sampling plan

Learning Objectives

1. Understand the concept and procedure of sampling.

2. List the primary types of sampling techniques: Non-probability vs Probability.

3. Determine the sample size required for research.

Sampling Procedure Steps

1. Define the Target Population.

2. Identify the Sampling Frame.

3. Select a Sampling Procedure.

4. Determine the Sample Size.

5. Select the Sample Elements.

6. Collect the Data from the Designated Elements.

Target Population Definition

• Definition: A population (N) includes all cases that meet specified criteria for membership.

• Example: Households in Sacramento, CA with one or more children under 18.

Population Parameters

Parameter vs. Statistics

• Parameter: Characteristic of the entire population, determinable through a census.

• Statistics: Measure calculated from sample data to estimate population parameters.

Identifying the Sampling Frame

• Sampling Frame: List of population elements from which sample (n) is drawn.

• Common sampling frames include:

  • Customer databases

  • Telephone directories

  • Lists from data compilers.

Choosing a Sampling Procedure

Types of Samples

• Nonprobability Samples:

  • Convenience Sample

  • Quota Sample

  • Judgment Sample

• Probability Samples:

  • Simple Random Sample

  • Stratified Sample

  • Systematic Sample

Nonprobability Sampling Definition

• Nonprobability Sample: Depends on researcher’s judgment; some individuals may have no chance of selection.

• Cannot estimate sampling error.

• Techniques include:

  1. Convenience

  2. Quota

  3. Judgment (e.g., Snowball)

• Probability Sample: Each element has a known chance of selection; sampling error can be assessed.

Convenience Sampling Example

• Example of Convenience Sampling:

  • Target population: W.P. Carey School of Business students.

  • Sampling Location: BAC building first floor hallway, collecting data from students between 9:00 am and 11:00 am.

Quota Sampling Explanation

• Quota Sample: Ensures proportions of characteristics match those in the target population.

• Example Scenario: Investigating undergraduate students’ attitudes towards a new technology fee based on class and gender distribution.

Class and Gender Quota Sample Idea

• Details on how to set up quotas for the sample based on class and gender:

  • 30 Freshmen, 15 Freshman Females, etc.

Simple Random Sampling Process

• Simple Random Sample: Each population element has an equal probability of selection.

• Steps to execute:

  1. Select sampling frame.

  2. Assign numbers to elements.

  3. Generate random numbers for sample selection.

Simple Random Sampling Example Tables

• Example tables illustrating how to set up sampling selection for simple random sampling.

In-class Assignment Instructions

• Implementation of simple random sampling using Excel functions.

Stratified Sampling Explanation

• Stratified Sample: Population is divided into subsets; simple random samples are taken from each.

• Example case: Feedback on exam preferences from male and female students in a marketing research class.

Stratified Sampling Setup Tables

• Layout sample tables for stratified sampling by gender and class.

In-class Assignment for Stratified Sample

• Instructions for carrying out stratified sampling in a class setting using Excel functions.

Nonprobability vs. Probability Sample

Nonprobability Sample

• Cannot estimate sampling error; results not generalizable.

Probability Sample

• Allows statistical assessment of sampling error; results generalizable to the population.

Sample Size Determination

Key Factors Affecting Sample Size

1. Amount of Diversity/Variation.

2. Degree of Precision.

3. Degree of Confidence.

• Formula used for sample size determination in simple random sampling: [ n = \frac{z^2 \cdot \sigma^2}{D^2} ]

Exercises for Sample Size Calculation

• Exercises illustrating the calculations for determining sample sizes based on parameters such as standard deviation, error range, and confidence level.

Exercise 1 Example Calculation

• Given parameters for soda consumption survey, resulting sample size determined to be 97.

Exercise 2 Example Calculation

• Surveys on average age at ASU football games, determining required sample sizes for different confidence levels and error ranges.

Page 41: Final Sampling Procedure Steps

• Confirmation of steps for drawing a sample again highlighted.