Do Activity 5.2A

Statistic: * A number that describes a sample Parameter: A number that describes a population EXAMPLE: A polling agency takes a sample of 1500 American citizens and asks them if they are lactose intolerant. 12% say yes. This is interesting, since it has been shown that 15% of the population is lactose intolerant. 12% = _________15% = __________

EXAMPLE 2: A random sample of 1000 people who signed a card saying they intended to quit smoking were contacted a year after they signed the card. It turned out that 210 (21%) of the sampled individuals had not smoked over the past six months. 21% = _________ Population = Sample = Parameter of interest =

EXAMPLE 3: On Tuesday, the bottles of tomato ketchup filled in a plant were supposed to contain an average of 14 ounces of ketchup. Quality control inspectors sampled 50 bottles at random from the day’s production. These bottles contained an average of 13.8 ounces of ketchup. 14 = _________13.8 = __________

EXAMPLE 4: On a New York-to-Denver flight, 8% of the 125 passengers were selected for random security screening prior to boarding. According to the Transportation Security Administration, 10% of airline passengers are chosen for random screenings. 8% = _________10% = __________

EXAMPLE 5: A researcher wants to find out which of two pain relievers works better. He takes 100 people and randomly gives half of them medicine #1 and the other half medicine #2. 17% of people taking medicine 1 report improvement in their pain and 20% of people taking medicine #2 report improvement in their pain. 17% = _________20% = __________

Different Symbols… StatisticParameterMeasures? p proportion/percent μ means/averages

SAMPLING VARIABILITY * Different samples give us different results * Bigger samples are better!! * If we take lots of samples of the same size, the variation from sample to sample follows a predictable pattern = they make a good graph! * Different size samples give us different results True parameter

* Variability = spread/width of graph Larger samples give smaller variability: Lots of samples of size 100 True parameter Lots of samples of size 1000

Bias VS. Variability: the bulls eyes! * Turn to page 225- look at pictures * Bias- consistent, repeated measurements that are not close to the population parameter * Variability- basically like reliability * To reduce bias… use random sampling * To reduce variability… use larger samples! * We want to keep both of these low!

Label each as high or low for bias and variability True parameter

Label each as high or low for bias and variability True parameter

Try the HW problems: Page 226 #33, 35, 36