
Statistics (Honors) 



Date* 
Objectives 

Lectures 
Standard(s)

8/19

Orientation




8/20

PreTest




8/21

11/12 Students will learn about a large group
by examining data from some of its members.


12 Statistical Thinking
HW: See
last panel of lecture


8/22

See Above




8/25



Odd problems on pg 10


8/26



Odd problems on pg 15


8/27

Students will learn about using sample data to
make inferences (or generalizations) about an entire population.


13 Types of Data
HW: See last
panel of lecture


8/28

Students will learn to vThink carefully about
the context, source, method, conclusions and practical implications.


14 Critical Thinking
HW: See
last panel of lecture 

8/29

See Above.




9/1

Labor Day




9/2

Students will learn about the basics of
collecting data .


15 Collecting Sample Data
HW: See last panel of
lecture


9/3

Review




9/4

Unit Exam


Practice Exam


9/5

Students will learn to identify the different
aspects of a frequency distribution.


22 Frequency Distributions


9/8

Students will
learn to create a histogram.


23 Histograms

MAFS.K12.MP.5.1

9/9

Students will learn the basics of using
Excel.


Beginning Excel 1


9/10

Students will learn the basics of using
Excel.


Beginning Excel 2


9/11

Students will learn to graph with Excel


Graphing with Excel


9/12

Excel Continued




9/15

Project
Students will create 3 Histograms and 3 Relative
Frequency Histograms with Excel (or other
spreadsheet) based on the teacher data in the
'Histogram" tab of the 'Histogram Data File'. The
Histograms are to be labled and printed
individually. Students will submit 2 hard copies of
the spreadsheet (one showing values and the other
showing formulas). Students will also write a
paragraph discussing results and analysis of results
with possible causes or implications. A cover sheet
with name, date, class, class period and title is to
be stapled on top. (Total of 10 pages required.)


Histogram Data File
How to create a Histogram on a Mac (Most
steps will work for a PC)

MAFS.K12.MP.5.1

9/16

See Above




9/17

See Above.


.


9/18

Students will learn to identify and create
scatter plots, line graphs, bar graphs, pareto charts, and pie charts.


24 Statistical Graphs
HW: See last
panel of lecture

MAFS.K12.MP.6.1

9/19

Project
Students will begin obtaining raw data based on criteria from the
instructor. Data is to be entered into a spreadsheet and emailed to
the instructor by Sunday. Teams failing to do so will have a 30 point
deduction to their project.



MAFS.K12.MP.6.1

9/22

Project
Students will create a Bar Chart, Pie Chart, Scatter Graph, and Histogram based
on the previous day's results. Students will submit 2 hard copies of
the spreadsheet (one showing values and the other showing formulas).
The 3 graphs are to printed Individually. A cover sheet with name,
date, class, class period and title is to be stapled on top. (Total of
7 pages required).


Cumulative Restults Spreadsheet

MAFS.K12.MP.6.1

9/23

Review


Ch2 Exam Review


9/24

Unit Exam




9/25

Students will learn to define and calculate mesures
of center.


32 Measures of Center
HW: See last
panel of lecture


9/26

Numb3rs (Weighted Mean Episode)




9/29

Students will learn to define and calculate
measures of variation


33 Measures of Variation
HW: See last
panel of lecture


9/30

Project
Students will begin obtaining raw data based on criteria from the
instructor. Data is to be entered into a spreadsheet and emailed to
instructor no later than 8:00 PM EST. Teams failing to do so will have a
30 point deduction to their project.
Spreadsheet is to be downloaded for use the following
day. See Measures and Variation link below.




10/1

Project
Students will create a Scatter
Plot based
on the previous day's results as well as a Pie Chart illustrating how
much each group contributed (%). Students will also calculate Mean,
Median, Mode, Range, Standard Deviation
(population and sample), Variance (population and
sample), Minimum Value, Maximum Value, and Range using appropriate Spreadsheet functions. Students will submit 2 hard copies of
the spreadsheet (one showing values and the other showing formulas).
The graph is to printed Individually. A cover sheet with name,
date, class, class period, and title is to be stapled on top. (Total of
4 pages required).


