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What is Statistics?
Statistics Is….
• Science and art of learning
through data
• Data are numbers with a context
Probability
• Study of chance behavior
through data
Sample vs. Population
• Population is the large group made up of
many individuals
• Sample is a smaller group of individuals
chosen from the population
Where do you get good data?
• Internet websites that have collected it for
you (available data)
• www.statca.ca
• www.inegi.gob.mx
• www.fedstats.gov
• www.cdc.gov/nchs
• You can collect your own data using the
prescribed methods explained in this
course
Some methods to collect data
• Surveys
• Observational studies
• Experiments
• Each of these will be studied in greater
detail later in the course in Unit 2
Data Analysis
• Characteristics of an individual are known
as variables
• Objects described by a set of data are
known as individuals
The 6 W’s & the H
• Who are the individuals that you have data
from
• What are the variables
• Why? (What is your underlying question)
• When?
• Where did you get the data from?
• How did you gather the data?
• By Whom was the data gathered?
Types of Variables
• Categorical (Qualitative) Variables
• Describe a quality that the variables have, you
can easily split the data into categories
• Quantitative Variables
• Gives a numerical value for a variable (You
can take the average of them)
Distribution of a Quantitative
Variable
• The pattern of variation of the numerical
values of a quantitative variable is known
as its distribution
• We can describe a distribution by its
center, shape and spread
• We will discuss distributions in much
greater detail later in the course mostly in
Units 2, 4, and 5
Data Anaylsis
• Examine a variable by itself first
• Study relationships among variables
• Utilize graphs and number summaries to
help organize data to make sense
Types of Graphs
(to be studied in Unit 1)
Qualitative:
Bar Graph
Side-by-side Bar Graph
Pie Chart
Quantitative:
Dotplot
Stemplot
Boxplot
Histogram
Ogive
Scatterplot
Probability
• Probability is usually unpredictable in the
short run but is regular and very
predictable in the long run
• We will study probability and long run
behavior in Unit 3 of the course
Statistical Inference (Units 4&5)
• How to draw conclusions from data
• Utilized in medical studies, political polling
• Allows you to make predictions and
conclusions
• We must understand that we cannot be
certain about our conclusions in statistics
so there is always room for error

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Intro to statistics

  • 2. Statistics Is…. • Science and art of learning through data • Data are numbers with a context
  • 3. Probability • Study of chance behavior through data
  • 4. Sample vs. Population • Population is the large group made up of many individuals • Sample is a smaller group of individuals chosen from the population
  • 5. Where do you get good data? • Internet websites that have collected it for you (available data) • www.statca.ca • www.inegi.gob.mx • www.fedstats.gov • www.cdc.gov/nchs • You can collect your own data using the prescribed methods explained in this course
  • 6. Some methods to collect data • Surveys • Observational studies • Experiments • Each of these will be studied in greater detail later in the course in Unit 2
  • 7. Data Analysis • Characteristics of an individual are known as variables • Objects described by a set of data are known as individuals
  • 8. The 6 W’s & the H • Who are the individuals that you have data from • What are the variables • Why? (What is your underlying question) • When? • Where did you get the data from? • How did you gather the data? • By Whom was the data gathered?
  • 9. Types of Variables • Categorical (Qualitative) Variables • Describe a quality that the variables have, you can easily split the data into categories • Quantitative Variables • Gives a numerical value for a variable (You can take the average of them)
  • 10. Distribution of a Quantitative Variable • The pattern of variation of the numerical values of a quantitative variable is known as its distribution • We can describe a distribution by its center, shape and spread • We will discuss distributions in much greater detail later in the course mostly in Units 2, 4, and 5
  • 11. Data Anaylsis • Examine a variable by itself first • Study relationships among variables • Utilize graphs and number summaries to help organize data to make sense
  • 12. Types of Graphs (to be studied in Unit 1) Qualitative: Bar Graph Side-by-side Bar Graph Pie Chart Quantitative: Dotplot Stemplot Boxplot Histogram Ogive Scatterplot
  • 13. Probability • Probability is usually unpredictable in the short run but is regular and very predictable in the long run • We will study probability and long run behavior in Unit 3 of the course
  • 14. Statistical Inference (Units 4&5) • How to draw conclusions from data • Utilized in medical studies, political polling • Allows you to make predictions and conclusions • We must understand that we cannot be certain about our conclusions in statistics so there is always room for error