School

University of Northern Colorado **We aren't endorsed by this school

Course

MBA 605

Subject

Statistics

Date

Sep 25, 2023

Type

Other

Pages

19

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2.1
Overview of Using Data:
Definitions and Goals
Data
are the facts and figures collected, analyzed, and summarized for
presentation and interpretation.
A characteristic or a quantity of interest that can take on different values is
known as a
variable
;
An
observation
is a set of values corresponding to a set of variables;
variation
is the difference in a variable measured over observations (time,
customers, items, etc.)
.
The values of some variables are under direct control of the decision maker
(these are often called decision variables
).
a quantity whose values are not known with certainty is called a
random
variable, or uncertain variable
2.2
Types of Data
Data can be categorized in several ways based on how they are collected and the
type collected
.
In many cases, it is not feasible to collect data from
the
population
of all elements of interest. In such instances, we collect data from
a subset of the population known as a
sample
.
a representative sample can be gathered by
random sampling
from the
population data.
Quantitative and Categorical Data
quantitative data
if numeric and arithmetic operations, such as addition,
subtraction, multiplication, and division, can be performed on them.
For instance,
we can sum the values for Volume in the Dow data in
Table 2.1
to calculate a total
volume of all shares traded by companies included in the Dow.
If arithmetic
operations cannot be performed on the data, they are considered
categorical
data
.
We can summarize categorical data by counting the number of
observations or computing the proportions of observations in each category.

Cross-Sectional and Time Series Data
Cross-sectional data
are collected from several entities at the same, or
approximately the same, point in time
.
Time series data
are collected over several time periods
.
Sources of Data
experimental study
, a variable of interest is first identified. Then one or more
other variables are identified and controlled or manipulated to obtain data about
how these variables influence the variable of interest.
Nonexperimental
, or
observational
,
studies
make no attempt to control the
variables of interest
.
A survey is perhaps the most common type of observational
study.
In some cases, the data needed for a particular application exist from an
experimental or observational study that has already been conducted
.
Anyone who wants to use data and statistical analysis to aid in decision making
must be aware of the time and cost required to obtain the data.
The cost of data acquisition and the subsequent statistical analysis should not
exceed the savings generated by using the information to make a better decision.
Frequency Distributions for Categorical Data
A
frequency distribution
is a summary of data that shows the number
(frequency) of observations in each of several nonoverlapping classes, typically
referred to as
bins
.
Relative Frequency and Percent Frequency
Distributions

Frequency Distributions for Quantitative Data
The three steps necessary to define the classes for a frequency
distribution with quantitative data are as follows:
1.
Determine the number of nonoverlapping bins.
2.
Determine the width of each bin.
3.
Determine the bin limits.
Number of Bins
Bins are formed by specifying the ranges used to group the data.
As a
general guideline, we recommend using from 5 to 20 bins. For a small