Measures and Variation Data


10/2

See Above




10/3

Inservice
Day  Student Holiday




10/6

Students will learn about Measures of Relative
Standing and Boxplots.


34 Measures of Relative Standing and Boxplots
HW: See last
panel of lecture


10/7

Review


Ch 3 Exam Review


10/8

Unit Exam




10/9

Students will learn to determine and calculate empirical probability
and see how it is affected by the Law of Large Numbers.


P1 Nature of Probability
HW: Worksheet


10/10

Enrichment: Numb3rs Episode 215




10/13

Students will learn to calculate theoretical probability given a
finite set of circustances with specific outcomes.


P2 Theoretical Probability
HW: Worksheet


10/14

Enrichment: Numb3rs Episode 318




10/15

PSAT Testing




10/16

Students will learn to determine odds based of specific events.


P3 Odds
HW: Worksheet


10/17

SIA #1




10/20

Enrichment: Numb3rs Episode 306




10/21

Students will learn to use probability to determine expected value of
a given event.


P4 Expected Value
HW: Worksheet


10/22

Students will learn to use tree diagrams and the counting principle to
predict the probability of a given event
End of 1st 9Weeks


P5 Tree Diagrams
HW: Worksheet


10/23

Enrichment: Numb3rs Episode 205




10/24

Students will learn to determine probability given AND and OR
statements.


P6 OR & AND Problems
HW: Worksheet


10/27

Students will learn to use determine probability of events given
specific conditions.


P7 Conditional Probability
HW: Worksheet


10/28

Enrichment: Numb3rs Episode 202




10/29

Students will learn to use the counting principle to determine
probability of a given event and use permutations to determine the
number of outcomes possible.


P8 Counting Principle
HW: Worksheet


10/30

Enrichment: Numb3rs Episode 211




10/31

Enrichment




11/3

M&M Project
Follow ALL directions on the
worksheet


M&M Project


11/4

Students will learn to determine probability of
multiple events using the counting method.


P9 Combinations
HW: Worksheet


11/5

Students will learn to apply Pascal's Triangle and
the Binomial Theorem to determine probability.


P10 Binomial Probability
HW: Worksheet


11/6

Enrichment: Numb3rs Episode 321




11/7

Review




11/10

Probability Exam




11/11

Veteran's Day




11/12

Project
Create a game of chance (i.e. carnivalstyle game)
Can
work Individually or in pairs. Presenttion may be in the form of a
PowerPoint, poster or physical demonstration (build it).
Elements of the presenttion MUST
include: Description of game & ways to win Probabilities of
winning & losing Fair price of the game Price you will charge
for the game Expected value per play All calculations shown
Rationle for the decisions you made while making up the game How
did probabilities affect those decisions Be Original. Common
preexisting games will suffer a severe
deduction. Unexcused
absenteeism on the day of the presenttion will result in a
grade of zero.




11/13

See Above




11/14

See Above




11/17

See Above




11/18

See Above




11/19

See Above




11/20

See Above




11/21

Enrichment/Makeup




11/2411/28

Thanksgiving Holiday




12/1

Presentations




12/2

Presentations




12/3

Enrichment: Numb3rs Episode 303 "Traffic"




12/4

Students will learn to define and develop continuous
and discrete random variables.


52 Random Variables
HW: See last panel of
lecture


12/5

Enrichment: Numb3rs Episode 202 "Better or Worse"




12/8

Enrichment: Numb3rs Episode 213 "Double Down"




12/9

Students will learn a basic definition of a
binomial distribution along with notation, and methods for finding
probability values.


53 Binomial Distribution
HW: See last panel of
lecture


12/10

Enrichment: Numb3rs Episode 217 "Mind Games"




12/11

Students will learn to calculate and use the Man, Variance, and
Standard deviation in a Binomial Distribution.


54 Mean, Variance & Std Deviation
HW: See
last panel of lecture


12/12

Enrichment: Numb3rs Episode 306 "Longshot"




12/15

Students will learn to evaluate small
distributions with rare probabilities with the Poisson Distribution.


