
10,12, 16, 26, SIS §2.3: 12, 16, 18
 Hand in BI5 (on an idea from Wednesday's class or readings)
 Quiz 2 today
Week 3
 :
 Yes, we do have class today, even though it is the federal
holiday celebrating the achievements of workers and the labor movement
— if you like the 40 hour work week, now is the time to give
thanks.
 Reread SIS §2.4 and this [the first 14 pages, in particular] as well
 Some content we discussed, terms defined:
 the $z$score of a data value
 the $1.5\times{}IQR$ rule for outliers
 Hand in ASE2: Your second ASE should
be something about what we've been covering since the first one,
probably to do with means, medians, standard deviations, maybe a
scientific paper with sidebyside boxplots, etc.
It should have the same parts as the first ASE, as described above,
including
 Source
 Quote/copy
 Explanation: identify the variables, what type they are,
methods
 Critique
Here is another example ASE.
If you are looking for a good source of possible statistics in the
wild to analyze on an ASE, you could try:
 any material used in one of your other classes
 any online version of a newspaper, such as
 a specifically datadriven organization, such as one of the
following [descriptions below, when in quotation marks and
italics are taken from the respective site's
selfdescription]

FiveThirtyEight
[FiveThirtyEight is an online journalism site which applies
careful research and thoughtful statistical modeling to
current stories in politics, economics, science, "life", and
sports. It was founded by Nate Silver, who has done
statistical analysis for sports betting and also predicted
statebystate the outcomes in the last several presidential
elections with incredible accuracy.]

The Pew Research
Center ["Pew Research Center is a nonpartisan fact
tank that informs the public about the issues, attitudes and
trends shaping America and the world. It conducts public
opinion polling, demographic research, media content analysis
and other empirical social science research. Pew Research
does not take policy positions."]

The Gapminder
Foundation ["Gapminder is a nonprofit venture –
a modern 'museum' on the Internet – promoting
sustainable global development and achievement of the United
Nations Millennium Development Goals."]

the Gallup polling
organization ["Gallup delivers forwardthinking
research, analytics, and advice to help leaders solve their
most pressing problems. Combining more than 75 years of
experience with its global reach, Gallup knows more about the
attitudes and behaviors of the world's constituents,
employees, and customers than any other organization."]
 Hand in BI6 (on an idea from Friday's class or readings)
 Today [Monday] is the last day to drop classes without a grade
being recorded.
 :
 Read SIS §2.5 and start
SIS §3.1
 Some content we discussed, terms defined:
 the empirical rule — also known as the
689599.7 rule
 the idea of randomness
 sample spaces, outcomes, events
 Hand in BI7 (on an idea from Monday's class or readings)
 :
 Continue reading SIS §3.1
 Some content we discussed, terms defined:
 the idea of probability
 fair coins and dice
 Hand in BI8 (on an idea from Wednesday's class or readings)
 Hand in HW3: SIS §2.4: 12, 14, 26, 32, and a supplemental problem which we will call 2.4.S1 which is Are there any outliers in the data for problem 32?, and SIS §2.5: 8, 24
 Quiz 3 today [on quartiles, the fivenumber summary, boxplots,
the IQR, zscores, the 1.5IQR rule for outliers, and the empirical
rule — also known as the 689599.7 rule]
Week 4
 :
 Read SIS §3.2
 Some content we discussed, terms defined:
 complement of a subset [event], notation $E^c$,
translation into English: not
 Venn diagrams
 probability rule for complements
 intersection of sets [events], notation $A\cap B$,
translation into English: and
 union of sets [events], notation $A\cup B$,
translation into English: or
 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, and/or
outliers.
 :
 Reread SIS §3.2 and read
SIS §3.3
 Some content we discussed, terms defined:
 mutually exclusive events, notation $\emptyset$ for the
empty set
 the book's Probability Rule for Mutually Exclusive
Events is somewhat inaccurate: while it is true that
if events $A$ and $B$ are mutually exclusive, then $P(A\cap
B)=0$, it is not true that if $P(A\cap B)=0$ then $A$ and
$B$ are necessarily mutually exclusive.
