CHAPTER 4 Data collection and sampling methods to accompany Introduction to business statistics fourth edition by ronald M. Weiers Presentation by Priscilla Chaffe-Stengel Donald N. stengel o 2002 The Wadsworth Group
CHAPTER 4: Data Collection and Sampling Methods to accompany Introduction to Business Statistics fourth edition, by Ronald M. Weiers Presentation by Priscilla Chaffe-Stengel Donald N. Stengel © 2002 The Wadsworth Group
Chapter 4-Learning objectives Describe the types of studies and the eir purposes Exploratory Descriptive Causal Predictive Explain the differences between data sources Primar Secondary: Internal versus external Differentiate between sampling designs Probabilitistic versus nonprobabilitistic designs Differentiate between sampling and nonsampling errors o 2002 The Wadsworth Group
Chapter 4 - Learning Objectives • Describe the types of studies and their purposes: – Exploratory – Descriptive – Causal – Predictive • Explain the differences between data sources: – Primary – Secondary: Internal versus External • Differentiate between sampling designs: – Probabilitistic versus nonprobabilitistic designs • Differentiate between sampling and nonsampling errors. © 2002 The Wadsworth Group
ll Chapter 4- Key terms error Probability sample Sampling Simple random sample Nonsampling Sⅴ stematic sample ° Types of Studies Stratified sample Exploratory Cluster sample Descriptive Causal Nonprobability sample Predictive Convenience sample ypes of Data Quota sample P Purposive sample rimar Secondary Judgment sample > Internals external o 2002 The Wadsworth Group
Chapter 4 - Key Terms • Error – Sampling – Nonsampling • Types of Studies – Exploratory – Descriptive – Causal – Predictive • Types of Data – Primary – Secondary »Internal vs External • Probability sample – Simple random sample – Systematic sample – Stratified sample – Cluster sample • Nonprobability sample – Convenience sample – Quota sample – Purposive sample – Judgment sample © 2002 The Wadsworth Group
l Types of studies Exploratory Understand a problem, identify relevant variables formulate hypotheses Descriptive Establish reliable measurements Causal Determine relationships among variables PredictiⅤe Use analysis to forecast o 2002 The Wadsworth Group
Types of Studies • Exploratory – Understand a problem, identify relevant variables, formulate hypotheses • Descriptive – Establish reliable measurements • Causal – Determine relationships among variables • Predictive – Use analysis to forecast © 2002 The Wadsworth Group
l Sources of data ° Primary Data generated by the researcher for this study Survey experimental, observational research most popular Tend to require more time and expense than secondary data condar Data gathered from another source or for another urpose > Internal sources within the researchers organization External sources, including governmental, trade, commercial and internet sources o 2002 The Wadsworth group
Sources of Data • Primary – Data generated by the researcher for this study – Survey, experimental, observational research most popular – Tend to require more time and expense than secondary data • Secondary – Data gathered from another source or for another purpose »Internal sources within the researcher’s organization »External sources, including governmental, trade, commercial and internet sources © 2002 The Wadsworth Group
l Types and Sources of error Sampling error Random nondirectional When a sample is used instead of a census Nonsampling error Directional bias overstating or understating the true population parameter Potential sources > Poor sample design > Poor measurement > Poor instrumentation o 2002 The Wadsworth Group
Types and Sources of Error • Sampling Error – Random, nondirectional – When a sample is used instead of a census • Nonsampling Error – Directional bias overstating or understating the true population parameter – Potential sources: »Poor sample design »Poor measurement »Poor instrumentation © 2002 The Wadsworth Group
Im Types of samples Probability, or Scientific, Samples: Each element to be sampled has a known( or calculable) chance of being selected Simple random Every person has an equal chance of being selected Best when roster of the population exists Systematic Randomly enter a stream of elements and sample ever kth element, Best when elements are randomly ordered, no cyclic variation o 2002 The Wadsworth Group
Types of Samples • Simple random • Systematic • Every person has an equal chance of being selected. Best when roster of the population exists. • Randomly enter a stream of elements and sample every kth element. Best when elements are randomly ordered, no cyclic variation. Probability, or Scientific, Samples: Each element to be sampled has a known (or calculable) chance of being selected. © 2002 The Wadsworth Group
Im Types of samples Probability, or Scientific, Samples: Each element to be sampled has a known( or calculable) chance of being selected ● Stratified Randomly sample elements from every layer, or stratum, of the population Best when elements within strata are homogeneous Cluster Randomly sample elements within some of the strata Best when elements within strata are heterogeneous o 2002 The Wadsworth Group
Types of Samples • Stratified • Cluster • Randomly sample elements from every layer, or stratum, of the population. Best when elements within strata are homogeneous. • Randomly sample elements within some of the strata. Best when elements within strata are heterogeneous. Probability, or Scientific, Samples: Each element to be sampled has a known (or calculable) chance of being selected. © 2002 The Wadsworth Group
Im Types of samples Nonprobability Samples: not every element has a chance to be sampled Selection process usually involves subjectivity Convenience Elements are sampled because of ease and availabilit Quota Elements are sampled, but not randomly, from every layer, or stratum, of the population o 2002 The Wadsworth Group
Types of Samples • Convenience • Quota • Elements are sampled because of ease and availability. • Elements are sampled, but not randomly, from every layer, or stratum, of the population. Nonprobability Samples: Not every element has a chance to be sampled. Selection process usually involves subjectivity. © 2002 The Wadsworth Group
Im Types of samples Nonprobability samples: not every element has a chance to be sampled Selection process usually involves subjectivity Purposive Elements are sampled because they are atypical not representative of the population Judgment Elements are sampled because the e researcher believes the members are representative of the po opulation o 2002 The Wadsworth Group
Types of Samples • Purposive • Judgment • Elements are sampled because they are atypical, not representative of the population. • Elements are sampled because the researcher believes the members are representative of the population. Nonprobability Samples: Not every element has a chance to be sampled. Selection process usually involves subjectivity. © 2002 The Wadsworth Group