55 Poisson Distribution
HW: See last panel
of lecture


12/16

Review




12/17

Unit Exam




12/18

Enrichment: Numb3rs Episode 322 "Under
Pressure"




12/19

Enrichment/Makeup




12/22  1/2

Winter Break




1/5

Students will develop the skill to find areas (or probabilities or
relative frequencies) corresponding to various regions under the graph
of the standard normal distribution.


Normal Distribution


1/6

Enrichment: Numb3rs Episode 316 "Contenders"




1/7

Students will learn to use a simple conversion that allows us to
standardize any normal distribution so that the same methods of the
previous section can be used.


Applications of Normal Distribution


1/8

Students will learn that some statistics are better
than others for estimating population parameters.


Sampling Distribution & Estimators


1/9

Review


Practice Exam


1/12

Review




1/13

SIA #2




1/14

Makeup/Enrichment




1/15

Makeup/Enrichment




1/16

Makeup/Enrichment
End of 2nd 9weeks & 1st Semester




1/19

MLK Holiday




1/20

Planning Day  Student Holiday




1/21

Data Collection Data is to be submitted via email as a
spreadsheet
attachment by midnight 1/23. Team name is to be in the subject line.
Send to kbaker@my.putnamschools.org. All students are to download and
print the compiled data prior to class on 1/30.


Compiled Data


1/22

Data Collection Continued




1/23

Students will learn how the distribution of the
sample means approaches a normal distribution as the
sample size increases


Central Limeit Theorem


1/26

Students will learn a a method for using a normal
distribution as an approximation to the binomial
probability distribution.


Normal as Approximation to Binomial


1/27

Project


Project Instructions


1/28

Students will learn the criteria for determining
whether the requirement of a normal distribution is
satisfied.


Assessing Normality


1/29





1/30

Review


Practice Exam


2/2

Review




2/3





2/4

UFO Data Collection




2/5

UFO Data Collection (Cont.)
Data Collection Data is to be submitted via email as a
spreadsheet
attachment by midnight 23/6. Team name is to be in the subject line.
Send to kbaker@my.putnamschools.org. All students are to download and
print the compiled data prior to class on 2/9.


Compiled Data


2/6

Grades Project


Data


2/9

UFO Project Cont.




2/10

UFO Quiz




2/11

Review




2/12

Unit Exam




2/13

Research




2/16

Research




2/17

Presidents Day




2/18

Research




2/19

Research




2/20

Research




2/23

Makeup/Enrichment
Num3ers 314  "Take
Out"




2/24

Students will learn methods for using a
sample proportion to estimate the value of a population proportion.


Estimating a Population Proportion
HW: pg
338341, 133 (odd)
Sig Fig Ref Sheet


2/25

SAT Testing




2/26

Students will
learn to estimate a population mean with a known standard deviation.


Estimating a Population Mean  Known SD
HW:
pg 309311, 123 (odd)


2/27

Research for Literature Review #2




3/2

Research/Enrichment/Makeup
FSA Writing Assesment (9th & 10th)




3/3

Research/Enrichment/Makeup
FSA Writing Assesment (9th)Quiz




3/4

Research/Enrichment/Makeup
FSA Writing Assesment (9th)Unit Exam




3/5

Research/Enrichment/Makeup
FSA Writing Assesment (9th)Unit Exam




3/6

Students will learn to estimate a population
mean with an unknown standard deviation.


Estimating a Population Mean  Unknown SD
HW: pg 320323, 123 (odd)


3/9

Students will learn to estimate a population
variance.


Estimating a Population Variance
HW: pg
351353, 119 (odd)


3/10

Quiz




3/11

Review




3/12

Unit Exam




3/13

Students will learn the basics of hypothesis
testing


Basics of Hypothesis Testing
HW: pg 378335,
133 (odd)


3/16

Students will learn how to test the claim
about a proportion.


Testing the Claim About a Proportion
HW: pg
414416, 119 (odd)


3/17

Review




3/18

SIA #3




3/19

Quiz




3/20

Students will learn how to test a claim about
a mean with a known standard deviation.


