文档介绍：Quantitative Business
Analysis
page: 1
Objektives
of
the
course
page: 2
1. To gain an understandction decisions.
Examples: When to order additional new material? What is the safety stock
level?
3
page: 6
Meaningful
Quantitative
Analysis
Raw Data
1.
Analyzing Business Data - Introduction
. Descriptive and Inferential Statistics (I)
We differentiate between descriptive and inferential statistics
Descriptive statistics include techniques that are used
describe numerical data for easier interpretation (. in
to summarize and
tables or graphs).
Determination of parameters . average, median or variances
Inferential
statistics
include
techniques by which
decisions
about
a
statistical population or process are made only on a sample having been
observed with hypothese testing and estimations => the resulting decisions are made under conditions of uncertainty. Therefore the use of probability is required
page: 7
1.
Analyzing Business Data - Introduction
.
Descriptive
and
Inferential
Statistics (II)
page: 8
Inferential
Drawing conclusions and/or making decisions concerning a population based only on sample data
Descriptive
Collecting, summarizing and describing data
Statistics
Data and Data Sets
Data are the facts and figures collected, analyzed,
and summarized for presentation and interpretation.
•
All the data collected in a particular
study
are
referred
to
as
the
data set
for
the
study.
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Elements, Variables, and Observations
Elements are the entities on which data are collected.
A variable is a characteristic of interest for the elements.
The set of measurements obtained for a particular
element is called an observation.
A data set with n elements contains n observations.
The total number of data values in a complete data set is the number of elements multiplied by the number of variables.
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