chapter 1 the role of statistics and the data analysis process
TRANSCRIPT
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Chapter 1
The Role of Statistics and the
Data Analysis Process
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What is statistics?
•the science of collecting, analyzing, and drawing conclusions from data
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Why should one study statistics?
1. To be informed . . .a) Extract information from tables,
charts and graphsb) Follow numerical argumentsc) Understand the basics of how data
should be gathered, summarized, and analyzed to draw statistical conclusions
Can dogs help patients with heart failure by reducing stress and anxiety?When people
take a vacation do they really
leave work behind?
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Why should one study statistics? (continued)2.To make informed judgments
3.To evaluate decisions that affect your life
If you choose a particular major, what are your chances of finding a job when you
graduate?
Many companies now require drug screening as a condition of employment. With these
screening tests there is a risk of a false-positive reading. Is
the risk of a false result acceptable?
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What is variability?
Suppose you went into a convenience store to purchase a soft drink. Does every can on the shelf contain exactly 12 ounces?
NO – there may be a little more or less in the various cans due to the variability that is inherent in the filling process.
In fact, variability is almost universal!universal!
It is variability that makes life
interesting!!
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If the Shoe Fits ...
The two histograms to the right display the distribution of heights of gymnasts and the distribution of heights of female basketball players. Which is which? Why?
Heights – Figure A
Heights – Figure B
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If the Shoe Fits ...
Suppose you found a pair of size 6 shoes left outside the locker room. Which team would you go to first to find the owner of the shoes? Why?
Suppose a tall woman (5 ft 11 in) tells you see is looking for her sister who is practicing with a gym. To which team would you send her? Why?
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The Data Analysis Process1. Understand the nature of the
problem
2. Decide what to measure and how to measure it
3. Collect data
4. Summarize data and perform preliminary analysis
5. Perform formal analysis
6. Interpret results
It is important to have a clear direction before
gathering data.It is important to carefully define the variables to be studied and to develop appropriate methods for determining their values.
It is important to understand how data is collected because the type of analysis that is appropriate depends on how the data was collected!
This initial analysis provides insight into important
characteristics of the data.
It is important to select and apply the appropriate inferential statistical
methodsThis step often leads to the formulation of new research
questions.
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Suppose we wanted to know the average GPA of high school graduates in the nation this year.
We could collect data from all high schools in the nation. What term would be used to
describe “all high school graduates”?
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Population
• The entire collection of individuals or objects about which information is desired
• A census is performed to gather about the entire population
What do you call it when you collect data
about the entire population?
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GPA Continued:Suppose we wanted to know the average GPA of high school graduates in the nation this year.
We could collect data from all high schools in the nation.
Why might we not want to use a census here?
If we didn’t perform a census, what would we
do?
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Sample
•A subset of the population, selected for study in some prescribed manner
What would a sample of all high school graduates across the nation look like?High school graduates from each state (region), ethnicity, gender, etc.
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GPA Continued:Suppose we wanted to know the average GPA of high school graduates in the nation this year.
We could collect data from a sample of high schools in the nation.
Once we have collected the data, what would we do
with it?
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Descriptive statistics•the methods of organizing & summarizing data
• Create a graph
If the sample of high school GPAs contained 1,000 numbers, how could the data be organized or summarized?
• State the range of GPAs• Calculate the average GPA
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GPA Continued:Suppose we wanted to know the average GPA of high school graduates in the nation this year.
We could collect data from a sample of high schools in the nation.
Could we use the data from our sample to answer this
question?
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Inferential statistics•involves making generalizations from a sample to a populationBased on the sample, if the average GPA for high school graduates was 3.0, what generalization could be made?
The average national GPA for this year’s high school graduate is approximately 3.0.Could someone claim that the average
GPA for graduates in your local school district is 3.0?No. Generalizations based on the results of a sample can only be made back to the population from which the sample came from.
Be sure to sample from the population of
interest!!
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Until Tomorrow……….
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Variable •any characteristic whose value may change from one individual to another
•Suppose we wanted to know the average GPA of high school graduates in the nation this year. Define the variable of interest.The variable of interest is the GPA of high school graduates
Is this a variable . . .The number of wrecks per week at the intersection
outside school? YES
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Data
•The values for a variable from individual observations
For this variable . . .The number of wrecks per week at the intersection outside . . . What could observations be? 0, 1, 2,
…
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Two types of variables
categorical
numerical
discrete continuous
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Categorical variables
•Qualitative
•Identifies basic differentiating characteristics of the populationCan you name any
categorical variables?
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Numerical variables•quantitative
•observations or measurements take on numerical values
•makes sense to average these values
•two types - discrete & continuous
Can you name any numerical variables?
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Discrete (numerical)
•Isolated points along a number line
•usually counts of items
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Continuous (numerical)•Variable that can be any value in a given interval
•usually measurements of something
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Identify the following variables:1. the color of cars in the teacher’s
lot
2. the number of calculators owned by students at your school
3. the zip code of an individual
4. the amount of time it takes students to drive to school
5. the appraised value of homes in your city
Categorical
Categorical
discrete numerical
Discrete numerical
Continuous numerical
Is money a measurement or a count?
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Classifying variables by the number of variables in a
data setSuppose that the PE coach records the height of each student in his class.
Univariate - data that describes a single characteristic of the population
This is an example of a univariate data
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Classifying variables by the number of variables in a
data setSuppose that the PE coach records the height and weight of each student in his class.
Bivariate - data that describes two characteristics of the population
This is an example of a bivariate data
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Classifying variables by the number of variables in a
data setSuppose that the PE coach records the height, weight, number of sit-ups, and number of push-ups for each student in his class.
Multivariate - data that describes more than two characteristics (beyond the scope of this course)
This is an example of a multivariate data
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Bar ChartWhen to Use Categorical data
How to construct– Draw a horizontal line; write the categories or labels below the line at regularly spaced intervals
– Draw a vertical line; label the scale using frequency or relative frequency
– Place equal-width rectangular bars above each category label with a height determined by its frequency or relative frequency
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Bar Chart (continued)What to Look For Frequently or infrequently occurring categories
Collect the following data and then display the data in a bar chart:
What is your favorite ice cream flavor?
Vanilla, chocolate, strawberry, or other
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Dotplot
When to Use Small numerical data sets
How to construct– Draw a horizontal line and mark it with an appropriate numerical scale
– Locate each value in the data set along the scale and represent it by a dot. If there are two are more observations with the same value, stack the dots vertically
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Dotplot (continued)
What to Look For – The representative or typical value– The extent to which the data values spread out– The nature of the distribution along the number line
– The presence of unusual values
Collect the following data and then display the data in a dotplot:
How many body piercings do you have?