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Frivolous & Fun StuffTED talks: Spanish with English subtitles, Eduardo Sáenz
de Cabezón: Math is forever. Roger
Antonsen: Math is the hidden secret to
understanding the world Salman Khan (the Khan Acadamy guy): Let's
use video to reinvent education Youtube videos: Malcolm Gladwell on the
importance of stubbornness (27:37) Rethinking Education – Sal
Khan (1:30:08) CBC Radio, How big data is changing
the video you watch (10:25) Malcolm Gladwell podcast, Revisionist History 
Download[Flatland (the book) can be downloaded from Wikipedia] Download Fathom for Windows from
our Google Classroom (only available to AP Statistics students). Fathom for the Mac is NOT
FREE. Download Mr. Shim’s recommended Graphing Software (free!) Grade 9 Academic EQAO Formula Sheet Geometer Sketchpad 5.06 (download) License name: ONTARIO DSBYORK Authorization
code: KQJ9P1RF7C9CVGP1M7REVX58 
Math Tools & ResourcesDesmos Graphing
Tool (online version) Math Tools (click here) Probability Tools (click here) Vector Visualizer (try this online vector
tool for visualizing) Wheel Decide practice function
spinners: function; a & k coeffcients; p & q
coefficients Wheel Decide practice trig
spinners: a & k coeffcients; p coefficient (radians); q coefficient UWaterloo CEMC Courseware – on line instructional
videos with exercise & enrichment questions (a work in
progress, but an excellent resource for 12U Advanced Functions and 12U Calculus
& Vectors) 
Grade 12 AP Statistics
· Hey, our textbook Stats: Modeling the World, is available online!
· Download the TI83 Plus guidebook PDF from Texas Instruments
· Graphing/Charting and General Data Visualization App
· Normal Distribution calculator, by David Lane
Date 
Topics & Learning Goals 
Resources & Work 
Feb 4 
Ch. 1. Read it. This is going to be fun. Ch. 2 – Categorical vs Quantitative Know that the Who, What, Why,
Where, When and how of the data help us understand the context. Understand the terms data,
case, population, sample, variable, units, categorical variable, and
quantitative variable. Recognize the difference
between categorical and quantitative variables. 
Online survey sent to everyone’s GApps email. Read Chapter 1
Text p.2 – 6…it’s an entertaining read! Text: p.7 – 14 p.16 #3, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25 Optional: YouTuber, Ben Lewis teaches AP Statistics. He is also teaching chapter by chapter using the same textbook. 
5 Lunar New Year 
Ch. 3 – Displaying and Describing Categorical Data Be able to recognize when a
variable is categorical and choose an appropriate display for it (frequency
table, bar chart or pie chart. Understand how to examine the
association between categorical variables by comparing conditional and
marginal percentages on a contingency table. *Understand Simpson’s paradox 
Handout, Ch. 3 Displaying & Describing Categorical Data (Check here for completed notes.) Text p.20 – 37 Acquire and install Fathom software for Windows only. p.38 #5, 7, 9, 11, 15, 19, 21, 25, 27, 29, 31, 33, 39 Optional: Mr. Nystrom, APStatsGuy, contingency tables (13:35) Mr. Nystrom, APStatsGuy, independence vs. association (8:42) 
6 
Ch. 4 – Displaying Quantitative Data Understand how to create
histograms, stem & leaf plots and dot plots. Describe a distribution by it’s shape (modes, symmetrical, gaps
and outliers), center (mean vs median) and spread (range, IQR, standard
deviation). Explore the software Fathom. 
Handout, Ch. 4 Mean and Standard Deviation (Check here for completed notes.) Handout, Ch. 4 Median & Quartiles (Check here for completed notes.) Text p.44 – 71 p.72 #5, 9, 11, 13,
15, 21, 23, 29, 33, 37, 41, 43, 49 (we will redo the
bolded questions tomorrow, using Fathom & the TI84s) CANCELED – Immunization clinic in our classroom. Class today will be in room 2027. 
7 AMC; Report Cards; Grad retake day 
Work Period Let’s have a discussion
about Data Visualization. Ch. 4 using Fathom and TI 
Handout, Fathom Quick
Reference Mandatory: watch the video
of Hans Rosling at TED2006, “The best stats you've ever seen”. (~20 min) Redo using
Fathom, p.72 #13, 15, 33, 37, 41 Optional: Hans Rosling
at TEDIndia2009, “Asia's rise — how and when”. (15:50) Hans Rosling
at TED2010, “Global population growth, box by box”. (10:04) 
8 
Ch. 5 – Comparing Distributions Understand how to create a
boxplot (5 number summary, outliers, percentiles). Compare sets of data using
histograms and boxplots *Transform data to make it
more symmetrical. 
Text p.80 – 93 p.95 #5, 9, 11, 15, 21, 23, 29, 33 (on Fathom), 35, 37, 39 
11 
Ch. 6 – Standard Deviation and ZScores Know how to calculate
zscores. Understand and apply the
properties of a normal distribution. *Construct a Normal
Probability Plot 
Text p.104 – 127 Good examples on p.122 & 123 p.129 #1, 5, 7, 9, 13, 17, 19, 21, 29, 31, 39, 45, 47 
12 
Work Period 
Ch. 3—6 assignment Partners and questions are posted on the Google Classroom. 
13 
Ch. 7 – Scatterplots & Correlation Describe the relationship
between two variables using a scatterplot by discussing direction, form,
strength and the effect of outliers. *Calculate the correlation
coefficient using and using TI
calculator Understand when it is
appropriate to use r. Understand correlation does not
imply causation. Understand the effect of
lurking variables. *Know some ways to straighten
a scatterplot. *Understand differences
between correlation & association. 
Text p.146  162 p.164 #1, 5, 11,
15, 17, 21, 25, 29, 37 Do #33 & 41
using Fathom. 
14 
Work Period 
Immunization clinic in our classroom. Class today will be in room 2027. 
15 
Ch. 8 – Linear Regression (part 1) *Calculate the least squares
line of best fit based on zscores , and based in real units, where and . Be able to interpret the slope
and y intercept of the regression line in context. 
Text p.179 – 192 p.192 #1, 3, 5, 7, 9, 11, 13 
18 
Family Day 

