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### chap01

Course: BUS 90, Spring 2009
School: San Jose State
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for Statistics Managers Using Microsoft Excel 4th Edition Chapter 1 Introduction and Data Collection Statistics for Managers Using Microsoft Excel, 4e 2004 Prentice-Hall, Inc. Chap 1-1 Chapter Goals After completing this chapter, you should be able to: Explain key definitions: Population vs. Sample Parameter vs. Statistic Primary vs. Secondary Data Descriptive vs. Inferential Statistics Describe key...

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for Statistics Managers Using Microsoft Excel 4th Edition Chapter 1 Introduction and Data Collection Statistics for Managers Using Microsoft Excel, 4e 2004 Prentice-Hall, Inc. Chap 1-1 Chapter Goals After completing this chapter, you should be able to: Explain key definitions: Population vs. Sample Parameter vs. Statistic Primary vs. Secondary Data Descriptive vs. Inferential Statistics Describe key data collection methods Describe different sampling methods Probability Samples vs. Nonprobability Samples Select a random sample using a random numbers table Identify types of data and levels of measurement Describe the different types of survey error Chap 1-2 Statistics for Managers Using Microsoft Excel, 4e 2004 Prentice-Hall, Inc. Why a Manager Needs to Know about Statistics To know how to: properly present information draw conclusions about populations based on sample information improve processes obtain reliable forecasts Statistics for Managers Using Microsoft Excel, 4e 2004 Prentice-Hall, Inc. Chap 1-3 Key Definitions A population (universe) is the collection of all items or things under consideration A sample is a portion of the population selected for analysis A parameter is a summary measure that describes a characteristic of the population A statistic is a summary measure computed from a sample to describe a characteristic of the population Chap 1-4 Statistics for Managers Using Microsoft Excel, 4e 2004 Prentice-Hall, Inc. Population vs. Sample Population a b cd Sample b gi o r y Measures computed from sample data are called statistics Chap 1-5 c n u ef gh i jk l m n o p q rs t u v w x y z Measures used to describe the population are called parameters Statistics for Managers Using Microsoft Excel, 4e 2004 Prentice-Hall, Inc. Two Branches of Statistics Descriptive statistics Collecting, summarizing, and describing data Drawing conclusions and/or making decisions concerning a population based only on sample data Inferential statistics Statistics for Managers Using Microsoft Excel, 4e 2004 Prentice-Hall, Inc. Chap 1-6 Descriptive Statistics Collect data e.g., Survey Present data e.g., Tables and graphs Characterize data e.g., Sample mean = X n i Statistics for Managers Using Microsoft Excel, 4e 2004 Prentice-Hall, Inc. Chap 1-7 Inferential Statistics Estimation e.g., Estimate the population mean weight using the sample mean weight e.g., Test the claim that the population mean weight is 120 pounds Hypothesis testing Drawing conclusions and/or making decisions concerning a population based on sample results. Statistics for Managers Using Microsoft Excel, 4e 2004 Prentice-Hall, Inc. Chap 1-8 Why We Need Data To provide input to survey To provide input to study To measure performance of service or production process To evaluate conformance to standards To assist in formulating alternative courses of action To satisfy curiosity Chap 1-9 Statistics for Managers Using Microsoft Excel, 4e 2004 Prentice-Hall, Inc. Data Sources Primary Data Collection Secondary Data Compilation Print or Electronic Observation Survey Experimentation Statistics for Managers Using Microsoft Excel, 4e 2004 Prentice-Hall, Inc. Chap 1-10 Reasons for Drawing a Sample Less time consuming than a census Less costly to administer than a census Less cumbersome and more practical to administer than a census of the targeted population Statistics for Managers Using Microsoft Excel, 4e 2004 Prentice-Hall, Inc. Chap 1-11 Types of Samples Used Nonprobability Sample Items included are chosen without regard to their probability of occurrence Probability Sample Items in the sample are chosen on the basis of known probabilities Statistics for Managers Using Microsoft Excel, 4e 2004 Prentice-Hall, Inc. Chap 1-12 Types of Samples Used (continued) Samples Non-Probability Samples Probability Samples Judgement Quota Chunk Convenience Simple Random Stratified Cluster Systematic Statistics for Managers Using Microsoft Excel, 4e 2004 Prentice-Hall, Inc. Chap 1-13 Probability Sampling Items in the sample are chosen based on known probabilities Probability Samples Simple Random Systematic Stratified Cluster Statistics for Managers Using Microsoft Excel, 4e 2004 Prentice-Hall, Inc. Chap 1-14 Simple Random Samples Every individual or item from frame the has an equal chance of being selected Selection may be with replacement or without replacement Samples obtained from table of random numbers or computer random number generators Statistics for Managers Using Microsoft Excel, 4e 2004 Prentice-Hall, Inc. Chap 1-15 Systematic Samples 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 N = 64 n=8 k=8 First Group Statistics for Managers Using Microsoft Excel, 4e 2004 Prentice-Hall, Inc. Chap 1-16 Stratified Samples Divide population into two or more subgroups (called strata) according to some common characteristic A simple random sample is selected from each subgroup, with sample sizes proportional to strata sizes Samples from subgroups are combined into one Population Divided into 4 strata Sample Statistics for Managers Using Microsoft Excel, 4e 2004 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 Chap 1-18 Statistics for Managers Using Microsoft Excel, 4e 2004 Prentice-Hall, Inc. Advantages and Disadvantages Simple random sample and systematic sample Simple to use May not be a good representation of the populations underlying characteristics Ensures representation of individuals across the entire population More cost effective Less efficient (need larger sample to acquire the same level of precision) Chap 1-19 Stratified sample Cluster sample Statistics for Managers Using Microsoft Excel, 4e 2004 Prentice-Hall, Inc. Types of Data Data Categorical Examples: Numerical Marital Status Political Party Eye Color (Defined categories) Discrete Examples: Continuous Examples: Number of Children Defects per hour (Counted items) Weight Voltage (Measured characteristics) Chap 1-20 Statistics for Managers Using Microsoft Excel, 4e 2004 Prentice-Hall, Inc. Levels of Measurement and Measurement Scales Differences between measurements, true zero exists Differences between measurements but no true zero Ratio Data Interval Data Ordinal Data Highest Level Strongest forms of measurement Ordered Categories (rankings, order, or scaling) Higher Level Categories (no ordering or direction) Nominal Data Lowest Level Weakest form of measurement ...

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