 additive rule of probability
 the conditional probability $P(A\mid B)$ of event $A$
given event $B$
 Hand in BI10 (on an idea from Monday's class or readings)
 :
 Reread SIS §3.3 and read
SIS §4.1
 Some content we discussed, terms defined:
 independent and dependent events
 random variables [RVs]
 discrete and continuous RVs
 Hand in BI11 (on an idea from Wednesday's class or readings)
 Quiz 4 today [on probability computations, including Venn
diagrams, intersections, unions, complements, and conditional
probabilities]
 Hand in HW4:
SIS §3.1: 2, 6, 16,
SIS §3.2: 4, 8, 16,
and SIS §3.3: 6, 10
Week 5
 :
 Read SIS §4.2
 Some content we discussed, terms defined:
 the [probability] distribution of a discrete RV
 mean or expectation of an RV
 Hand in BI12 (on an idea from Friday's class or readings)
 Hand in ASE4. Please try to find something which mentions
probability, maybe even conditional probability, and/or
independence [for events], if possible.
 :
 Read SIS §5.1 and SIS §5.2
 Some content we discussed, terms defined:
 the [probability] distribution of a continuous RV
 how to computer probabilities from the distribution of a
continuous RV
 the Normal Distribution with mean $\mu$ and standard
devision $\sigma$
 the standard Normal RV
 tools [tables] to compute probabilities on the standard Normal
distribution
 Hand in BI13 (on an idea from Monday's class or readings)
 :
 Read SIS §5.3
 Some content we discussed, terms defined:
 computing probabilities for general [nonstandard] Normal RVs,
algebraically and then with a standard Normal table or tool
 computing probabilities for general [nonstandard] Normal RVs,
directly with calculators and computers
 Hand in BI14 (on an idea from Wednesday's class or readings)
 Quiz 5 today [on independence, RVs, distribution of RVs, Normal
distributions and probabilities]
 Hand in HW5: SIS §3.3: 2, 4, 8, SIS §4.1: 4, SIS §4.2: 2, 10, 12 a&b, SIS §5.1: 4, and SIS §5.2: 2 a, b, d, & e
Week 6
 :
 Read SIS §5.4
 Some content we discussed, terms defined:
 areas of tails of the standard Normal distribution
 finding cutoffs for tails of the standard Normal distribution
with specified areas
 the above for nonstandard Normal distributions
 Hand in BI15 (on an idea from Friday's class or readings)
 Hand in ASE5. It would be nice to find something which uses
one of our recent terms, such as normally distributed, or
expectation [in probability].
 :
 :
 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!
Week 7
 :
 There was a delay with grading midterm I  sorry! As a consequence,
it's best to start new material today and come back to the midterm on
Wednesday. So:
 Skim the following background, examples of ethically questionable
experiments:
 Nazi doctors experimented on human subjects during the Holocaust.
It is very hard to read about this horror. But — despite the
denials of some deranged quacks even today — it really did
happen, and We Must Never Forget, as is said. If you want
to look into this, search a bit on the Internet, or read a few
articles in Wikipedia on the subject.
 The Tuskegee syphilis experiment, particularly the background sections on
History,
Study termination, and
Aftermath, as well as the section
Ethical implications, important for our class
 Philip Zimbardo's Stanford Prison Experiment, particular the sections on
Goals and methods and
Ethical issues
 Stanley Milgram's experiment on obedience to authority figures, particularly the
sections The experiment and Ethics
 Some content we discussed, terms defined: Ethical experimental
design is now a major subject of study. Major organizations have made
statements of principles in this area, for which you might look
at this Wikipedia page or other articles to which it refers. In this
large, nuanced field, we will take as basic at least the following
four required components of ethical experimentation on human
subjects:
 Informed Consent: Note that true informed consent is more
difficult than it might seem at first. In particular, economic or
other constraints on potential experimental subjects might make it
very hard for them to refuse. Also, being truly informed does mean
that subjects are aware of all possible consequences and outcomes,
good and bad, of the experimentation.
 "Do No Harm": This, also, can be tricky. Some
inconvenience to a subject might be considered small harm contrasted
with a potentially large benefit from running the experiment through
to its conclusion. But the principle insists that we confront this
issue and always err, to the extent we can, on conservative views of
what might harm the experimental subjects. This principle is
related, therefore, to the Hippocratic Oath taken by physicians, which contains the
requirement First do no harm.
Note also that paying attention to this issue sometimes requires
that an experiment be interrupted early, if preliminary data show
that one treatment or another in the experiment is doing harm to
some of the subjects.
