In the second half of the semester, we’ll be working on creating an annotated study guide for use in preparing for the final. Everyone will be responsible for creating a guide explaining how to do one type of problem.

Assignment (Due Thursday, April 4, 2:30pm). The list below gives an overview of topics/types of problems covered in the class.  In this assignment, you should choose THREE of the following topics that you think are interesting or might like to work on.  One or more of your choices must be from the second half of the class (items 10-18, things we have not studied yet).  Don’t be afraid to choose a topic you don’t know – you will have opportunity to learn, ask questions, and get help along the way!  Respond to this post, including your top three choices (give both the number and name of your choice, for example “my first choice is: #5, probability and counting”).

1. Frequency distributions (sec 2.1). tallying data, classes, relative frequencies and percentages, histograms
2. Measures of central tendency (sec 2.3). mean, median, mode
3. Measures of variation (sec 2.4). range, variance, standard deviation
4. Representing data visually (sec 2.2, 2.5).  stem-and-leaf plots, quartiles, box-and-whiskers plots
5. Probability and counting (sec 3.1, 3.4). combinations, permutations, sample space, events, probabilities
6. Combining probabilities (sec 3.2, 3.3). multiplication rule “and”, addition rule “or”, mutually exclusive events
7. Independent events (sec 3.2).  conditional probability, given, independent
8. Discrete probability distributions (sec 4.1).  mean, standard deviation, probability distributions based on frequency, based on tree diagram
9. Binomial distributions (sec 4.2).  trials, success, failure, binomial formula, finding probabilities in binomial distributions
10. The Normal Distribution (sec 5.1, 5.2, 5.3).  z score, finding probabilities, finding values
11. Normal Approximations to Binomial Distributions (sec 5.5). solving binomial problems using the normal distribution, continuity correction
12. Sample Mean problems (sec 5.4) finding probabilities involving the sample mean
13. Hypothesis Testing for the Mean (Large Samples) (sec 7.2), null hypothesis, alternative hypothesis, level of significance, rejection region, critical value, z-test
14. Hypothesis Testing for the Mean (Small Samples) (sec 7.3), null hypothesis, alternative hypothesis, rejection region, critical value, degrees of freedom, t-test
15. Correlation (sec 9.1), positive and negative correlation, correlation coefficient
16. Linear Regression (sec 9.2), find equation of the line of best fit/regression line, use it to predict values
17. Goodness-of-Fit Test (sec 10.1), multinomial experiments, chi-square test
18. Independence (sec 10.2), chi-square test for independence

As you know, your second exam will take place next Thursday, March 21.    I know you have a lot to work on this weekend, including WeBWorK assignment #6 and the Exam 2 Review Sheet, so we will NOT have an OpenLab assignment this week.  As you are working, if you have questions about WeBWorK, the review sheet, or anything else, I strongly encourage you to post them on the discussion board – either under the existing thread or by creating a new topic.

You can still earn extra credit this week by answering another students’ question on the discussion board.

Best of luck with your studying,
Mr. Reitz

UPDATE 3/12/13:  There have been some great, and very creative, responses so far – thanks.  Translating a “real-world” percentage into an experiment, and determining the possible outcomes, is a significant challenge!  In many cases I’ve asked a question or made a suggestion — if you respond to my comment appropriately, I’ll give you extra credit for this assignment.  Here are some tips, based on what I’ve seen so far:

• The Experiment should describe a process that could result in one of several outcomes. 
• The Outcomes  describe the different possible things that could happen.  There should always be more than one outcome.  Often, news articles will focus on something that already happened (as if the experiment already took place), and so we may already know what outcome was obtained in that particular case, and it’s easy to think of this as “THE outcome” — but there is always something else that could have happened, and might happen if the experiment were repeated. Don’t forget this ‘other outcome’.
• If your example began with a percentage, this will almost always be the probability that one of the outcomes will happen.  Take a look at your experiment/outcomes — does this fit?

Probability is an idea that shows up very often in the world outside our math classroom.  It occurs whenever a chance of something happening is described, often as a percentage (“a 90% chance of rain”), but sometimes in other forms (“a 9 out of 10 chance”).  However, it is not always simple to see how the basic setup described in class applies to one of these situations — that is, to think of probability in terms of an experiment, with various outcomes.

Recall that an experiment is a process which, when carried out, results in just one of several possible outcomes.  The outcomes are simply the different results that can occur.

Here are some examples from the news:

Example 1:

According to weather.com, there is a 10% chance of rain on Thursday, March 14 (at least, this is the percent reported on Wednesday, March 6).
Link: http://www.weather.com/weather/tenday/Brooklyn+NY+11201:4:US 

The experiment: we wait and see what the weather is like on Wednesday, March 6.
Outcomes: it rains, it doesn’t rain.

Example 2:

“Spanish researchers have completed the first human trial of a new vaccine against HIV. It has been successful in 90% of the HIV-free volunteers during phase I testing. This vaccine brings great hope to eradicate this plague forever.”
Link: http://gizmodo.com/5844706/this-90-successful-vaccine-may-be-our-best-chance-to-eradicate-aids

The experiment:  HIV-negative people are given the vaccine, and then are tested to see if they can contract HIV when exposed.
Outcomes: They do not contract HIV (the vaccine was  successful), or they do contract HIV (the vaccine was unsuccessful).

Assignment (Due Thursday, March 14):  Find an example of probability in the news.  Reply to this post including the following:

1. A brief description (what is it about?).
2. A link to news story or article.
3. Describe the experiment to which the probability refers.
4. Describe the outcomes of the experiment.

NOTE: You may NOT use the same example as someone else – please check the existing responses before you submit yours.

Extra Credit:  For extra credit, choose an example from your own major or intended career.  At the end of your submission, include the words “Extra Credit:” followed by  a brief description of how the example relates to your major/career choice.