Have a nice Break!!

Project Presentations

In class students presented their projects on Collecting Data.  There is no homework.

Probability Models

In class students continued to create probability models and find mean (expected value) and standard deviation of problems involving discrete random variables. 

The notes are attached and the homework is listed below.

Notes - Probability Models

HW - complete pgs. 383-384 (1-17 odd, 18)
          read pgs. 372-376
          Finish Projects

Quiz - Basic Probability

In class students took a quiz on basic probability.  Afterwards, students began working on probability models for discrete random variables.  We will continue this discussion on Monday.  For homework, work on your projects.

Basic Probability Review

In class we reviewed chapters 14 and 15 on basic probability. 

The class notes are attached as is the practice quiz and answer key.  The homework is listed below.

Notes - Basic Probability Review


Practice Quiz - Basic Probability


Answer Key - Practice Quiz - Basic Probability


HW - Study for Quiz
          Read pgs. 366-372
          Work on Projects Due Wed. Dec. 17

Conditional Probabilities - Tree Diagrams

In class students reviewed how to use Venn diagrams and contingency tables to find probabilities.  Afterwards, students learned that when given a conditional probability, one should use a tree diagram to find other probabilities.

Things to Remember.

            1.  "Replacement" or "Without Replacement?"
            2.   Use Venn or Contingency table when given basic probabilities.
            3.   Use tree diagram when given conditional probabilities.
            4.  Be familiar with formulas but use graphic organizers to answer questions.
            5.  "At least one" or "some" means...1 - none.
            6.  Define/differentiate disjoint/mutually exclusive and independent...and prove
                 independence P (A|B) = P(A)


The notes are attached and the homework is listed below.

Notes - Conditional Probabilities

HW - pgs. 363-365 (13-33odd)
          Read 366-372
          Work on Projects

Probability Cont.

In class students continued learning about probability.  Students learned about 2 graphic organizers that can be used to answer questions involving probability:

1) Venn Diagram - disjoint/mutually exclusive, A ∩ B, A ∪ B.
2) Contingency Table - can answer all questions involving probability.

The homework is listed below and the notes are attached.

Notes - Probability Cont.

HW - Complete pgs. 361-363 (1-11 odd) - draw a Venn/Table for each question (good practice!)
          Read pgs. 353-360

Formal Probability

In class students were introduced to the basic probability rules.  Students should be familiar with and able to differentiate between disjoint/mutually exclusive and independent.

Students should also remember when a question asks for "at least 1" or "some" that means 1 - none.


The notes are attached and the homework is listed below.

Notes - Formal Probability

HW - pgs. 338-341 (12, 14, 16, 20, 24, 32, 34, 36)
          Read pgs. 342-351
          Project Proposal

Introduction to Probability

In class students were introduced to probability and talked about how we can use information about the long run to make predictions about what will happen in the short run.

The notes are attached below and there is no homework.

Notes - Introduction to Probability

Quiz - Collecting Data

In class students took a quiz on collecting data.  Afterwards, they were given a group project to complete with various deadlines. 

The homework is listed below and the project is attached.

Group Project - Collecting Data

HW - Read Chapter 14 - From Randomness to Probability

Review - Collecting Data

In class students reviewed the various ways in which we collected data which are as follows: simulation, sample survey and experiment. 

The notes on the section are attached below as is the homework.


Notes - Review - Collecting Data



Practice Quiz - Collecting Data

Answer Key - Practice Quiz - Collecting Data

HW - Study for Quiz
          Investigative Task - Forklifts and Backhoes
          Read Chapter 14 - pgs. 324-336 - "From Randomness to Probability"

Experimental Design (2)

In class we continued to talk about experimental design.  Be familiar with vocabulary and how to diagram experiments. 

The homework is listed below and the notes and investigative task are attached.

Notes - Experimental Design (2)

Investigative Task - Backhoes and Forklifts

HW - pgs. 312-315 (12-18 even, 33, 41)


Also, take a look at this video on ethics...good stuff.

