I.  Introduction.
        A.  The goal of estimation is to use sample statistics to develop 
            unbiased and efficient estimates of population parameters.
	B.  Estimation in scientific research and polling.

 II.  Point estimates.
        A.  Using a single sample statistic to estimate a population 
        B.  Calculating point estimates.

III.  Confidence intervals.
        A.  Defining a range of values in which you believe the actual 
            value occurs. 
        B.  Selecting a confidence level. 
              1.  Alpha level-the probability that an interval does not 
                  contain the actual population value. 
              2.  Alpha and confidence. 
              3.  Confidence and interval width. 
        C.  Calculating confidence intervals using z-scores. 
              1.  Calculating confidence intervals for means. 
                    a.  Assumptions.
                    b.  The formula.
              2.  Calculating confidence intervals for proportions. 
                    a.  Assumptions.
                    b.  The formula.
              3.  Estimating sample size needed to obtain confidence
		  intervals of a specified width.
                    a.  Assumptions.
                    b.  The formula.
        D.  Calculating confidence intervals for means using t-scores.
              1.  Assumptions.
                    a.  The t-distribution.
                    b.  Similarities with the z-distribution.
                    c.  Differences from the z-distribution.
                    d.  The t-table. 
              2.  The formula.

 IV.  Bias and efficency in estimation.       
        A.  Bias. 
              1.  Random vs. non-random sampling error. 
              2.  An estimate is unbiased if the mean of its sampling 
                  distribution is equal to the actual population value. 
        B.  Efficiency. 
              1.  An estimate is efficient if sample outcomes in a 
                  sampling distribution cluster around the mean of the 
              2.  Influences on the efficiency of confidence intervals 
                  (interval widths). 
                    a.  Dispersion of the population. 
                    b.  Sample size. 
                    c.  Confidence level.