Upload
rennamagdalena
View
222
Download
0
Embed Size (px)
Citation preview
8/11/2019 statistika bisnis chapter 1
1/29
Business Statistic: Chapter 1The Where, Why, and How ofData Collection
Prepared by:Renna Magdalena
8/11/2019 statistika bisnis chapter 1
2/29
Tools of Business Statistics
Descriptive procedures
Collecting, presenting, and describing data
Inferential procedures
Drawing conclusions and/or makingdecisions concerning a population based
only on sample data
Goal: Convert data into meaningful information!
8/11/2019 statistika bisnis chapter 1
3/29
Descriptive Procedures
Collect data
e.g., Survey, Observation,
Experiments Present data
e.g., Charts and graphs
Characterize data
e.g., Sample mean =n
xi
8/11/2019 statistika bisnis chapter 1
4/29
Making statements about a population by examiningsample results
Sample statistics Population parameters(known)
Inference unknown, but canbe estimated fromsample evidence
Sample Population
Inferential Procedures
8/11/2019 statistika bisnis chapter 1
5/29
Inferential Statistics
Estimation
e.g., Estimate the populationmean weight using the samplemean weight
Hypothesis Testing e.g., Use sample evidence to
test the claim that thepopulation mean weight is 120pounds
Drawing conclusions and/or making decisions concerning apopulation based on sample results.
8/11/2019 statistika bisnis chapter 1
6/29
Procedures for Collecting Data
Data Collection Procedures
Writtenquestionnaires
Experiments
Telephonesurveys
Direct observation andpersonal interview
8/11/2019 statistika bisnis chapter 1
7/29
Survey Design Steps
Define the issue What are the purpose and objectives of the
survey?
How will the survey be administered? (e.g. phone, email, face to face)
Define the population of interest
Develop survey questions Make questions clear and unambiguous Use universally-accepted definitions Limit the number of questions
8/11/2019 statistika bisnis chapter 1
8/29
Survey Design Steps
Pre-test the survey
Pilot test with a small group ofparticipants
Assess clarity and length
Determine the sample size andsampling method
Select sample and administer thesurvey
(continued)
8/11/2019 statistika bisnis chapter 1
9/29
Types of Questions
Closed-end Questions Select from a short list of defined choices
Example: Major: __business __liberal arts__science __other
Open-end Questions Respondents are free to respond with any value, words, or
statement
Example: What did you like best about this course?
Demographic Questions Questions about the respondents personal characteristics
Example: Gender: __Female __ Male
8/11/2019 statistika bisnis chapter 1
10/29
Observations and Interviews
Observations Data collected is observed and recorded
based on what takes place
Very subjective Example: Observe reactions of customersto a new store layout
Interviews Can be structured fixed set of questions Can use a variety of questions Requires more time from the researcher
8/11/2019 statistika bisnis chapter 1
11/29
Data Collection Pitfalls
Interview bias
Non response
Selection bias Observer bias
Measurement error
Internal/External validity
The objective is to collect accurate and reliable data!
http://images.google.com/imgres?imgurl=http://www.llnsciencepark.be/en2/images/caution.jpg&imgrefurl=http://www.llnsciencepark.be/en2/index.php%3Foption%3Dcom_content%26task%3Dview%26id%3D21%26Itemid%3D37&usg=__efY6hz89iWRC91riHE87Xlsjs7Y=&h=450&w=450&sz=33&hl=en&start=1&itbs=1&tbnid=VZSsFCl2m3JKhM:&tbnh=127&tbnw=127&prev=/images%3Fq%3Dcaution%26gbv%3D2%26hl%3Den8/11/2019 statistika bisnis chapter 1
12/29
A Population is the set of all items orindividuals of interest
Examples: All likely voters in the next electionAll parts produced todayAll sales receipts for November
A Sample is a subset of the population Examples: 1000 voters selected at random for interview
A few parts selected for destructive testingEvery 100th receipt selected for audit
Populations and Samples
8/11/2019 statistika bisnis chapter 1
13/29
Key Definitions
A population is the entire collection of things underconsideration and referred to as the frame
The sampling unit is each object or individual in the frame
A parameter is a summary measure computed to describea characteristic of the population
A sample is a subset of the population selected foranalysis
A statistic is a summary measure computed to describe acharacteristic of the sample drawn from the population
8/11/2019 statistika bisnis chapter 1
14/29
Population vs. Sample
a b c d
ef gh i jk l m n
o p q rs t u v w
x y z
Population Sample
b c
g i n
o r u
y
8/11/2019 statistika bisnis chapter 1
15/29
Why Sample?
