1. Section 1.1
What is Statistics

2. Statistics is The study of how to: collect organize analyze Interpret
numerical information from data

3. The characteristic of an individual to be measured or observed.
Individuals are:
The people or objects included in a study
Example:
People who have climbed Mt. Everest.
A Variable is:
The characteristic of an individual to be measured or observed.
Example: age, weight, gender, nationality,
income and so on.

4. Types of Variables Quantitative variables are numerical measurements.
example: height, weight, age, income.
Example: number of siblings – “3”
Qualitative variables place individuals into a category or group
example: gender, nationality
Example: brand of computer – “Dell”

5. Population Data
The variable is the data from every individual of interest.
Example: The data from all individuals who have climbed Mt. Everest.
Example: incomes of all residents of a county -- $20,000, $49,000, $38,500, …

6. Sample Data
The variable is the data from only some of the individuals of interest
Example: The data from some of the individuals who have climbed Mt. Everest.
Example: incomes of selected residents -- $20,000, $49,000, $38,500

7. Levels of Measurement (NOIR)
Nominal
Ordinal
Interval
Ratio

8. The data consists of names, labels, or categories.
Nominal Measurement
The data consists of names, labels, or categories.
Examples: eye color – blue, green, hazel,…
The data cannot be ordered
from smaller to largest

9. Example: class rank – 1st, 2nd, …
Ordinal Measurement
This data can be ordered.
But differences cannot be calculated or interpreted.
Example: class rank – 1st, 2nd, …

10. Example: temperatures – 95°F, 37C,…
Interval Measurement
This data can be ordered.
The differences between data values are meaningful.
Example: temperatures – 95°F, 37C,…

11. Ratio Measurement This data can be ordered.
Differences between and ratios of data values are meaningful.
Examples (time):
It took 15 seconds from start to finish.
John took twice as long as Juan to finish.

12. Statistical methods
Provide us tools to obtain information from data. These methods break into two branches.
Descriptive Statistics
Inferential Statistics

13. Descriptive Statistics
Involves methods of:
organizing,
picturing, and
summarizing
information from samples or populations.
Inferential Statistics
Involves methods of using information
from a sample to
draw conclusions
regarding the population.