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AMS 110, Probability and Statistics for Life Sciences

Catalog Description: A survey of probability theory and statistical techniques with applications to biological and biomedical situations. Topics covered include Markov chain models; binomial, Poisson normal, exponential and chi-square random variables; tests of hypotheses; confidence intervals; t-tests; analysis of variance, regression and contingency tables. May not be taken for credit in addition to  AMS 310 .

Prerequisites: AMS 151 or MAT 125 or 131 or 141

Antirequisite: May not be taken by students with credit for AMS 102 or AMS 310

3 credits

 

Required Course Materials for Summer and Fall 2020:

Please be sure to choose ISBN 9781323840115 which includes MyLab Access Code + eText (both items required for the course.)  Hard copy of the textbook is OPTIONAL (not required).

 

Students may purchase course materials through Follett Bookstore, or directly through their MyLab Statistics course in Blackboard:
https://www.bkstr.com/sbuweststore/shop/textbooks-and-course-materials

  • Log in to your Blackboard Account, and access Course AMS 110
  • Left margin will contain a link for “MyLab Statistics”
  • Click into ANY of the links that appear on the right side of the screen.
  • Follow the instructions to register.
  • When prompted, you can click the “Use an Access Code” option if you purchased from Follett, or can BUY HERE using a Credit Card or Paypal.
  • Once you complete this transaction, you can click “Go to Your Course"



     

The option above includes the Pearson eText; HARD COPY OF THE TEXTBOOK IS NOT REQUIRED

  • If you wish to purchase a loose-leaf version of the text, you can click “PURCHASE OPTIONS” from your MyLab Statistics course, and order a $49.95 copy mailed directly to you.

 

 

Topics
1.  Descriptive Statistics –  3 class hours
2.  Basic Concepts of Probability  –  6 class hours
3.  Discrete Probability Distributions  –  7 class hours
4.  Continuous Probability Distributions –  6 class hours 
5.  Statistical Estimation –  6 class hours
6.  Hypothesis Testing  – 7 class hours
7.  Regression and Correlation Methods  – 3 class hours
8.  Mid-Term Test and Review – 4 class hours

 

Learning Outcomes for AMS 110, Probability and Statistics for the Life Sciences
(Most of the material in AMS 110 is similar to AMS 102 but covered in greater depth.)

1.) Describe and apply the process of statistical investigations from conception through conclusion, with particular emphasis to life science applications.  This process involves:
     * Formulating questions and collecting data;
     * Analyzing data and drawing inferences;
     * Interpreting results and communicating conclusions.

2.) Demonstrate facility with, and a solid conceptual understanding of, the key tools of data analysis, including:
      * histograms; 
      * box plots, stem-and-leaf plots and other graphical displays;
      * measures of central tendency;
      * measures of dispersion.

3.) Demonstrate knowledge of elements of probability and key probability distributions, including:
      * probability of an event, sample space, equi-probable outcomes;
      * conditional probability and Bayes’ theorem;
      * binomial distribution;
      * normal distribution
      * chi squared distribution.

4.) Demonstrate facility with, and a solid conceptual understanding of, the key tools of statistical inference, including: 
      * z-scores;
      * estimation of intervals;
      * testing hypotheses, including Type 1 and Type 2 errors.

5.) Perform important statistical procedures, such as:
       * z-test;
       * t-test;
       * the chi square test;
       * linear regression.

6.) Work with technology to:
      * analyze data graphically; 
      * analyze data numerically; 
      * analyze data inferentially.

7.) Decide which statistical methods to use in which situations:
       * Recognizing which statistics tests apply in a situation;
       * Checking the necessary conditions for those methods to be valid.

8.)  Use statistics to address the biomedical research question at hand.
        * Interpret the results of statistical analyses to answer the research question;
        * Communicate conclusions that follow from the statistical analyses of the question.

9.)  Demonstrate an appreciation of the power and scope of statistical thinking for addressing research questions in a variety of scientific disciplines and in everyday life.

 

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