Testing a Claim About a MeanKnown SD
HW: pg
394398, 127 (odd)


3/23

Students will learn how to test a claim about
a mean with a known standard deviation.


Testing a Claim About a MeanUnknown SD
HW:
pg 405408, 127 (odd)


3/24

Quiz




3/25

Students will learn how to test a claim about a standard deviation.
End of Third 9Weeks


Testing a Claim About a Std Dev or Var
HW: pg
421423, 115 (odd)


3/26

Makeup/Enrichment




3/27

Planning Day




3/30  4/3

Spring Break




4/6

Review




4/7

Unit Exam




4/8

Students will learn to make inferences about 2 proportions.


Inferences About 2 Proportions
HW: pg
466468, 119 (odd)


4/9

Students will learn to make inferences
about two means generated with independent samples.


Inferences
About 2 MeansInd Samples
HW: pg
444448, 119 (odd)


4/10

Students will learn to make inferences from
matched pairs.


Inferences from Matched Pairs
HW: pg
454457, 113 (odd)


4/13

Quiz




4/14

Students will learn to compare variances in two
samples.


Comparing Var in 2 Samples
HW: pg
476478, 111 (odd)


4/15

Project Data
Collection




4/16

Project Data Collection Cont.




4/17

Project Analysis




4/20

Unit Exam




4/21

Students will learn to determine if there is a
relationship between two variables.


Correlation
HW: pg
520523, 119 (odd)


4/22

Students will learn express a linear
relationship between the independent and dependent variables.


Regression
HW: pg
535537, 119 (odd)


4/23

Students will learn to determine the
proportion of the variation in y that can be explained with the linear
relatonship between x and y.


Variation and Prediction Intervals
HW: pg
545547, 115 (odd)


4/24

Quiz




4/27

Students will learn express a linear
relationship between a dependent variables and two or more independent
variables.


Multiple Regression
HW: pg
555557, 115 (odd)


4/28

Students will learn to develop a mathematical
model that fits given data.


Modeling
HW: pg
562563, 17 (odd)


4/29

Project




4/30

Unit Exam




5/1

Students will learn to determine if a
distribution agrees (fits) a hypothesis.


Goodness of Fit
HW: pg
584587, 115 (odd)


5/4

Students will learn to test claims about tables.


Contingency Tables
HW: pg
598603, 117 (odd)


5/5

Students will learn to use McNemarâ€™s test for testing the null
hypothesis that the frequencies from the discordant (different)
categories occur in the same proportion.


McNemars Test for Matched Pairs
HW: pg
421423, 115 (odd)


5/6

Quiz




5/7

Students will learn to use the the method
of oneway analysis of variance, which is used for tests of hypotheses
that three or more population means are all equal.


OneWay ANOVA
HW: pg
626628, 111 (odd)


5/8

Students will earn to use the the method of
twoway analysis of variance, which is used with data partitioned into
categories according to two factors.


TwoWay ANOVA
HW: pg
638640, 113 (odd)


5/11

Project




5/12

Unit Exam




5/13

LazStats Training


Laz Stats Download
Users of the free WINE
program should be able to run either OpenStat or
LazStats (Windows versions) on a Linux system or
MacIntosh OSX system. Ubuntu users may need to download
ia32libs if using the 64bit version of Ubuntu.
LazStats User Manual
LazStats Tutorial
LazStats Practice Data Set


5/14

LazStats Training




5/15

Final Project Lab Time




5/18

Final Project Lab Time




5/19

Final Project Lab Time




5/20

Final Project Lab
Time




5/21

Final Project Lab Time




5/22

Final Project Lab Time




5/25

Memorial Day
Holiday




5/26

Project Paper Due
Today (10 pt deduction for each calendar day late)
Project Presentations


Project Tools, Requirements & Suggestions


5/27

Project Presentations




5/28

Project Presentations




5/29

Project Presentations




6/1

Review




6/2

SIA #4




6/3

Makeup/Enrichment
Half Day




6/4

Makeup/Enrichment
Half Day




6/5

Makeup/Enrichment
Half Day
Last Day of
School



