Download - Enrollment Fall 2005 (all students)
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Enrollment Fall 2005 (all students)
Classification Men Women Total
Undergraduate 1,533(52%)
1,416(48%) 2,949
Professional* 17 22 39
Graduate 1,285 698 1,983
Master 505 276 781
Doctoral 780 422 1,202
Total2 2,835 2,136 4,971
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Geographic Origin3 (Fall 2005)
Undergraduates* Graduates Total Master Doctoral
Texas 1,532(51.3%) 474 482 2,488
Other U.S. 1,320(44.2%) 157 178 1,655
International 96(3.2%) 123 521 740
Not Designated 40(1.3%) 27 21 88
Total 2,988 781 1,202 4,971
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Student Demographics (Fall 2005)
Undergrad Grad
# % Master % Doctoral %
Architecture 126 4% 74 9% 1 1%
Engineering 751 25% 36 5% 464 39%
Humanities 559 19% 16 2% 175 14%
Management -- 0% 471 60% -- 0%
Music 128 4% 123 16% 39 3%
Natural Sciences 704 23% 29 4% 346 29%
Social Sciences 693 23% -- 0% 135 11%
Interdisciplinary 21 1% -- 0% 42 3%
Continuing Studies -- 0% 32 4% -- 0%
Unclassified 6 1% -- 0% -- 0%
Total 2,988 781 1,202 100%
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Chapter 1Statistics: The Art and Science of
Learning from Data
Learn ….
What Statistics Is
Why Statistics Is Important
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Chapter 1
Learn…
How Data is Collected
How Data is Used to Make Predictions
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Section 1.1
How Can You Investigate using Data?
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Health Study
Does a low-carbohydrate diet result in significant weight loss?
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Market AnalysisAre people more likely to stop at a
Starbucks if they’ve seen a recent TV advertisement for their coffee?
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Heart Health
Does regular aspirin intake reduce deaths from heart attacks?
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Cancer ResearchAre smokers more likely than non-
smokers to develop lung cancer?
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To search for answers to these questions, we…
Design experiments
Conduct surveys
Gather data
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Statistics is the art and science of:
Designing studies Analyzing data Translating data into knowledge and
understanding of the world
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Example from the National Opinion Center at the University of Chicago:
General Social Survey (GSS) provides data about the American public
Survey of about 2000 adult Americans
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Example from GSS: Do you believe in life after death?
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Three Main Aspects of StatisticsDesign
Description
Inference
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Design
How to conduct the experiment
How to select the people for the survey
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Description
Summarize the raw data
Present the data in a useful format
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Inference
Make decisions or predictions based on the data.
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Example: Harvard Medical School study of Aspirin and Heart attacks
Study participants were divided into two groups• Group 1: assigned to take aspirin• Group 2: assigned to take a placebo
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Example: Harvard Medical School study of Aspirin and Heart attacks
Results: the percentage of each group that had heart attacks during the study:
0.9% for those taking aspirin 1.7% for those taking placebo
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Example: Harvard Medical School study of Aspirin and Heart attacks
Can you conclude that it is beneficial for people to take aspiring regularly?
Example: Harvard Medical School study of Aspirin and Heart attacks
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Section 1.2
We Learn About Populations Using Samples
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Subjects
The entities that we measure in a study
Subjects could be individuals, schools, countries, days,…
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Population and Sample
Population: All subjects of interest
Sample: Subset of the population for whom we have data
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Geographic Origin (Fall 2005)
Undergraduates* Graduates Total Master Doctoral
Texas 1,532(51.3%) 474 482 2,488
Other U.S. 1,320(44.2%) 157 178 1,655
International 96(3.2%) 123 521 740
Not Designated 40(1.3%) 27 21 88
Total 2,988 781 1,202 4,971
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Enrollment Fall 2005Classification Men Women Total
Undergraduate 1,533(52%)
1,416(48%) 2,949
Professional* 17 22 39
Graduate 1,285 698 1,983
Master 505 276 781
Doctoral 780 422 1,202
Total2 2,835 2,136 4,971
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Majors (Fall 2005)Undergrad Grad
# % Master % Doctoral %
Architecture 126 4% 74 9% 1 1%
Engineering 751 25% 36 5% 464 39%
Humanities 559 19% 16 2% 175 14%
Management -- 0% 471 60% -- 0%
Music 128 4% 123 16% 39 3%
Natural Sciences 704 23% 29 4% 346 29%
Social Sciences 693 23% -- 0% 135 11%
Interdisciplinary 21 1% -- 0% 42 3%
Continuing Studies -- 0% 32 4% -- 0%
Unclassified 6 1% -- 0% -- 0%
Total 2,988 781 1,202 100%
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Example Format• Picture the Scenario• Question to Explore• Think it Through• Insight• Practice the concept
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Example: The Sample and the Population for an Exit Poll
In California in 2003, a special election was held to consider whether Governor Gray Davis should be recalled from office.
An exit poll sampled 3160 of the 8 million people who voted.
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What’s the sample and the population
for this exit poll?
The population was the 8 million people who voted in the election.
The sample was the 3160 voters who were interviewed in the exit poll.