 Anonymity/Confidentiality: This again is based on respect for
the autonomy of experimental subjects, that they should be able to
control the release of information about themselves. The default,
therefore, is that subjects' identities must be kept confidential
when the experimental results are announced. The easiest way to do
this, although often not the way it is actually done, is for the
subjects actually to remain anonymous during the entire experiment.
 Institutional Review Board [IRB] (or FDA)
oversight: The IRB is an external board which checks that the
principles of ethical experimental design are being followed in
each case. The IRB must be approached, in advance, regarding
any experimentation that has human subjects, for approval when the
organization (university, company, research lab, etc.) gets
any US Federal support. Failure to do so can result in all future
such funding being cut to that organization. See this Wikipedia article.
In the US, the Food and Drug Administration (FDA) has oversight of
medical products and drugs, some of which includes detailed control
of the clinical experiments done to validate them.
:
 Test I postmortem.
 Hand in BI17 on basics of experimental ethics.
:
 Skim The Belmont Report (or even this Wikipedia summary), a famous and important report
giving Ethical Principles and Guidelines for the Protection of Human
Subjects of Research, as its subtitle says.
 Hand in BI18. 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.
 Quiz 6 today [on experimental ethics]
Week 8
 :
 Yes, we do have class today, even though it is the federal
holiday celebrating the arrival of Christopher Columbus in the New
World. (Not so clear why we celebrate him: his idea of how big the
world is was wildly off the mark (unlike the quite accurate estimate
produced by Eratosthenes in the 3^{rd} century BCE); he never
actually made it to the North American continent; he brought back from
his very first trip some of the indigenous people he met as slaves;
etc., etc.)
 Read this page which discusses some
basics of experimental design.
 Some content we discussed, terms defined:
 observational studies vs experiments
 bias
 control groups
 randomization [to prevent bias]
 The Placebo Effect
 blinding and particularly doubleblind experiments
 RCTs
 Hand in BI19 (on an idea from Friday's class or readings)
 Hand in ASE6, 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.
 :
 Read SIS §6.1 and
this page.
 Some content we discussed, terms defined:
 the sampling distribution of a statistic
 the probability distribution of the sample mean, particularly
its mean and standard deviation
 simple random samples [SRSs]
 Hand in BI20 (on an idea from Monday's class or readings)
 :
 Read SIS §6.2 and
this page.
 Some content we discussed, terms defined:
 The Central Limit Theorem [CLT]
 volunteer sample bias
 block designs for experiments
 Quiz 7 today [on experimental design, basics of the sampling
distribution of the mean, and SRSs]
 Hand in BI21 (on an idea from Wednesday's class or readings)
 Hand in HW7:
 Suppose I am curious if people learn as well when they read
books on a screen (such as a phone, computer, or ereader) as
they do when they read the same book on paper. Describe in a
sentence or two (or three...) an observational study I
might do on this topic, and then, separately,
an experiment.
 For the observational study, think of a lurking variable which
might be confounded with the variable of the study you proposed.
 People who eat lots of fresh fruits and veg have lower rates of
colon cancer than people who don't eat those things. One ideas is
that certain vitamins in these foods have a preventative effect
for cancer. To test this, a researcher got 1000 people who were
at risk of colon cancer and divided them into a group which got a
vitamin supplement every day and another group which got a placebo.
The experiment was performed doubleblind.
After four years of this study, it was found that there was
almost no difference in colon cancer rates.
 Was that an observational study or an experiment?
 Explain very concretely how the experiment was (should have
been) done: groups chosen, pills given, results processed,
etc.
 The experimental result in the previous problem was surprising
because it is really a fact that people who eat the fruit and veg
which have those vitamins do have lower rates of colon cancer.
Suggest some lurking variables which might explain this observation.
Since the experiment found no difference in colon cancer rates,
one of the lurking variables you suggest might be the real cause
of the beneficial effect of eating fruits and veg, rather than
just the vitamins, as our disappointed experimenter above was
hoping.
 SIS §6.1 problem 4
Week 9
 :
 Read SIS §7.1 and the first
part of this page.