19 
Practice using TI83s 
TI Tips on pages:
15*, 46, 65*, 86, 117*, 119*, 125. Items marked with an * are the most important to know. Quiz Chapters 2  6 
20 
Ch. 8 – Linear Regression (part 2) *Connection between r(the correlation coefficient) and R^{2} (the
variability accounted for, association). *Calculate the residuals, and create a residual plot. *Calculate the standard
deviation of the residuals using . *Interpret the results of the
residual plot and standard deviation of the residuals. 
p.192 #23, 27, 29, 31, 37, 39, 45, 47, 51 (#51 has been entered into Fathom. Check the Google classroom to download.) Box on top of p.183 is important. 
21 
Work Period 

22 
Ch. 9 – NonLinear Regression Understand the following terms: extrapolation, outliers *Leverage – difference between
x and the mean of x. *Residual – difference between
the actual value of y and the predicted value of y. *Influential point – a point
that changes the model significantly Understand the effect of
lurking variables (again). *Regressions based on summary
statistics. 
Text p.201 – 212 Using Fathom
features: ·
Copy As Picture ·
Scatter Plot ·
Line of Best
Fit ·
Show Squares ·
Make a Residual
Plot ·
Using sliders ·
Create a
Nonlinear model Handout, Regression with
Fathom; download the required files here. p.214 #1, 5, 7, 9,
11, 17, 21, 23, 29 
25 
Work period 

