TOPICS COVERED - Sections Shown with Numbers As in E-Book

CHAPTER 9 –PRODUCING DATA - EXPERIMENTS

TOPICS COVERED - Sections shown with numbers as in e-book

We will not cover all the material of the chapter and you will not be required to know the non-covered material in the class exam. Follow the outline listed below

Section 9.1 – OBSERVATION VERSUS EXPERIMENTS (pg. 223)

·  Observational Study - Cannot be used to establish “cause and effect” relationships

o  Often, in an observational study there is a lurking variable which is confounded with the explanatory variable and is responsible for the changes in the response variable

·  Experiment - Allow researchers to establish “cause and effect” relationships

Assignment 1:

·  Listen to STATS TUTOR in the e-book section OBSERVATION versus EXPERIMENT

Listen to the examples listed below and for each one

a)  Identify the explanatory and response variables

b)  Is the study an observational study or an experiment? Explain why

c)  Can you conclude causation? Why?

Example 1: POWER LINES AND CANCER.

Example 2: BOTOX AND EXCESSIVE SWEATING

Example 3: DRINKING BEER, WINE OR GRAPE JUICE HELPS PREVENT HEART DISEASE

Assignment 2: - helps to understand lurking variable

·  Within STAT TUTOR, In the same section of OBSERVATION versus EXPERIMENTS, the concepts of lurking and confounding variables are discussed. Listen to the example about: BREASTFED BABIES DO BETTER IN SCHOOL THAN BOTTLE FED BABIES in the section OBSERVATION versus EXPERIMENT

Section 9.2 – SUBJECTS, FACTORS TREATMENTS (p. 225)

·  Subject (individuals)

·  Treatment

·  Explanatory variable, x, FACTOR

·  Response variable, y

·  Control group

·  Placebo – to reduce the bias when the subjects react to the treatment because they believe it will help them

Assignment 3: no need to turn in

·  Use STATS TUTOR within the section SUBJECTS, FACTORS, TREATMENTS and listen to the examples listed below in order to recognize the vocabulary listed above.

Example 1: “FERTILIZER and corn yield”

Example 2: “The Salk Vaccine Experiment”

·  We can produce data intended to answer specific questions by observational studies or experiments. Sample surveys that select a part of a population of interest to represent the whole are one type of observational study. Experiments, unlike observational studies, actively impose some treatment on the subjects of the experiment.

·  Variables are confounded when their effects on a response can’t be distinguished from each other. Observational studies and uncontrolled experiments often fail to show that changes in an explanatory variable actually cause changes in a response variable because the explanatory variable is confounded with lurking variables.

·  In an experiment, we impose one or more treatments on individuals, often called subjects. Each treatment is a combination of values of the explanatory variables, which we call factors.

·  The design of an experiment describes the choice of treatments and the manner in which the subjects are assigned to the treatments. The basic principles of statistical design of experiments are control and randomization to combat bias and using enough subjects to reduce chance variation.

·  The simplest form of control is comparison. Experiments should compare two or more treatments in order to avoid confounding of the effect of a treatment with other influences, such as lurking variables.

·  Randomization uses chance to assign subjects to the treatments. Randomization creates treatment groups that are similar (except for chance variation) before the treatments are applied. Randomization and comparison together prevent bias, or systematic favoritism, in experiments.

·  You can carry out randomization by using software or by giving numerical labels to the subjects and using a table of random digits to choose treatment groups.

·  Applying each treatment to many subjects reduces the role of chance variation and makes the experiment more sensitive to differences among the treatments.

·  Good experiments require attention to detail as well as good statistical design. Many behavioral and medical experiments are double-blind. Some give a placebo to a control group. Lack of realism in an experiment can prevent us from generalizing its results.

·  In addition to comparison, a second form of control is to restrict randomization by forming blocks of individuals that are similar in some way that is important to the response. Randomization is then carried out separately within each block.

·  Matched pairs are a common form of blocking for comparing just two treatments. In some matched pairs designs, each subject receives both treatments in a random order. In others, the subjects are matched in pairs as closely as possible, and each subject in a pair receives one of the treatments.

/ CHAPTER 9 SUMMARY /