 Some content we discussed, terms defined:
 the idea of a confidence interval, particularly the meaning
of its confidence level [very important!]
 the largesample confidence for the population mean
 the margin of error of a confidence interval
 the critical values used in the formulæ for
confidence intervals
 Hand in BI22 (on an idea from Friday's class or readings)
 Hand in ASE7. See if you can find a source which describes
its experimental design, mentioning a few of the terms we have used
in our discussions of this topic. Then do a usual ASE which talks
about individuals, populations, variables, methods, etc., and
then also includes a critique of the stated experimental design.
 :
 Read SIS §7.2 and the rest
of this page.
 Some content we discussed, terms defined:
 the smallsample confidence for the population mean
 Student's $t$distribution
 Hand in BI23 (on an idea from Monday's class or readings)
 :
 Read SIS §7.3 and
this page.
 Some content we discussed, terms defined:
 the largesample confidence interval for the population
proportion
 Hand in BI24 (on an idea from Wednesday's class or readings)
 Quiz 8 today [on confidence intervals for the population mean]
 Hand in HW8: SIS §6.2: 2, 10; SIS §7.1: 2, 8; SIS §7.2 6, 8
 Today [Friday] is the last day to withdraw (with a W) from
classes.
Week 10
 :
 Read SIS §7.4
 Some content we discussed, terms defined:
 the sample size needed for a particular margin of error in
a CI for a population mean
 the sample size needed for a particular margin of error in
a CI for a population proportion
 the most conservative estimate (of that sample size
for proportions)
 Hand in BI25 (on an idea from Friday's class or readings)
 Hand in ASE8. Try to 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." 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).
 :
 Read SIS §8.1 but skip
the sections called The Rejection Region and Standardizing
the Test Statistic; in the section Two Types of Errors,
only read the definition of the two types, skip the "level of
significance of the test"
 Some content we discussed, terms defined:
 the null hypothesis $H_0$ and alternative $H_a$ of
a test of hypotheses ... also called a test of
significance and hypothesis test
 our null hypotheses $H_0$ are (always!) of the form
$H_0$: parameter = value
 our alternative hypotheses $H_a$ can have the form
 $H_a$: parameter ≠ value, called a
twotailed test; or
 either
 $H_a$: parameter < value or
 $H_a$: parameter > value
both called onetailed tests
 conclusions we make: "reject $H_0$" or
"fail to reject $H_0$"
 what could go wrong? there are two types of errors we could
make:
 a Type I error, when we reject the $H_0$ even though it
is true, and
 a Type II error, when we fail to reject the $H_0$ even
though it is false
 Hand in BI26 (on an idea from Monday's class or readings)
 :
 Read SIS §8.2 looking
mostly for the definition of the test statistic and the examples; read
this page for details of how we will do
the tests in this class.
 Some content we discussed, terms defined:
 test statistic or $z$statistic
 $p$value of a test [this is very important, and
you will be expected to understand and to be able to explain
this concept]
 significance level
 Hand in BI27 (on an idea from Wednesday's class or readings)
 Quiz 9 today [on confidence intervals for the population
proportion, finding the sample size needed for a given margin of error,
and/or some basic ideas/terms from hypothesis testing]
 Hand in HW9: SIS §7.3: 6, 20 [hint: "point estimate" here is another way of saying "sample
proportion"]; SIS §7.4: 2, 4, 16;
SIS §8.1: 2.
Week 11
 :
 Read, if you like, SIS §8.3
— that is the book's description of the material we've already
seen on this page. New material to read
for today is SIS §8.4, or
this page for our version of this.
 Some content we discussed, terms defined:
 Always start a hypothesis test by stating the population, RV,
parameter of interest, and null and alternative hypotheses
$H_0$ and $H_a$
 formulæ for the test statistic in a hypothesis for a
population mean $\mu$ in the case of
 known population standard deviation $\sigma$: the
test statistic is a $z$statistic, with formula
$z=\frac{\overline{X}\mu_0}{\sigma/\sqrt{n}}$; you
compute the $p$value with the standard Normal table (based
upon what kind of alternative hypothesis you have); this whole
test is then called a "$Z$Test".
 unknown population standard deviation: the
test statistic is a $t$statistic, with formula
$t=\frac{\overline{X}\mu_0}{s/\sqrt{n}}$, where $s$ is the
sample standard deviation; you compute the $p$value with the
appropriate part of a table of Student's $t$Distribution
depending upon the degrees of freedom $df=n1$ and in the
direction determined by the kind of alternative hypothesis
you have); this whole test is then called a "$T$Test".