26 PCF 
Ch. 10 – Reexpressing Data *Know the 4 Goals of
Reexpression: Make the distribution more
symmetric Make the spread of several
groups more alike Make the form of a scatter
plot more linear Make the scatter plot more
evenly spread out rather than thickening at one end. *Know how to pick a type of
reexpression based on the “Ladder of Powers” *Reexpressing data using the
TI calculator 
Text p.222 – 236 Good example on p.232 for the TI p.239 #1, 3, 5, 7, 9, 15 (use TI), 17 (use TI), 27, 29 
27 
Statistical Analysis Assignment Work period 

28 
Statistical Analysis Assignment Work period 

March 1 
Statistical Analysis Assignment Work period 

4 
Ch. 11 – Understanding Randomness Creating a simulation using
random number generators 
Text p. 256 – 263 p.265 #11, 13, 15,
19, 25, 33, 39 
5 
Work period 

6 
Ch. 12 – Surveys Understand the meaning and
importance of the terms: population,
sample, sampling frame, survey, bias, randomness, sample size, census,
population parameter vs sample statistic Know different kinds of
sampling techniques: Simple Random
Sample, Stratified (strata = homogeneous), Cluster (cluster = heterogeneous),
Multistage, Systematic, Voluntary Response, Convenience Tips on creating a valid
survey Know different kinds of
bias: Response Bias, NonResponse
Bias, Sampling Bias (Undercoverage Bias) 
Text p.268 – 285 (beware of the
creepy guy on p.268) Strange analogy on p.276 involving Boston Cream Pie strange video on response bias p.288 #1, 3, 5, 9,
13, 17, 19, 23, 25, 33 
7 
Review – Chapters 2 – 7 Review – Chapters 8 – 12 

8 
Ch. 13 – Experiments Observational study: retrospective and prospective Experimental study: Subjects are randomly assigned to a
treatment which must have at least one explanatory variable (factor) to
manipulate at least one response variable.
The 4 Principles of
Experimental Design: Control,
Randomize, Replicate, Block Statistically significant,
control treatments, blind experiments, placebo effect, randomized block
design, matching, randomized twofactor experiment, lurking vs confounding 
Text p.292 – p.309 DoubleBlind
Experiment (you tube link) Results of
violin experiment (link to pdf) p.313 #1, 3, 5, 7,
11, 17, 27, 29, 33, 35 
11 – 15 
March Break 

18 
Ch. 14 – Probability Basics Understand
the meanings of: trial, outcome, event,
sample space, empirical vs theoretical vs subjective probability, independent
events *The Law of Large
Numbers Basic
Rules of Probability 1.
2.
The sum of all possible probabilities of an event is 1. 3.
(complement rule) 4.
for mutually
exclusive events. 5.

Text p.324 – 336 Click below to
look at the origins of probability Problem of Points p.338 #1, 7, 11, 19, 21, 23, 29, 33, 35, 41, 43 
19 
Statistics Test (Chapters 2 – 12) 

20 
Ch. 15 – Probability Rules 1.
for any pair of
events. 2.
Conditional Probability:
Also
know tests for independence and how to use tree diagrams 
Text p.342  360 p.361#1, 3, 7,
9, 13, 15, 17, 19, 21, 27, 31, 37, 39, 45 
21 Naw Ruz (Ismaili) 
Ch. 16 – Mean & Variance Be
able to recognize the difference between a discrete random variable and a
continuous random variable. Recognize
that the expected value of a random variable X, is equivalent to the
population mean, µ. *Calculate
the standard deviation of a random variable X using *Apply
the following properties for expectation and variance for two independent
variables X and Y.

