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