Chapter 12 Guiding Questions

1) Please define/describe and give an example of each of the following terms:

Simple Random Sample (SRS)

Stratified Sample

Cluster Sample

Systematic Sample

Census

Undercoverage

Nonresponse bias

Response Bias

2) What is a voluntary response sample and what is wrong with this type of sampling?

3) What is convenience sampling and what is wrong with this type of sampling?

4) Why is your sample size important when conducting a survey?

5) Why is randomizing important when conducting a survey?

6) What is the difference between a parameter and a statistic?

Chapter 11

How do you conduct a simulation in statistics?

What do you need to be careful of when running a simulation (What can go wrong)?

How can you run a simulation in your calculator?

For the following examples, please describe how you would run the following simulation, and then actually run the simulation.

Problem 1
You are about to take the road test for your driver's license. You hear that only 40% of candidates pass the test the first time. Suppose 20 people go to take their road test in one day. Run a simulation to find the number of people that pass their road test that day.

Problem 2
Recall the hiring discrimination problem from day 1 of class.  We ran a simulation using red and white beads.  Run two different simulations for this situation.  (The details if you don't have the paper with you, was 25 people up for a certain job, 15 male, 10 female.  A lottery is done to choose 8 of the 25,  the results were that 6 females and 2 males are chosen.  Do we suspect the lottery was rigged?)

Problem 3
Describe an event that can be modeled by a simulation.  Plan and run the simulation.

Ch 10 Problems Explined

Sorry about the tech issues yesterday with the Google form.

Since I wasn't able to see what problems were the biggest issues so I created these videos to explain the solutions.  They were made on the iPad, so they may be a little shaky.

Don't watch them all, just watch the ones you think will help you most.  If you are having troubles with logs, you may want to watch the Kahn Academy video at the end.

With about 25 minutest to go in class you will take a quiz.  So use your time wisely in the beginning of class.

Here is an explanation of the pressure problem... (The direct link should allow full screen if it doesn't work within the blog)

about 4 minutes, Link the video: http://youtu.be/eZd5yjZlZ2I

Here are the life expectancy problems (about 7 minutes) Link to the video: http://youtu.be/Z1_WXSIerrE

And the baseball salaries problem (note this one shows the work for logs at the end that were not discussed at the end of the life expectancy problem, about 8 minutes).

Link to the video http://youtu.be/DwaWkd94nGE

And finally not my video, this comes from the Kahn Acadmy

Chapter 10 Practice Problems

Hello students, today I would like to work on the practice problems found here (or that will be handed out in class)

Submit your answers here.  I will look over your results.

The site has a couple of resources that you may find helpful.  The StatTrek site has a video tutorial that is pretty nice, the youtube video relates specifically to using the TI-84 for transforming data.

Chapter 10 Guiding Questions

Here are a few questions you need to address:

1) What is the Ladder of Powers? (make a chart and explain what each part of the ladder means)

2) What are the four goals of re-expressing data?

3) What are exponential, logarithmic, and power models and what are their roles in re-espressing data?


To help answer these questions use the Ladder of Powers_Aligators.ftm to explore the ladder of powers.


Wildlife biologists can fairly accurately determine the length of an alligator from aerial photographs or from a boat. Determining the weight of an alligator from a distance is much more difficult. Wildlife biologists in Florida captured 25 alligators in order to collect data and to develop a model from which weight can be predicted from length. The data set (in case fathom isn't working on your computer) alligator.txt contains the resulting 25 measurements, the first variable is the alligator's weight (in pounds?) and the second is its length (in inches?). 

 

1. Create a scatterplot of the raw data.
2. Play around with the scatterplot, swapping out the values for your x and or y variables with the the calculated re-expressed values, such as y-squared, sqrt_y, sqrt_x..., in order to get a scatter plot that is approximately linear. 
3. When you have a scatter plot that is approximately linear, create a least squares regression line (LSRL)  by right clicking on the scatter plot and selecting "Least Squares Line
4. Using Google docs, explain how you can uses this model to predict the weight of an aligator with length 140 inches. 
1. Log into google apps.  One team member should create a file "Group # Alligator Problem"
2. Then in the upper right hand corner of the document, click "share"  Add your group members email addresses and your teacher's email address.
3. Be sure to include images from fathom, that show the original data, re-expressed data, LSRL, residual plots, and an explanation of how you find the predicted weight of a 140 inch alligator.

Multiple Choice Practice for Test

Chapter 9 Guiding Questions

Here are a few questions to consider for chapter 9:

What should we always look at before deciding a linear model is a good fit for our data?

What should we do if there looks to be subsets in our data?

What is extrapolation and why is it dangerous?

Describe/define high leverage points

Describe/define outliers.

Describe/define influential points.

Describe a point on a scatterplot that would have a large residual.

What is wrong with working with summary values when comparing two quantitative variables?