Statistics
Chapter 1
•
What is Statistics?
o
The art and science of designing studies and analyzing the data that those studies
produce
o
Its ultimate goal is translating data into knowledge and understanding of the world
around us
o
Basically.
. the art and science of learning from data
•
Statistical methods
o
Design
:
planning how to obtain data to answer the question of interest
o
Description
: summarizing the data obtained
o
Inference
: making decisions and predictions based on that data
•
Descriptive Statistics
o
Utilizes numerical and graphical methods to look for patterns, to summarize and to
present the information in
sample
data
•
Inferential statistics
o
Utilizes sample data to make estimations, decisions, or other predictions about a
population
and measure their reliability (need probability)
•
Introduction to basic terms
o
Population
: an
entire
collection of subjects(persons or objects) whose properties are
to be analyzed
o
Sample
:
subset
if the population
o
Variable
: a
characteristic
about each subset of a population or sample
o
Parameter
: a numerical value summarizing the population data, a constant/truth
[remember by: p in population]
o
Statistic
: a numerical value summarizing the sample data, an estimate/vary
[remember by: s in sample]
•
Randomness an variability
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Random sampling
: each subject in the population has the same chance of being in the
sample
This is desirable because this sample tends to be a good reflection of the
population
Randomization is also important to good experimental design
o
Variable
: the measurements we make of a variable vary from subject to subject
Likewise, results of descriptive and inferential statistics vary, depending on the
sample chosen
•
What role do computers play?
o
Computer applications perform the calculations for data analysis
o
Data is organized in a data file
subject(row)
variable (column)
Chapter 2
(2.1) what are the types of data?
•
Variable
: characteristic of a subject about which information is sought
•
Two types:
o
Categorical
: each data value belongs to one of a set of data (gender, major, color)
almost always words
Ex: the average social security # or zip code would make no sense
o
Quantitative
: each data value takes numerical values that represent different
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 Spring '08
 smith
 Statistics, #, Frequency distribution, 50%, 360°

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