ExperimentalDesign.ppt

(1)

Chapter 13

(2)

Definitions:

1) Observational study -

observe outcomes without

imposing any treatment

2) Experiment - actively impose

some treatment in order to

(3)

I’ve developed a new rabbit food, Hippity Hop.

Rabbit Food

Makes fur

soft &

shiny!

Increases

energy!

100% of daily

vitamins &

(4)

Can I just make these claims?

What must I do to make these

claims?

Who (what) should I test this

on?

What do I test?

NO

Do an experiment

Rabbits

(5)

3)Experimental unit – the single

individual (person, animal,

plant, etc.) to which the

different treatments are

assigned

4) Factor – is the explanatory

variable

(6)

6) Response variable – what you

measure

7) Treatment – a specific

(7)

I

plan to test my new rabbit

food.

What are my experimental

units?

What is my factor?

What is the response variable?

Rabbits

Type of food

(8)

Hippity Hop

I’ll use my pet rabbit, Lucky!

Since Lucky’s coat is shinier &

he has more energy, then

(9)

8) Control group – a group that

is used to compare the factor

against; can be a placebo or the

“old” or current item

9) Placebo – a “dummy”

(10)

Old Food _{Hippity Hop}

Now I’ll use Lucky & my friend’s rabbit, Flash. Lucky gets Hippity Hop

food & Flash gets the old rabbit food.

WOW! Lucky is bigger &

shinier so Hippity Hop is

better!

(11)

The first five rabbits that I catch will get Hippity Hop food and the remaining five will

get the old food.

The Hippity Hop rabbits have

(12)

Number the rabbits from 1 – 10.

Place the numbers in a hat.

1 2 3 4 5 6 7 8 9 ₁₀

The first five numbers pulled from the hat will be

the rabbits that get Hippity Hop food.

I

evaluated the rabbits & found

that the rabbits eating Hippity Hop

are better than the old food!

The remaining rabbits get the old food.

(13)

10) blinding - method used so

that units do not know which

treatment they are getting

(14)

Rabbit Food

Hippity Hop

Rabbit Food

makes fur soft

and shiny, &

increases

energy for

ALL

types of

rabbits!

Can I make this

(15)

Principles of Experimental

Design

• Control

of effects of extraneous

variables on the response – by

comparing treatment groups to a

control group (placebo or “old”)

• Replication

of the experiment on

many subjects to quantify the natural

variation in the experiment

(16)

The

ONLY

way to show

cause & effect is with a

designed,

(17)

Example 1: A farm-product manufacturer wants to determine if the yield of a crop is different when the soil is treated with three different types of fertilizers. Fifteen similar plots of land are planted with the same type of seed but are fertilized differently. At the end of the growing season, the mean yield from the sample plots is compared.

Experimental units? Factors?

Levels?

Response variable?

How many treatments?

Plots of land

Type of fertilizer

Fertilizer types A, B, & C Yield of crop

(18)

Example 2: A consumer group wants to test cake pans to see which works the

best (bakes evenly). It will test aluminum, glass, and plastic pans in both gas and

electric ovens.

Experiment units? Factors?

Levels?

Response variable?

Number of treatments?

Two factors - type of pan & type of oven

Type of pan has 3 levels (aluminum, glass, & plastic & type of oven has 2 levels (electric & gas)

How evenly the cake bakes 6

(19)

Example 3: A farm-product manufacturer wants to determine if the yield of a crop is different when the soil is treated with three different types of fertilizers. Fifteen similar plots of land are planted with the same type of seed but are fertilized differently. At the end of the growing season, the mean yield

from the sample plots is compared.

Why is the same type of seed used on all 15 plots?

What are other potential extraneous variables?

Does this experiment have a placebo? Explain

It is part of the controls in the experiment.

(20)

Experiment Designs

• Completely randomized – all

experimental units are

allocated at random among all

treatments

Treatment group 1

Treatment group 2

(21)

Treatment C

Treatment B

Completely randomized design Randomly assign

experimental units to treatments

Treatment A

(22)

• Randomized block – units are

blocked into groups

(homogeneous) and then

randomly assigned to treatments

R an do m a ss ig nm en t Group1 Group2 Treatment 1 Treatment 2 Treatment 3 Treatment 3 Treatment 2Treatment 1

explanatory _response

varaible _varaible

(23)

Treatment B

Randomized block design Randomly assign

experimental units to treatments

Treatment A

Put into homogeneous groups

(24)

– match up experimental units

according to similar

characteristics & randomly assign

on to one treatment & the other

automatically gets the 2nd

treatment

– have each unit do both

treatments in random order

– the assignment of treatments is

dependent

• Matched pairs - a special

_{Matched pairs - a special}

type of block design

(25)

Pair experimental units according to

specific

characteristics. Next, randomly assign

one unit from a pair to Treatment A. The

other unit gets Treatment B.

Treatment A Treatment B

This is one way to do a matched

pairs design – another way is to have the individual unit do both

(26)

12) Confounding variable – the

effect of the confounding

variable on the response cannot

(27)

Suppose we wish to test a new

(28)

Treatment B

Treatment & group are confounded

Treatment A

Treatment A Treatment B

One group is assigned to

treatment A & the other group to

treatment B.

Confounding

does

NOT

(29)

Example 4: An article from

USA

Today

reports the number of victims

of violent crimes per 1000 people. 51

victims have never been married, 42

are divorced or separated, 13 are

married, and 8 are widowed.

Is this an experiment? Why or why

not?

What is a potential confounding

variable?

Age – younger people are more at risk _{to be victims of violent crimes}

(30)

Example 5: Four new word-processing

programs are to be compared by measuring

the speed with which standard tasks can

be completed. One hundred volunteers are

randomly assigned to one of the four

programs and their speeds are measured.

Is this an experiment? Why or why not?

What type of design is this? Factors? Levels?

Response variable?

Yes, a treatment is imposed.

Completely randomized

one factor: word-processing program with 4 levels

(31)

Example 5: Four new word-processing

programs are to be compared by

measuring the speed with which

standard tasks can be completed.

One hundred volunteers are randomly

designed to one of the four programs

and their speeds are measured.

Is there a potential confounding

variable?

_{Can this design}

be improved? Explain.

NO, completely randomized designs have no confounding

You could do a block

design where each person uses each program in

(32)

Example 6: Suppose that the manufacturer wants to test a new fertilizer against the

current one on the market. Ten 2-acre plots of land scattered throughout the county are used. Each plot is subdivided into two subplots, one of which is treated with the current fertilizer, and the other with the new fertilizer. Wheat is planted and the crop yields are measured.

What type of design is this? Why use this

method?

When does

randomization occur?

Matched - pairs design

Randomly assigned

(33)

Randomization

reduces bias by

spreading any uncontrolled

confounding variables evenly

throughout the treatment groups.

Variability

is controlled by sample

size. Larger samples produce

statistics with less variability.

Blocking

also helps reduce

variability.

Is there another way

to reduce variability?

(34)

High bias & low variability

Low bias & low variability Low bias & high variability