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Chapter 3

Chapter 3

7 Pages
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Department
Statistics
Course Code
STAB22H3
Professor
Moras

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Chapter 3
Anecdotal evidence: individual cases that are striking in some way and occur rarely that needs
not to be represented for any large group of cases.
Ex: friends are big fans the show “barney”, this cant be generalized to a larger population. This
is because any group of friends cannot be used as a representative for all college students
Available data: data produced in the past for some other purpose but may help answer a present
question
Ex: library and internet
-Statistical designs for producing data rely on either sampling or experiments
-The idea of sampling is to study a part (sample) in order to gain information about the
whole (population)
-Data are often produced by sampling a population of people or things.
-Census – attempt to contact every individual in the entire population
-Carefully conducted sample is better than a census
Observational vs experiement
Observational study: individuals are observed and variables of interest are measured but do not
attempt to influence the responses
Experimental study: give out treatments to individuals and observe responses
-The best way to see the affects of a change is to do an intervention where we actually
impose the change
-Intervention: where we impose the change
-Experiments are the only source when understanding cause and affect
-Confounding variable: observational study that examine the affect of a single variable of
an outcome can be misleading when the affects the explanatory variable are confounded
with those are other variables
Ex: observational study: child who attend daycare are rated by their parents as
disobedience, however this is not a cause-effect relationship b/c there can be lurking
variables influenced by their parents
Statistical techniques:
-Experiments require randomization
-Statistical inference: answers specific questions with a known degree of confidence
-Ethics - is the questions asked in order to make an experiment
3.1 Design of Experiments
- Experimental units: individuals on which the experiment is done on.
- When units are humans = subjects
- treatment: specific experimental condition applied to the units
Purpose of experiment is to reveal the response of one variable to changes in other variables.
In experiments:
www.notesolution.com
Explanatory variable = factors
Ex: asprin and beta carotene
Levels: values of factors
Ex: yes or no
Treatment: factor level combinations
Ex: 4 treatments => beta + asprin: yes + yes , yes +no , no + yes, no + no
Factors x levels give you the number of treatments:
Ex 3.7: Are smaller class sizes better
Factor: types of class
Levels: regular class + 1 teacher, regular class + techer + fulltime teacher aid and small class
Treaments = combinations of the levels and factors // 3(levels) x 1 (factor) = 3 treatments
Ex 3.8 Repeated exposure to advertising
Factor: 1: length of commercial
Level 1: 60s or 90 s
Factor 2: length of the repetition
Level 2: 1, 3 or 5 times
Treatments = 6
Response variable: attitude towards the product and the intention purchase it
Comparative experiments
Placebo effect: is the response to the dummy treatment
Ex: patients become favorable to any treatment even in the placebo effect
-Can eliminate confounding variables by comparing two groups = control groups and
experiment groups
Bias: when it favours certain outcomes
Randomization
Randomized comparative experiments
-Randomization produces two groups where the individuals are similar in all aspects
before the treatments are applied
-Comparative design helps ensure that the only thing that changes in both groups is the
factor being tested (ex: cell phone use while driving), everything else is in control.
-Therefore the difference in response should be due to either the factor being tested or the
chance of random assignment
For ex: to eliminate the chance of random assignment, the sample size should be larger so
that the sample has mixed individuals of those that react faster than others
Principles of experimental design:
-Compare two or more treatments
-Randomization
www.notesolution.com

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Description
Chapter 3 Anecdotal evidence: individual cases that are striking in some way and occur rarely that needs not to be represented for any large group of cases. Ex: friends are big fans the show barney, this cant be generalized to a larger population. This is because any group of friends cannot be used as a representative for all college students Available data: data produced in the past for some other purpose but may help answer a present question Ex: library and internet - Statistical designs for producing data rely on either sampling or experiments - The idea of sampling is to study a part (sample) in order to gain information about the whole (population) - Data are often produced by sampling a population of people or things. - Census attempt to contact every individual in the entire population - Carefully conducted sample is better than a census Observational vs experiement Observational study: individuals are observed and variables of interest are measured but do not attempt to influence the responses Experimental study: give out treatments to individuals and observe responses - The best way to see the affects of a change is to do an intervention where we actually impose the change - Intervention: where we impose the change - Experiments are the only source when understanding cause and affect - Confounding variable: observational study that examine the affect of a single variable of an outcome can be misleading when the affects the explanatory variable are confounded with those are other variables Ex: observational study: child who attend daycare are rated by their parents as disobedience, however this is not a cause-effect relationship bc there can be lurking variables influenced by their parents Statistical techniques: - Experiments require randomization - Statistical inference: answers specific questions with a known degree of confidence - Ethics - is the questions asked in order to make an experiment 3.1 Design of Experiments - Experimental units: individuals on which the experiment is done on. - When units are humans = subjects - treatment: specific experimental condition applied to the units Purpose of experiment is to reveal the response of one variable to changes in other variables. In experiments: www.notesolution.com
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