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

pok-statsUniversal-06-IntroInferentialStats

Supplemental readings:

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

    • Throwing Dice - Theory

  • 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