Topic 6: Introduction Inferential Statistics
(sampling & sampling distribution)
Chapter Objectives:
After this chapter, students should be able to
explain the purpose of inferential statistics
define and explain sampling techniques
explain and define key terms including population, sample, parameter, statistics, representative, EPSEM
differentiate between the sample distribution, sampling distribution, and population distribution
explain how the sampling distribution is related to the sample and population distributions
explain the First Theorem and the Central Limit Theorem
Supplemental readings:
read Pew's description of the purposes of oversampling and weighting Oversampling is used to study small groups, not bias poll results
Suggested activities:
Dice Experiment (graphs output)
limited to 2 dice, graphs the means to see how the distribution changes (but while there are variations, it always tends to approach a normal curve)
Try rolling 1 dice repeated times (keep hitting "Throw dice"
Do the same for 2 dice to see how it differs
visit AnyDice.com to try out what it would be like to roll a number of dice and the resulting graph (demonstrates the a normal distribution with increasing number of rolls; e.g. each dice is a respondent, each roll is sample)
Measuring Rocks as natural occurrence of normal distribution (possible activity)
if students gather and record 100+ regular size rocks (not the boulders in Central Park!), they will find that by in large the distribution of the sizes of the rocks tend to be normal
N males = 191
Males mean = 69.2
stdev = 4.2
N females = 207
Females mean = 63.2
stdev = 4.2
Total N = 398
Mean = 66
stdev = 5.1
Random Number Generators