statistics at a glance part i organizing, decribing, and analyzing data part ii producing data-...
TRANSCRIPT
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Statistics at a Glance
Part IOrganizing, decribing, and analyzing data
Part IIProducing Data- Surveys, Experiments, and
Observational studies
Part IIIProbability
Part IVStatistical Inference
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Data or Personal Experience?
Attendance Policy and Dances?
Airplane Crash Deaths?
Leukemia and Power Lines?
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Where does data come from?
Available DataData that were produced in the past for some other purpose
but that may help answer a present question.
Producing Data• Surveys
• Experiments• Observational Studies
Why might you use either method?
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Part IData Analysis
Data Analysis: organizing, displaying, summarizing, and asking questions of data
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Individuals and Variables
Individuals are the objects described by a set of data. Individuals may be people, but they may also be animals or things.
A variable is any characteristic of an individual. A variable can take different values for different
individuals.
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Categorical and Quantitative Variables
A Categorical Variable places an individual into one of several groups or categories.
A Quantitative Variable takes numerical values for which arithmetic operations such as adding and
averaging make sense.
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Meeting a new data set...
Who are the individuals described by the data?
What are the variables? Units?
Why were the data gathered?
When, where, how, and by whom were the data produced?
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Education in the United States
Who?
What?
Why?
When, where, how, and by whom?
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Distribution
The distribution of a variable tells us that values the variable takes and how often it takes these
values
Birth month in the school?
Favorite type of music?
Values close together or spread out?
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Exploratory Data Analysis
Using statistical tools and ideas to help you examine data in order to describe their main
features.
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Describing Categorical Variables
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Describing Categorical Variables
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Describing Categorical Variables
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Describing Quantitative Variables
Soccer goals scored by the US women's soccer team in 34 games during the 2004 season.
3 0 2 7 8 2 4 3 5 1 1 4 5 3 1 1 3 3 3 2 1 2 2 2 4 3 5 6 1 5 5 1 5
What do the numbers tell us?
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Describing Quantitative Variables
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Relationships between Variables
State vs national ACT scores
Attendance at different schools within the district
Seat belt usage and area of the country
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Relationships between Variables
Which airline appears to have less delayed flights?
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Relationships between Variables
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Relationships between Variables
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Relationships between Variables
Many relationships between two variables are influenced by other variables lurking in the
background
(We'll see more examples like this later).
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Part IIProducing Data
Surveys
• Select a sample• Ask questions
• Draw Conclusions
Where the data come from is important!(Ann Lander's)
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Observational study slide
Are surveys an observational study or experiment?
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Why one or the other?
What are the advantages of one or the other?
Estrogen and Heart Attacks Example
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Part IIIProbability
If I flip a coin four times, am I guaranteed to get heads twice?
The big idea of probability:Chance behavior is unpredictable in the short run but has a predictable pattern in the long
run.
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Probability:What happens in the long run
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Probability:answers the question “how likely”
This graph shows the probability for each possible number of correct guesses for an experiment in Mr. Bullard's class. If it the results of the
experiment where complete chance, how likely would it be that 13 people would guess the correct answer in the experiment?
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Part IVStatistical Inference
Drawing conclusions from data
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Statistical Inference
A Gallup survey conducted an Internet survey of 1200 students, aged 13 to 17. They asked, “Have you, yourself, ever cheated on a test or exam?”
Forty-eight percent said “yes.”
If Gallup had asked the same question of all 13-to-17 year old students, would exactly 48% have
said yes?
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Statistical Inference
A Gallup survey conducted an Internet survey of 1200 students, aged 13 to 17. They asked, “Have you, yourself, ever cheated on a test or exam?”
Forty-eight percent said “yes.”
If they had selected a different sample of 1200 students to respond to the survey, would they
have gotten the same percent?
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Statistical Inference
Even under the best of situations, variation is everywhere.
When we study statistical inference, we learn that even with variation, we can be quite confident that
between 45% and 51% of all teenage students would say that they have cheated on a test.