Course Information

Please see the course information below.
 
  Course:      MATH 115 - Probability and Statistics  
 
  Catalog Desc:  
(Prerequisite: Math 103 or placement by the current assessment methods. Credit awarded for either Math 115 or STAT 115, but not both courses.) 
An in-depth introduction to probability and statistics appropriate for students in the math and life/earth science disciplines. Descriptive statistics, introduction to probability theory, probability distributions, data sampling, estimation, correlation, hypothesis testing. (CSU/UC) AA/AS Area E, CSU Area B-4, IGETC Area 2, C-ID: MATH 110
 
 
  Expected Outcomes:  
1.  Organize, display, and summarize a data set using appropriate graphical and numerical methods.
2.  Determine the likelihood of events via enumeration methods and known distributions.
3.  Make a qualitative or quantitative inference about a population based on a sample.
 
 
  Critical Thinking:  
Students must be able to analyze a problem; choose appropriate concepts and methods to be used in its solution; then apply these tools skillfully to solve the problem. "Evaluate", "synthesize", and "differentiate" are all terms applicable to the use of probability and statistics in problem solving.
 
 
  Lecture Content:  
1. The nature of statistics
    a.  Simple Random Sampling
    b.  Experimental Designs
2. Descriptive statistics: relative position and levels/scales of measurement; 
    a.  Graphs and Charts
    b.  Measures of Center
    c.  Measures of Variation
3. Probability theory
    a.  Events
    b.  Conditional Probability
    c.  Independence
    d. The Mean and Standard Deviation of a Discrete Random Variable
    e.  The Binomial Distribution
    f.  The Normal Distribution
    g.  Sampling distributions
6. Inferential statistics
    a.Confidence intervals (means, proportions)
    b.Hypothesis testing (means, proportions)
    c. Chi square procedures (goodness of fit and independence)
  
7. Regression, correlation
    a.  Least Squares Regression Line
    b.  Correlation coefficient.
    c.  prediction
8. Applications using data from disciplines including business, social sciences, psychology, life science, health science, and education
9. Statistical analysis using technology such EXCEL, Minitab, or graphing calculators.
 
 
  Lab Content:  
N/A