Download Basic Definitions and Concepts

Chapter 1
Introduction
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Learning Objectives

To learn the basic definitions used in statistics and some of its key
concepts.

To obtain an overview of the material in the text.
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Basic Definitions and Concepts
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Population: The specific collection of objects of interest.
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Sample: Any subset or sub-collection of the population.
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Census: A sample that consists of the whole population.
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Measurement: A number or attribute computed for each member of a
population or of a sample.
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Parameter: A number that summarizes some aspect of the population as a
whole.
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Statistic: A number computed from the sample data.
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Basic Definitions and Concepts
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Statistics: A collection of methods for collecting, displaying, analyzing, and
drawing conclusions from data.
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Descriptive Statistics: The branch of statistics that involves organizing,
displaying, and describing data. It utilizes numerical and graphical methods
to look for patterns in a data set, to summarize the information revealed
in a data set and to present that information in a convenient form.
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Inferential Statistics: The branch of statistics that consists of methods for
drawing and measuring the reliability of conclusions about a population
based on information obtained from a sample of the population.
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Basic Definitions and Concepts
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A measure of reliability is a statement about the degree of uncertainty
associated with a statistical inference.
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Example: Based on our analysis, we think 56% of soda drinkers prefer Coke
to Pepsi, ± 5%.
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These ideas will be developed in chapter 7.
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Basic Definitions and Concepts
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Qualitative variable: allows for the classification of individuals based on
some attribute or characteristic. It is a non-numerically valued variable.
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Quantitative variable: provides numerical measures of individuals.
Arithmetic operations such as addition and subtraction can be performed
on the values of the quantitative variable and provide meaningful results.
•
A discrete variable is a quantitative variable that either has a finite number of possible
values or a countable number of possible values.
•
A continuous variable is a quantitative variable that has infinitely many possible values
that correspond to some continuous scale that covers a range of values without gaps,
interruptions, or jumps. A continuous variable can be measured to any desired level of
accuracy.
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Basic Definitions and Concepts

Qualitative data: Measurements or observations for which there is no
natural numerical scale, but which consist of attributes, labels, or other
non-numerical characteristics.
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Quantitative data: Numerical measurements or observations that arise
from a natural numerical scale.
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Overview of the Text
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Chapter 4 deals with statements of probability.
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Chapter 5 deals with discrete random variables.
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Chapter 6 deals with continuous random variables and the Central Limit
Theorem (CLT).
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Chapter 7 deals with confidence intervals.
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Chapter 8 deals with hypothesis testing.
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Key Takeaways

Statistics is a study of data: Describing properties of data (descriptive
statistics) and drawing conclusions about a populations based on
information in a sample (inferential statistics).
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The distinction between a population together with its parameters and a
sample together with its statistics is a fundamental concept in inferential
statistics.
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Information in a sample is used to make inferences about the population
from which the sample was drawn.
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Key Takeaways
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Statistics computed from samples vary randomly from sample to sample.
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Conclusions made about population parameters are statements of
probability.
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