Harvard - Course on Justice/Ethics

Experimental Design(1)

In class we finished up the section on sampling and did an activity on sampling.  We differentiated between a sample distribution (distribution of 1 sample) and a sampling distribution (distribution of many samples).  This led us to a discussion on the Central Limit Theorem which will play an important role during the second half of the course.

CW - Sampling Distribution

Afterwards, students were introduced to experimental design.  Students should be familiar with the following vocabulary words: factor(s) - explanatory or "x" variable(s), levels and treatments. 

The notes are attached and the homework is listed below.

Notes - Experimental Design (1)

HW - pgs. 312 (1-17 odd)
          read pgs. 301-309

**Quiz on Simulation, Sampling and Experimental Design - Thursday 11/20

Sampling (2)

In class we continued to talk about the various sampling methods.  Reiterated during this time was the difference between sampling error, or variability and sampling bias.  Sampling error is okay, it is bias that is the bane of any sample.  In class we completed the assignment below; complete and turn in if you were absent.


The homework is listed below and the notes are attached.

Notes - Sampling (2)

HW - pgs. 288-291 (8, 10, 12, 24, 26, 32)
        - Read pgs. 292-300 - Experimental Design

Sampling (1)

In class student learned about the 5 different methods of sampling.   Students also learned the difference between sampling variability/error and sampling bias.  Sampling error is okay as samples vary from one to the next.  Sampling bias is not okay as it renders the sample useless.

The notes are attached and the homework is listed below.

Notes - Sampling (1)

HW - pgs. 288 - 290 (1-11 odd, 15-27odd)
          Investigative Task #7 - ESP
         

Simulation

In class students learned how to use random numbers and the random number generator on the calculator to run a simulation and use that information to answer a question.

The notes are attached and the homework is listed below.

Notes - Simulation

HW - Read pgs. 268-285 - Sample Surveys
          Complete investigative Task - Alligators

Straightening the Line - Regression

In class students learned what to do when a scatterplot is not roughly linear and/or there is a pattern in the residual plot.  We can re-express the data using the ladders of powers.

The notes and classwork is attached.  The homework, Investigative Task #6, is listed below.

Notes - Re-Expressing the Data

Classwork - Non-Linear Models

HW - Read pgs. 255-263 - Understanding Randomness
          Investigative Task #6 - Alligators

Quiz #3 - The Normal Model and the Linear Model

In class students turned in Investigative Task #5 and then took Quiz #3 on the Normal Model and Linear Model.

There is no assigned homework but read Chapter 10 - Re - Expressing the Data if you have not done so already.

Quiz Review - Normal Model and Linear Model

In class we went over the homework and discussed the Investigative Task that is due Friday 10/24.

Afterwards, students completed a practice Quiz. 

***Disregard Question #7 on the practice quiz, we have yet to discuss how to complete the problem and we will briefly touch on it on Friday.

The homework is listed below and the Practice Quiz and Answer Key are attached.

Practice Quiz #3

Answer Key - Practice Quiz #3


HW - Investigative Task #5 - Olympic Long Jumps
          Read Chapter 10 - Re-Expressing the Data (pgs. 222-236)

Regression Wisdom

In class students finished a classwork activity on linear regression and turned in Investigative Task #4 - Smoking.  Afterwards, students learned about outliers, influential points and leverage.  It is very important to identify and distinguish between outliers and influential points.  Finally, we discussed what a lurking variable is...a lurking variable is an underlying variable that may cause association.  Examples include: 

       (a)  # of Firefighters (x) and cost of structure damage (y)....(lurking variable - size of fire)

       (b) # of TVs (x) and Life Expectancy (y)...(lurking variable - doctors/money spent on healthcare)


The notes are attached and the homework is listed below.


