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Chapter 1The Where, Why, and How of Data Collection : 

Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 1-1 Business Statistics: A Decision-Making Approach 6th Edition Chapter 1The Where, Why, and How of Data Collection

Chapter Goals : 

Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 1-2 Chapter Goals After completing this chapter, you should be able to: Describe key data collection methods Know key definitions: ?Population vs. Sample ?Primary vs. Secondary data types ?Qualitative vs. Qualitative data ?Time Series vs. Cross-Sectional data Explain the difference between descriptive and inferential statistics Describe different sampling methods

Tools of Business Statistics : 

Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 1-3 Descriptive statistics Collecting, presenting, and describing data Inferential statistics Drawing conclusions and/or making decisions concerning a population based only on sample data Tools of Business Statistics

Descriptive Statistics : 

Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 1-4 Descriptive Statistics Collect data e.g. Survey, Observation, Experiments Present data e.g. Charts and graphs Characterize data e.g. Sample mean =

Data Sources : 

Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 1-5 Data Sources Primary Data Collection Secondary Data Compilation Observation Experimentation Survey Print or Electronic

Survey Design Steps : 

Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 1-6 Survey Design Steps Define the issue what are the purpose and objectives of the survey? Define the population of interest Formulate survey questions make questions clear and unambiguous use universally-accepted definitions limit the number of questions

Survey Design Steps : 

Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 1-7 Survey Design Steps Pre-test the survey pilot test with a small group of participants assess clarity and length Determine the sample size and sampling method Select Sample and administer the survey (continued)

Types of Questions : 

Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 1-8 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

Populations and Samples : 

Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 1-9 A Population is the set of all items or individuals of interest Examples: All likely voters in the next election All parts produced today All 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 testing Every 100th receipt selected for audit Populations and Samples

Population vs. Sample : 

Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 1-10 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

Why Sample? : 

Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 1-11 Why Sample? Less time consuming than a census Less costly to administer than a census It is possible to obtain statistical results of a sufficiently high precision based on samples.

Sampling Techniques : 

Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 1-12 Sampling Techniques Convenience Samples Non-Probability Samples Judgement Probability Samples Simple Random Systematic Stratified Cluster

Statistical Sampling : 

Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 1-13 Statistical Sampling Items of the sample are chosen based on known or calculable probabilities Probability Samples Simple Random Systematic Stratified Cluster

Simple Random Samples : 

Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 1-14 Simple Random Samples Every individual or item from the population has an equal chance of being selected Selection may be with replacement or without replacement Samples can be obtained from a table of random numbers or computer random number generators

Stratified Samples : 

Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 1-15 Stratified Samples Population divided into subgroups (called strata) according to some common characteristic Simple random sample selected from each subgroup Samples from subgroups are combined into one Population Divided into 4 strata Sample

Systematic Samples : 

Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 1-16 Decide on sample size: n Divide frame of N individuals into groups of k individuals: k=N/n Randomly select one individual from the 1st group Select every kth individual thereafter Systematic Samples N = 64 n = 8 k = 8 First Group

Cluster Samples : 

Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 1-17 Cluster Samples Population is divided into several “clusters,” each representative of the population A simple random sample of clusters is selected All items in the selected clusters can be used, or items can be chosen from a cluster using another probability sampling technique Population divided into 16 clusters. Randomly selected clusters for sample

Key Definitions : 

Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 1-18 Key Definitions A population is the entire collection of things under consideration A parameter is a summary measure computed to describe a characteristic of the population A sample is a portion of the population selected for analysis A statistic is a summary measure computed to describe a characteristic of the sample

Inferential Statistics : 

Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 1-19 Making statements about a population by examining sample results Sample statistics Population parameters (known) Inference (unknown, but can be estimated from sample evidence) Inferential Statistics

Inferential Statistics : 

Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 1-20 Inferential Statistics Estimation e.g.: Estimate the population mean weight using the sample mean weight Hypothesis Testing e.g.: Use sample evidence to test the claim that the population mean weight is 120 pounds Drawing conclusions and/or making decisions concerning a population based on sample results.

Data Types : 

Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 1-21 Data Types Examples: Marital Status Political Party Eye Color (Defined categories) Examples: Number of Children Defects per hour (Counted items) Examples: Weight Voltage (Measured characteristics)

Data Types : 

Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 1-22 Data Types Time Series Data Ordered data values observed over time Cross Section Data Data values observed at a fixed point in time

Data Types : 

Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 1-23 Data Types Time Series Data Cross Section Data

Data Measurement Levels : 

Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Data Measurement Levels Ratio/Interval Data Ordinal Data Nominal Data Highest Level Complete Analysis Higher Level Mid-level Analysis Lowest Level Basic Analysis Categorical Codes ID Numbers Category Names Rankings Ordered Categories Measurements

Chapter Summary : 

Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 1-25 Chapter Summary Reviewed key data collection methods Introduced key definitions: ?Population vs. Sample ?Primary vs. Secondary data types ?Qualitative vs. Qualitative data ?Time Series vs. Cross-Sectional data Examined descriptive vs. inferential statistics Described different sampling techniques Reviewed data types and measurement levels

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