 Hand in BI28 (on an idea from Friday's class or readings)
 Hand in ASE9. Try to find one about a confidence interval for
a population proportion  there should be tons of these in coverage of
the presidential election. It can help to look (again) for the phrase
"margin of error." Be careful not to get a source which is
about a confidence interval for a population mean; proportions will
often be expressed as percentages, remember.
 :
 Read SIS §8.5 or
our version of this material
 Some content we discussed, terms defined:
 the test statistic for a hypothesis test of the population
proportion: $z=\frac{\widehat{p}p_0}{\sqrt{p_0(1p_0)/n}}$
 the process for a hypothesis tests for the population proportion,
which is just like the $Z$Test using this new version of the
$z$statistic
 Hand in BI29 (on an idea from Monday's class or readings)
 :
 Review for Test II. See this review sheet.
 Hand in BI30 (on an idea from Wednesday's class or readings)
 Quiz 10 today [on confidence intervals for the population mean
with known and/or unknown population standard deviation and/or for the
population proportion; particular attention on the logic and structure
of hypothesis test and the meanings of $p$values]
 Hand in HW10: In these problems, always use the
$p$value approach of the descriptions in the web pages for our
class: one,
two,
three, and
four. Problems to do are
SIS §8.2: 8, 14;
SIS §8.4: 12, 18; and
SIS §8.5: 12, 14.
Week 12
 :
 :
 :
 Yes, we do have class today, even though it is the federal
holiday honoring veterans of the United State Armed Forces.
 Read SIS §10.1 and SIS §10.2
 Some content we discussed, terms defined:
 independent and dependent variables
 scatterplots
 shape, strength, and direction of a
relationship visible in a scatterplot
 [linear] correlation coefficient, some properties
 Hand in BI31. This is another special one: think about the
previous special BI18. Did the same thing happen? Did you
manage to make the change you contemplated? Did it have the desired
effect? What do you think you could do next time?
 Hand in Test II revisions, if you like.
Week 13
 :
 Skim SIS §10.3 and read
SIS §10.4
 Some content we discussed, terms defined:
 review of equations of lines:
 slope
 $y$intercept
 equation: $y=mx+b$
 the idea of the least squares regression line [LSRL]
 how to compute the LSRL
 electronic tools to compute correlation coefficients and LSRLs:
 Hand in BI32 (on an idea from Friday's class or readings)
 Hand in ASE10: this is a "freerange" 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 want
to do one which has a scatterplot and/or mentions correlation, that
would be great [but is not required, since we've just started talking
about this material].
 :
 Reread SIS §10.4 and read
this page
 Some content we discussed, terms defined:
 using the LSRL to guess missing values of a linear relationship
[interpolation]
 potential issues with the LSRL:
 correlation is not causation — but it sure is a
hint
 sensitivity to outliers — but what are outliers on
scatterplots?
 extrapolation — but sometimes it's the best you
can do
 the meaning of $r^2$, the square of the correlation coefficient
 time permitting, discussion of using LSRLs when the relationship
is not linear
 Hand in BI33 (on an idea from Monday's class or readings)
 Hand in HW11: SIS §10.1: 4, 8, 12;
SIS §10.2: 6, 12; and
SIS §10.4: 4, 12.
 :
 Really, read this page, it has lots of useful
information about the content of this unit of the course.
 Some content we discussed, terms defined:
 continuing with topics started on Wednesday, and on
this page.
 Hand in BI34 (on an idea from Wednesday's class or readings)
 No quiz today because this material [on scatterplots, the
correlation coefficient, and least squares regression lines] will be
tested in the [fairly short] midterm following our Thanksgiving Break.
Week 14
 Thanksgiving Break! No classes, of course.
Week 15
 :
 :
 Test III 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!
 Today is the last day to hand in any late work for credit, even
with Homework Late Passes.
Please also hand in any unused Homework Late Passes you have left,
for course extra credit.
 :
 Test III postmortem will be sent by email! If you do not get an
email with links to videos explaining how to do the Test III problems,
inquire further (by email) about it. But there will be
no inperson class.
 Make sure you drop by GCB314 at some point to pick up any graded work
for which you may be waiting.
 Review for final exam by looking over
this review sheet and watching
this video.
 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!
Week 16