Notes - Regression Wisdom


HW - pgs. 214-221 (1-15 odd, 17, 21, 31)
          Read pgs. 222-236 - Re-Expressing the Data- For Fri. 10/24

         Investigative Task #5 - Olympic Long Jumps  - Due Fri. 10/24

Linear Regression cont.

In class students continued working on linear regression. The homework is listed below.

HW - Investigative Task #4
          Read Chapter 9 - "Regression Wisdom" - pgs. 201-210

Linear Regression cont.

In class students continued working on linear regression which is our second statistical model we have encountered in the course.  In class students learned how to calculate residuals (e = y - y hat).  They also learned that r is the correlation coefficient and r-squared is the coefficient of determination.  If r-squared is .25 that means that 25% of the variation in y can be explained by x.

Students also learned about extrapolation which is predicting for values that are outside our data range.

The homework is listed below and the notes are attached.

Notes - Linear Regression cont.

HW - Complete pgs. 192-198 (1-13 odd, 21, 27, 29, 31, 37, 41)
          Read pgs. 201 - 210

Investigative Task #4 - Smoking - Due Monday 10/20      


      

Linear Regression

In class students learned how to find the "least squared" line or line of regression. 

The notes are attached below and there is no homework.

Notes - Linear Regression

Association, Correlation and Causation

In class students were introduced to scatterplot which is the visual used to display 2 quantitative variables.  When describing a scatterplot we describe "form, direction and strength." 

We also differentiated between the words "association," "correlation" and "causation."  Know when (and when not to) use those terms.

The homework is listed below and the notes are attached.

Notes - Scatterplots


HW - Complete pgs. 164 (1-17odd, 25, 35)
          Read pgs. 171-179

Friday, October 3rd

The following is what you will complete during my absence.

1) The substitute teacher will hand out the answer key to the homework.  Look over it as a group.  If there are any problems or questions try to resolve them as a group. I also linked the answer key below for anyone who is absent.

Answer Key - HW - pgs. 129-133 (5-15 odd, 25, 27, 28, 38, 39, 41)

2) The substitute should also handout a classwork worksheet that can be completed with your Syracuse Partner.  Put both (all) of your names on your worksheet/loose-leaf.   Activity 14-8, 14-10 and 14-11 should be completed on a loose leaf sheet of paper.  Place completed work in the tray in the front of the room.  I have linked the classwork below for anyone who is absent.

CW - The Normal Distribution

3) Upon completing the classwork you can start the homework which will be Tuesday October 7th.:

HW - Complete pgs. 129-133 (17, 29, 43, 45, 47)
          Read Chapter 7 (146-160)

The Normal Model (cont.)

In class students continued working with the normal model to find normal percentiles (NormCDF in calculator) and percentiles to z-scores (InvNorm in calculator).

The homework is listed below and the notes are attached.

Notes - Normal Percentiles

HW -  pgs. 129-131 (5-15 odd, 25, 27, 38, 39, 41)
       -  Read Chapter 7 by Tuesday 10/7

The Normal Distribution

In class students took Quiz #2 on Categorical and Quantitative Data.  Afterwards, students were introduced to their first model in the course - The Normal Model.  The Normal Model will be used to talk about populations that are "normally distributed," meaning the shape of the distribution is unimodal and roughly symmetric. 

Students learned about the 68-95-99.7 rule which states that for a normal population 68% of the data lies within one standard deviation(σ) of the mean (μ), 95% of the data lies within 2 standard deviations of the mean and 99.7% of the data lies within 3 standard deviations of the mean. 

*Anything beyond 3 standard deviations of the mean is unusual.

The notes are attached.  The only homework is to get the AP Statistics Contract signed which I have linked below.

Notes - The Normal Model

AP Statistics Contract

Z-Scores

In class students were introduced to z-scores which are number of standard deviations away from the mean.  We now have a way of comparing apples to oranges.  How far away datum is from the mean tells us whether something is unusual or not.  Standardized tests such as the SATs and ACTs are scored based upon z-scores.

