Download - Mng - Ch-1.Introduction Statistik
-
7/31/2019 Mng - Ch-1.Introduction Statistik
1/21
Business Statistics
-
7/31/2019 Mng - Ch-1.Introduction Statistik
2/21
What is Statistics ?
1. Collecting Data Data Analysis
e.g., Survey
2. Presenting Data
e.g., Charts & Tables
3. Characterizing Data Making decisione.g., Average
Business Statistics
-
7/31/2019 Mng - Ch-1.Introduction Statistik
3/21
Business Statistics
Statistical
Methods
Descriptive
Statistics
Inferential
Statistics
Statistical Methods
-
7/31/2019 Mng - Ch-1.Introduction Statistik
4/21
Business Statistics
Descriptive Statistics
1. Involves
Collecting Data
Presenting Data
Characterizing Data
2. Purpose
Describe Data
X = 30.5 S2 = 113
0
25
50
Q1 Q2 Q3 Q4
$
-
7/31/2019 Mng - Ch-1.Introduction Statistik
5/21
Business Statistics
Inferential Statistics
1. Involves
Estimation
HypothesisTesting
2. Purpose
Make decisions about
population characteristics
-
7/31/2019 Mng - Ch-1.Introduction Statistik
6/21
Business Statistics
Types of
Data
QuantitativeData
QualitativeData
-
7/31/2019 Mng - Ch-1.Introduction Statistik
7/21
Business Statistics
Quantitative Data
Measured on a numeric
scale.
Number of defectiveitems in a lot.
Salaries of CEO's of
oil companies.
Ages of employees at
a company. 3
52
71
4
8
943
120 1221
-
7/31/2019 Mng - Ch-1.Introduction Statistik
8/21
Business Statistics
Qualitative Data
Classified into categories.
College major of eachstudent in a class.
Gender of each employeeat a company.
Method of payment(cash, check, credit card).
$ Credit
-
7/31/2019 Mng - Ch-1.Introduction Statistik
9/21
Business Statistics
Type of Data
Four type of data :Nominal
Ordinal
Interval
Rasio
-
7/31/2019 Mng - Ch-1.Introduction Statistik
10/21
Business Statistics
Data
Categorical Numerical
Discrete Continuous
Examples:
Marital Status Political Party
Eye Color
(Defined categories)
Examples:
Number of Children
Defects per hour
(Counted items)
Examples:
Weight
Voltage
(Measured
characteristics)
-
7/31/2019 Mng - Ch-1.Introduction Statistik
11/21
Business Statistics
Levels of Measurement and Measurement Scales
Interval Data
Ordinal Data
Nominal Data
Highest Level
(Strongest forms of
measurement)
Higher Levels
Lowest Level
(Weakest form of
measurement)
Categories (noordering or direction)
Ordered Categories
(rankings, order, orscaling)
Differences betweenmeasurements but notrue zero
Ratio DataDifferences betweenmeasurements, truezero exists
-
7/31/2019 Mng - Ch-1.Introduction Statistik
12/21
Business Statistics
Levels of Measurement and Measurement Scales
Interval Data
Ordinal Data
Nominal Data
Height, Age, Weekly Food
Spending
Service quality rating,
Standard & Poors bond
rating, Student letter grades
Marital status, Type of car
owned
Ratio Data
Temperature in Fahrenheit,Standardized exam score
Categories (no orderingor direction)
Ordered Categories
(rankings, order, orscaling)
Differences betweenmeasurements but notrue zero
Differences betweenmeasurements, truezero exists
EXAMPLES:
-
7/31/2019 Mng - Ch-1.Introduction Statistik
13/21
Application Areas
Economics ForecastingDemographics
Sports Individual & TeamPerformance
Engineering Construction
MaterialsBusiness Consumer Preferences
Financial Trends
Business Statistics
-
7/31/2019 Mng - Ch-1.Introduction Statistik
14/21
Business Statistics
Random SampleEvery sample of size n has an equal chance of selection.
-
7/31/2019 Mng - Ch-1.Introduction Statistik
15/21
Business Statistics
Key Tems1. Population (Universe)
All items of interest
2. Sample Portion of population
3. Parameter
Summary measure about population
4. Statistic Summary measure about sample
P in Population
& Parameter
S in Sample& Statistic
-
7/31/2019 Mng - Ch-1.Introduction Statistik
16/21
Business Statistics
Activities of Statistics1. Designing the study:
First step
Plan for data-gathering
Random sample (control bias and error)
2. Exploring the data:
First step (once you have data) Look at, describe, summarize the data
Are you on the right track?
-
7/31/2019 Mng - Ch-1.Introduction Statistik
17/21
Business Statistics
3. Modelingthe dataA framework of assumptions and equations
Parameters represent important aspects of thedata
Helps with estimation and hypothesis testing
4. Estimating an unknown: Best guess based on data
Wrong - buy by how much?Confidence interval - were 95% sure that
the unknown is between
-
7/31/2019 Mng - Ch-1.Introduction Statistik
18/21
Business Statistics
5. Hypothesis testing:Data decide between two possibilities
Does it really work? [or is it just randomly
better?] Is financial statement correct? [or is error
material?]
Whiter, brighter wash?
-
7/31/2019 Mng - Ch-1.Introduction Statistik
19/21
Business Statistics
Probability Inverse of statistics
Statistics: generalizes from data to the world Probability: What if Assuming you know how the
world works, what data are you likely to see? Examples of probability:
Flip coin, stock market, future sales, IRS audit,
Foundation for statistical inference
The
world
You
seeProbability
Statistics
-
7/31/2019 Mng - Ch-1.Introduction Statistik
20/21
Business Statistics
Statistical View of the World Data are imperfect
We do the best we can -- Statistics helps!
Events are random
Cant be right 100% of the time Use statistical methods
Along with common sense and goodjudgment
Be skeptical! Statistics can be used to support contradictory
conclusions Look at who funded the study?
-
7/31/2019 Mng - Ch-1.Introduction Statistik
21/21
Business Statistics
Statistical Computer Packages
1. Typical Software SAS
SPSS MINITAB
Excel
2. Need Statistical
Understanding Assumptions
Limitations