Chapter 9 Day 1

Parameter and Statistic  Parameter – a number that describes a population, usually impossible to find  Statistic – A number described in a sample, use to estimate an unknown parameter.

Sampling Distribution  Parameters - parameters are measures from the entire POPULATION  Measures of center – mean, mode, median  Measures of spread – range, variance, standard deviation, Q 1, Q 3, minimum, maximum  Measures of percentage – population proportion  Statistics – statistics are measures from one SAMPLE  Measures of center – mean, mode, median  Measures of spread - range, variance, standard deviation, Q 1, Q 3, minimum, maximum  Measures of percentage – sample proportion

Notation Review  N = number in population  μ = population mean  σ 2 = population variance  σ = population standard deviation  ρ = population proportion

Example  For each boldface number state whether it is a parameter or a statistic and use appropriate notation to describe each number, for example p = 0.65  The Tennessee STAR experiment randomly assigned children to regular or small classes during their first four years of school. 40.2% of African Americans from small classes took the ACT or SAT college entrance exam. Only 31.7% of African Americans from regular classes took one of these exams.

Example  For each boldface number state whether it is a parameter or a statistic and use appropriate notation to describe each number, for example p = 0.65  A random sample of female college students has a mean height of 64.5 inches, which is greater than the 63-inch mean height of all adult American women.

Sampling Distribution

Example – Homework #6 Student Score