Statistics is the science and art of learning from data. It involves collecting and analyzing data to describe variables and examine relationships between variables. There are different types of variables, including categorical and quantitative variables, and different ways of collecting data, such as surveys, experiments, and observational studies. Graphs and numerical summaries are used to organize and make sense of the data. Statistical inference allows conclusions to be drawn from a sample to a larger population with some degree of uncertainty.

1. What is 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