Text p.366 –
382 p.383 #1, 3, 5,
9, 11, 13, 19, 21, 25, 27, 33, 35, 37, 43 
22 Interim Report Cards 
Ch. 17 – Probability Models Recognize
the difference between a geometric (models a waiting time) and a binomial
probability model (models # of successes). Understand
the term “Bernoulli Trial”. Geometric: Binomial: , ,
Using
the Normal Model to approximate a Binomial Model. 
Text p.388 –
400 p.401 #1, 9, 11, 15, 17, 19, 21, 23, 27, 31, 35 
25 
Other
probability models: Hypergeometric and Uniform. 
Chapter 7 from
the old MDM4U textbook is called “Probability Distributions”. Check the AP
Stats Team Drive, in a folder called “MDM textbook”. The answers to
homework questions is a separate file called, “Answers”. 7.4 Hyper Geo Dist, p.404 #1, 3, 4, 6, 7, 9 – 12 Ch.7 Review, p.406 #1, 2, 4 
26 

Review
questions: p.405 #1, 3, 7, 9, 15, 17,
23, 31, 35, 41 
27 
OSSLT (school is
open for Grade 10s, but we don’t have class) 

28 Parents Night 
Review for Test 2 

29 
Ch. 18 – Sampling Distribution Models *Central
Limit Theorem – conditions for using CLT Sampling
Distribution Model for a proportion is Sampling
Distribution Model for a Mean is 
p.412 – p.430 In the data
text book, you can find this topic in section 8.6 p.432 #1, 3, 5,
7, 9, 15, 21, 23, 29, 31, 37, 39, 43, 45 
April 1 
Test 2: Chapters 14 – 17
and Hypergeometric, Uniform Distributions 

April 2 
Ch. 19  Confidence Intervals for Proportions Creating &
interpreting CI’s for proportions: Calculating
the margin of error, based on a given CI. Calculating the sample size, n, based on a given CI. 
p.439 – p.453 In the data
text book, you can find this topic in section 8.6 In class, 3sided coins.
Estimate the probability of tossing “sides”. p.455 #1, 5, 7,
9, 13, 17, 23, 27, 29, 31 
3 Euclid 
Work period 

4 
Ch. 20 – Hypothesis Testing for Proportions Understand
the setup, mechanics and conclusion for a hypothesis test *Understand
when and how to do a twosided hypothesis test. 
p.459 – 479 For two tail
tests, see example on p.466 p.476 #3, 5, 9,
13, 17, 19, 21, 25, 29 #13 and #21
require doing a two tail test. 
5 
Constructing Simulations using Excel and Fathom 

8 
Work period 

9 
*Ch. 21 – More about Tests and Intervals Understanding
how to conclude a hypothesis test by either saying “reject H_{0}”, or
“fail to reject H_{0}”. Type I and Type II errors and how to reduce them Understand
what the Power of a Test means 
p.480 – 497 Type I and Type II errors and the
power of a test p.499 #3, 7, 9,
15, 17, 21, 25, 27, 29, 33 
10 FGH 
Work period 
Get to know your calculator (again!)…here are some TI Tips
that you should familiarize yourself with:
p.448, p.469, p.510, p.515 
11 
*Ch. 22 – Comparing Proportions Know the
sampling distribution model for the difference between two proportions (box
on p.507) Know how
to create and interpret a confidence interval for the difference between two
proportions (box on p.508) Know how
to perform a two proportion hypothesis test and interpret the results (box on
p.513) 
p.504 – 518 Hypothesis Testing comparing
Proportions video Confidence Intervals for comparing
proportions p.519 #3, 5, 9,
11, 17, 19, 23, 25, 31 
12 FGH 
Work period 

15 
*Ch. 23 – Inferences about Means Reminder
of the CLT for means For
smaller samples, use the students’s t (Gosset’s t) instead of a zscore. Know how
to create and interpret a confidence interval for a mean (box on p.523) Know how
to perform a hypothesis test a mean and interpret the results (box on p.543) 
p.530  550 Confidence Intervals for Means example of a two tail test for a
mean **You will need to know how to calculate the probabilities based
on t values using your TI83, as the text book does not provide a t table.
(see the TI Tip on p.545) p.554 #1, 3, 5,
7, 9, 11, 19, 21, 25, 29, 31, 37 
16 
Work period 