The notes are attached and the homework is listed below.

Notes - Z Scores

HW - Read pgs. 111-126
          Study for Quiz #2
          Investigative Task #3 - Auto Safety - Due 9/24

Comparing Distributions

In class students learned the various ways in which to compare distributions using the following:

                                              1) Histograms
                                              2) Back-to-Back Stemplots
                                             *3) Boxplots (2 or more distributions)

In class we spent time learning how to draw boxplots using the 5 number summary.  Students should be conscious of outliers (1.5 x IQR ± the quartiles) and extreme outliers (3 x IQR ± the quartiles).

The homework is listed below.  The notes and Investigative Task #3, due Wednesday 9/24, are attached.

Notes - Comparing Distributions

Investigative Task #3 - Auto Safety

HW - complete pgs. 99-101 (26-29, 34)
          read pgs. 104-109

**Quiz on Quantitative data Wednesday 9/24**

The 5 Number Summary and Symmetric Distributions

In class students learned how to use the 5 number summary (min, Q1, med., Q2, max) to describe a asymmetric distribution.  Students also learned how to find the Interquartile Range (IQR) = Q3 - Q1. 

Afterwards, students learned about symmetric distributions.  For symmetric distributions we use the mean and standard deviation to describe the center and spread, respectively.

The notes and homework are attached. 

Notes - Symmetric Distribution

HW - Complete Investigative Task #2 (attached below)
          Read Chapter 5 - Comparing Distributions

Investigative Task #2 - Dollar for Scholars

Quantitative Data

In class students took their first quiz on categorical data.  Afterwards, students were introduced to quantitative data and the 4 distributions used to display quantitative data:

                                      1. Histograms
                                      2. Stem and Leaf Plots
                                      3. Dot Plots
                                      *4. Box Plots (used to compare 2 or more distributions)

Students also learned how describe quantitative distributions:

                                       1. Shape - a. symmetry/b. modes
                                       2. Center - a. mean/ b. median
                                       3.Spread - a. Standard Deviation/b. Interquartile Range (IQR)

The notes are attached and the homework is listed below.

Notes - Quantitative Data

HW - pgs. 72-73 (7-15 odd)

Review - Catagorical Data/Contingency Tables

In class we reviewed the material on categorical data and contingency tables for Quiz #1 which will be administered on Friday.  Afterwards, students completed Groupwork Activity #1. 

For homework, study for the Quiz #1, complete Investigative Task #1 and read Chapter 4.

Contingency Tables

In class students were introduced to contingency tables that showed the interaction between 2 variables.  We can use a side-by-side bar chart, segmented bar graph or comparative pie charts to display the data.

Students were also introduced to marginal and conditional distributions.  Marginal distribution is the distribution along one variable.  Conditional distribution is the distribution of one variable along another.

If the conditional distribution = marginal distribution; we say the variables are independent.  If conditional distribution  ≠ marginal distribution we say there is an association between the two variables.

The notes are attached and the homework is listed below.

Notes - Contingency Table

HW - pgs. 40-43 (21-35 odd)



Due Friday:

Investigative Task #1 - Race and the Death Penalty

Read Chapter 4 - Displaying and Summarizing Quantitative Data

Introduction to Statistics/Categorical Data Displays

In class students were introduced to the world of statistics.  We also collected some class data and created some categorical data displays (bar graphs/pie charts).

The homework is listed below and the notes are attached.

Notes - Intro to Stats/Categorical Data Displays

HW - Read Chapter 3
        - Complete pgs. 38-39 (5-15 odd)


P.S. - Did I spell "Categorical" as "Catagorical" during the entire period and nobody corrected me?

First Day!

Welcome Back! I enjoyed meeting all of you today and getting back into the swing of things.  Below, I have attached the course syllabus.

Statistics - Syllabus

HW - Signed Syllabus
        - Finish Summer Packet