Less time consuming than a census
Less costly to administer than acensus
It is possible to obtain statistical
results of a sufficiently highprecision based on samples
Strive for representative samples to reflect the
population of interest accurately!
8/11/2019 statistika bisnis chapter 1
16/29
Sampling Techniques
Convenience
Sampling Techniques
Nonstatistical Sampling
Judgment
Statistical Sampling
Simple
Random
Systematic
StratifiedCluster
8/11/2019 statistika bisnis chapter 1
17/29
Nonstatistical Sampling
Convenience Collected in the most convenient manner
for the researcher
Judgment Based on judgments about who in thepopulation would be most likely to provide
the needed information
8/11/2019 statistika bisnis chapter 1
18/29
Statistical Sampling
Items of the sample are chosen basedon known or calculable probabilities
Statistical Sampling(Probability Sampling)
SystematicStratified ClusterSimple Random
8/11/2019 statistika bisnis chapter 1
19/29
Simple Random Sampling
Every possible sample of a given sizehas an equal chance of being selected
Selection may be with replacement orwithout replacement
The sample can be obtained using a
table of random numbers or computerrandom number generator
8/11/2019 statistika bisnis chapter 1
20/29
Stratified Random Sampling
Divide population into subgroups (called strata)according to some common characteristic
e.g., gender, income level
Select a simple random sample from each subgroup
Combine samples from subgroups into one
Population
Divided
into 4
strata
Sample
8/11/2019 statistika bisnis chapter 1
21/29
Decide on sample size: n
Divide ordered (e.g., alphabetical) frame of Nindividuals into groups of k individuals: k=N/n
Randomly select one individual from the 1st group Select every kth individual thereafter
Systematic Random Sampling
N = 64
n = 8
k = 8First Group
8/11/2019 statistika bisnis chapter 1
22/29
Cluster Sampling
Divide population into several clusters,each representative of the population (e.g.,county)
Select a simple random sample of clusters All items in the selected clusters can be used, or items can
be chosen from a cluster using another probability samplingtechnique
Population divided
into 16 clusters.
Randomly selected
clusters for sample
8/11/2019 statistika bisnis chapter 1
23/29
Data Types
Data
Qualitative
(Categorical)
Quantitative
(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)
8/11/2019 statistika bisnis chapter 1
24/29
Data Types
Time Series Data Ordered data values observed over
time
Cross Sectional Data Data values observed at a single point in
time
8/11/2019 statistika bisnis chapter 1
25/29
Data Types
Sales (in $1000s)
2009 2010 2011 2012
Atlanta 435 460 475 490Boston 320 345 375 395
Cleveland 405 390 410 395
Denver 260 270 285 280
TimeSeriesData
Cross SectionalData
8/11/2019 statistika bisnis chapter 1
26/29
Data Measurement Levels
Ratio/Interval Data
Ordinal Data
Nominal Data
Highest Level
Complete Analysis
Higher Level
Mid-level Analysis
Lowest Level
Basic Analysis
Categorical Codese.g., ID Numbers, gender
RankingsOrdered Categoriese.g., age range 25-34
Measurementse.g., temperature
8/11/2019 statistika bisnis chapter 1
27/29
Steps to Categorizing Data
1. Identify each factor in the data set2. Determine if the data are time-series
or cross-sectional3. Determine which factors are
quantitative and which are qualitative
4. Determine the level of datameasurement
e.g., nominal, ordinal
8/11/2019 statistika bisnis chapter 1
28/29
Chapter Summary
Reviewed key data collection methods
Introduced key definitions:Population vs. Sample Primary vs. Secondary data types
Qualitative vs. Quantitative data Time Series vs. Cross-Sectionaldata
Examined descriptive vs. inferential
procedures Described different sampling techniques
Reviewed data types and measurement levels
8/11/2019 statistika bisnis chapter 1
29/29
THANK YOU.
END OF TOPIC