17 
*Ch. 24 – Comparing Means Know the
sampling distribution model for the difference between two means (box on
p.563) Know how
to create and interpret a confidence interval for the difference between two
means (box on p.564) Know how to
perform a two sample hypothesis test for the difference between two means and
interpret the results (box on p.569) Note that
you do NOT need to know the material on The Pooled tTest starting on page
574. 
p.560  574 **You will need to know how to calculate the degrees of freedom
using the TI83. Check out the TITip
starting at the bottom of page 567. p.579 #1, 5,7,
9, 13, 17, 19, 21, 23, 27, 33, 35 
18 
Work period 

19 
Good Friday 

22 
Easter Monday 

23 
*Ch. 25 – Paired Samples and Blocks (Comparing
Means for groups that have data that are NOT independent) Understand
circumstances that could lead to paired (dependent) data: 1)
Blocked pairs compare data before and
after an experiment 2)
Matched pairs are data from an observational study Understand
the Assumptions and Conditions (p.589) Know how
to create and interpret a confidence interval for the difference between two
means of paired data (box on p.595) Know how
to perform a two sample hypothesis test for the difference between two means
of paired data and interpret the results (box on p.591) 
p.587 – 600 How to create null and alternate
hypotheses review p.602 #1, 3, 5,
9, 11, 13, 17, 19, 23, 25 
24 
Work period 

25 Full Disclosure 
*Ch. 26 – ChiSquared Distribution The
chisquare statistic is .
It is used for the following tests: Chisquared
goodness of fit test (p.622, 623). This is testing to see if a model is
appropriate for the data. Chisquared
test of homogeneity (p.627). This is
like the ztest for two proportions. Chisquared
test for independence(p.633) 
p.618 – 640 Notes: You won’t be able to use your TI for the TI
tip on page 624. This is only for the
TI84s. You can, however, do the
cumulative distribution function on your TI83. p.642 #1, 3, 7,
11, 13, 15, 17, 19, 23, 29, 35 
26 Holy Friday 
Work period 

29 
*Ch. 27 – Inferences for Regression The
idealized line of best fit is denoted .
This corresponds to our fitted line . Assumptions
& Conditions: 1.
Linearity 2.
Independence 3. Equal
Variance 4. Normal
Population Sampling
Distribution for Regression Slopes (bottom of p.658) 
p.649 – 665 Notes: The material after page 665 is all
optional. p.673 #1, 3, 5,
13, 15, 23, 25, 27, 33, 41 
30 
Work period 

May 1 


2 Prom; CEMC marking 


3 CEMC marking 
PA Day 

6 Ramadan begins 


7 
Review for test 

8 
Test – Statistical Inference (chapters 18 – 25) 

9 
Review for AP Exam 

10 
Review (Multiple Choice) 

13 
Review (Full response –
short answer) 

14 
Review (Full response –big answer) 

15 
Review (Full response –big answer) Day 2 

16 
AP Statistics Exam, 12:00 noon 

17 
4.1 Organized Counting Understand the Fundamental Counting
Principle; when to correctly multiply or add (and sometimes subtract). Using “Counting Boxes” with
annotations for proper solutions. 4.2 Factorials and Permutations Understand the basics of combinatorics including factorial and permutation
notation. Learn and practice how to communicate your solution. 
Handout,
4.1 Intro to Organized Counting (Check the completed notes here.) Handout,
4.2 Factorials and Permutations (Check the completed notes here.) §4.1 p.229 # 1–5, 8–10, 13, 14,
17, 18ab §4.2 p.239 #1 – 4, 6, 7, 10, 15,
17, 18 , 11, 13, 14, 19, 22, 16, 12 
20 
Victoria Day 

21 
Work period 
Handout,
Permutations with Restrictions (Check the completed notes here.) §4.1 p.230
#19, 23, 24 §4.2 p.239
#9, 11, 12, 16, 20, 22, 23 
22 
4.3 Permutations with some identical items Understand how to calculate the
number of permutations of n objects
where some of the objects are identical. 
Handout, 4.3 Arrangements with Some Alike (Check the completed notes here.) (If you want, start tomorrow’s homework. Today’s homework is a bit light.) §4.3 p.245 #2–7, 10, 12, 14, 16 
23 
Work period 
Handout, Permutations  Extra Problems 
24 
Dice Assignment 1 