Example: The Sample and the Population for an Exit PollExample: The Sample and the Population for an Exit Poll
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Descriptive Statistics
Methods for summarizing data Summaries usually consist of graphs
and numerical summaries of the data
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Types of U.S. Households
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Inference
Methods of making decisions or predictions about a populations based on sample information.
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Parameter and StatisticA parameter is a numerical
summary of the population
A statistic is a numerical summary of a sample taken from the population
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Randomness
Simple Random Sampling: each subject in the population has the same chance of being included in that sample
Randomness is crucial to experimentation
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Variability
Measurements vary from person to person
Measurements vary from sample to sample
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a. To describe whether a sample has more females or males.
b. To reduce a data file to easily understood summaries.
c. To make predictions about populations using sample data.
d. To predict the sample data we will get when we know the population.
Inferential Statistics are used:
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Chapter 2Exploring Data with Graphs and
Numerical SummariesLearn ….
The Different Types of Data
The Use of Graphs to Describe Data
The Numerical Methods of Summarizing Data
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Section 2.1
What are the Types of Data?
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In Every Statistical Study:
Questions are posedCharacteristics are observed
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Characteristics are Variables
A Variable is any characteristic that is recorded for subjects in the study
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Variation in Data
The terminology variable highlights the fact that data values vary.
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Example: Students in a Statistics Class
Variables:• Age• GPA• Major• Smoking Status• …
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Data values are called observations
Each observation can be:
• Quantitative
• Categorical
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Categorical Variable Each observation belongs to one of a set of
categories
Examples:• Gender (Male or Female)• Religious Affiliation (Catholic, Jewish, …)• Place of residence (Apt, Condo, …)• Belief in Life After Death (Yes or No)
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Quantitative Variable Observations take numerical values
Examples:• Age• Number of siblings• Annual Income• Number of years of education completed
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Graphs and Numerical Summaries
Describe the main features of a variable
For Quantitative variables: key features are center and spread
For Categorical variables: key feature is the percentage in each of the categories
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Quantitative Variables
Discrete Quantitative Variables
and
Continuous Quantitative Variables
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Discrete
A quantitative variable is discrete if its possible values form a set of separate numbers such as 0, 1, 2, 3, …
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Examples of discrete variables Number of pets in a household Number of children in a family Number of foreign languages spoken
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Continuous
A quantitative variable is continuous if its possible values form an interval
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Examples of Continuous Variables Height Weight Age Amount of time it takes to complete
an assignment
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Frequency Table
A method of organizing data
Lists all possible values for a variable along with the number of observations for each value
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Example: Shark Attacks
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Example: Shark Attacks What is the variable?
Is it categorical or quantitative?
How is the proportion for Florida calculated?
How is the % for Florida calculated?
Example: Shark Attacks
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Insights – what the data tells us about shark attacks
Example: Shark Attacks
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Identify the following variable as categorical or quantitative:
Choice of diet (vegetarian or non-vegetarian):
a. Categoricalb. Quantitative
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Number of people you have known who have been elected to political office:
a. Categoricalb. Quantitative
Identify the following variable as categorical or quantitative:
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Identify the following variable as discrete or continuous:
The number of people in line at a box office to purchase theater tickets:
a. Continuousb. Discrete
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The weight of a dog:a. Continuousb. Discrete
Identify the following variable as discrete or continuous:
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Section 2.2
How Can We Describe Data Using Graphical Summaries?
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Graphs for Categorical Data Pie Chart: A circle having a “slice of
pie” for each category
Bar Graph: A graph that displays a vertical bar for each category
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Example: Sources of Electricity Use in the U.S. and Canada
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Pie Chart
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Bar Chart
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Pie Chart vs. Bar Chart Which graph do you prefer? Why?
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Graphs for Quantitative Data Dot Plot: shows a dot for each
observation
Stem-and-Leaf Plot: portrays the individual observations
Histogram: uses bars to portray the data
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Example: Sodium and Sugar Amounts in Cereals
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Dotplot for Sodium in Cereals Sodium Data: 0 210 260 125 220 290 210 140 220 200 125
170 250 150 170 70 230 200 290 180
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Stem-and-Leaf Plot for Sodium in Cereal
Sodium Data: 0 210260 125220 290210 140220 200125 170250 150170 70230 200290 180
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Frequency TableSodium Data: 0 210
260 125220 290210 140220 200125 170250 150170 70230 200290 180
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Histogram for Sodium in Cereals
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Which Graph? Dot-plot and stem-and-leaf plot:
• More useful for small data sets• Data values are retained
Histogram• More useful for large data sets• Most compact display• More flexibility in defining intervals
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Shape of a Distribution Overall pattern
• Clusters?• Outliers?• Symmetric?• Skewed?• Unimodal?• Bimodal?
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Symmetric or Skewed ?
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Example: Hours of TV Watching
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Identify the minimum and maximum sugar values:
a. 2 and 14 b. 1 and 3c. 1 and 15 d. 0 and 16
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Consider a data set containing IQ scores for the general public:What shape would you expect a histogram of
this data set to have?a. Symmetricb. Skewed to the leftc. Skewed to the rightd. Bimodal
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Consider a data set of the scores of students on a very easy exam in which most score very well but a few score very poorly:
What shape would you expect a histogram of this data set to have?
a. Symmetricb. Skewed to the leftc. Skewed to the rightd. Bimodal