27 
5.1 Venn Diagrams 5.2 Intro to Combinations Understand how to solve problems
using Venn Diagrams. Learn the
principal of inclusion and exclusion.
Recognize the difference between a permutation and a combination. Solve problems involving combinations. 
Handout, 5.1 Counting Using Venn Diagrams (Check the completed notes here.) Handout, 5.2 Introduction to Combinations (Check the completed notes here.) §5.1 p.270 #1–5, 9 §5.2 p.279 #1, 2, 4, 5, 9, 11,
12, 13, 18, 22 
28 
Work period 
Handout, 5.2 Introduction to Combinations Handout, p.4 #1–6 
29 
5.3 Types of Combinations Solve problems with combinations
involving different scenarios: size of
the subset is known / unknown and some items identical. 
Handout, 5.3 Take ‘em or leave ‘em Counting (Check the completed notes here.) §5.3 p.286 #1 – 11, 14, 16, 18,
22, 24 
30 
Work period 
Handout, Combinations & Permutations 
31 
Work period Dice Assignment due 
Combinatorics & probability 
June 3 
Dice Assignment II rolled out 
Handout, Review Combinatorics Activity – Make up a Question Chapters
6.1 – 6.5 
4 
Choose & arrange type questions Work period 
Handout,
Review Probability 
5 EidulFitr 
Work period · Gambling Case Study · Poker · Blackjack · Roulette · Lotteries 

6 


7 Carnival 

Carnival Schedule: ??? (last year’s) Period 1 8:50  9:30 Period 2 9:35  10:05 Period 3 10:10  10:45 Period 4 10:50  11:25 Period 5 11:30  12:05 The Carnival will run from 12:05
 3:30 
10 


11 
Test 4 – Combinatorics & Probability 

12 
Dice Assignment II due 

13 


14 
Review for Exam 
Final exam review Read the sample Final Exam cover page. Download and check the corrections
for the MDM textbook. 
17 
Review for Exam 

18 
Detailed
Exam Review 2.1 Graphs – be able to
draw and interpret graphs 2.3 Sampling Techniques
(note the vocabulary and the typical examples for different sampling
techniques) 2.4 Bias 2.5
Measures of Central Tendencies (mean
& median) 2.6
Measures of Spread (standard dev & quartiles) 3.1
scatter plots 3.2
linear regression 3.3
NonLinear Regression (it is not reasonable to DO nonlinear regression
without a computer, but you should know how to discuss, interpret and explain
nonlinear regression.) 3.4
Cause & Effect (5 Types of Cause & Effect) 3.5
Critical Analysis (be able to interpret statistics) 4.1—4.3
Permutations 5.1—5.3
Combinations 6.1—6.5
Probability 7.1
Probability Distributions 7.2
Binomial Distributions (same as AP Stats) 7.3
Geometric Distributions (same as AP Stats; different format) 7.4
Hypergeometric Distributions (In AP Stats we always
approx. using a normal dist. In Data Mgt the
numbers are small and simple enough that we calculate and graph the actual
distribution.) 8.1
Continuous Distributions (introduces “area under the curve =1” distributions,
particularly Uniform.) 8.2—8.4
Normal Distributions (same as AP Stats BUT we only use the table on P606) 8.5
Hypothesis Tests (only 1tail normal tests) 8.6 Confidence Intervals 

19 
Exams 

20 
Exams 

21 
Exams 

24 
Exams 

25 
Exams 

26 
Exam
Feedback Day 
8:50 – 9:20 Period 1 9:25 – 9:55 Period 2 10:00 – 10:30 Period 3 10:35 – 11:05 Period 4 11:10 – 11:40 Period 5 11:45  12:25 Lunch 
27 Grad 
PA Day 

28 
PA Day 

Mon July 1^{st} 
Canada Day 
