--- url: "https://questionstar.com/principles-of-survey-research/chapter-4/" title: "Chapter 4: Sampling" type: "lehrbuch-chapter" chapter: 4 chapterTitle: "Sampling" --- # Chapter 4: Sampling *37 slides (117–153) · Principles of Survey Research.* ## Slides - [Slide 117: Sampling](slide-117.html.md) — 4.1 Non-probability Sampling · 4.2 Probability Sampling · 4.3 Choosing Non-probability vs. Probability Sampling · 4.4 Sample Size - [Slide 118: Dewey Defeats Truman](slide-118.html.md) — 1948: The Chicago Daily Tribune announces the wrong election result. President Harry Truman beats Thomas Dewey — against all polls. Reason: a biased… - [Slide 119: Sampling](slide-119.html.md) — Most surveys cannot survey every person. Instead, a sample is drawn and examined — this procedure is called sampling. - [Slide 120: Sampling](slide-120.html.md) — But not everyone selected actually answers: those who really take part are the respondents. - [Slide 121: Sampling: Two General Methods](slide-121.html.md) — The sample is drawn based on the personal judgment of the researcher — often at random (convenience sample, e.g. passersby in a shopping mall). - [Slide 122: Sampling Techniques](slide-122.html.md) — Overview of Techniques - [Slide 123: Sampling](slide-123.html.md) — 4.1 Non-probability Sampling · 4.2 Probability Sampling · 4.3 Choosing Non-probability vs. Probability Sampling · 4.4 Sample Size - [Slide 124: Convenience Sampling](slide-124.html.md) — In convenience sampling (selection at random), respondents enter the sample uncontrolled — mostly out of convenience. Often simply because they are in… - [Slide 125: Judgmental Sampling](slide-125.html.md) — Judgmental sampling is a form of convenience sampling in which respondents enter the sample at the discretion of the researcher.. - [Slide 126: Quota Sampling](slide-126.html.md) — The sample is drawn according to predefined control characteristics (e.g. gender, age, income), so that it reflects the structure of the population… - [Slide 127: Snowball Sampling also chain sampling](slide-127.html.md) — Technique 4 - [Slide 128: Sampling](slide-128.html.md) — 4.1 Non-probability Sampling · 4.2 Probability Sampling · 4.3 Choosing Non-probability vs. Probability Sampling · 4.4 Sample Size - [Slide 129: Sampling Techniques](slide-129.html.md) — Focus - [Slide 130: Simple and Systematic Random Sampling](slide-130.html.md) — Requires knowledge of the population - [Slide 131: Stratified Sampling](slide-131.html.md) — The population is first divided into non-overlapping strata. Then a (dis-)proportional share is drawn at random from each stratum. Elements within a… - [Slide 132: Cluster Samplingalso called cluster sampling](slide-132.html.md) — The population is divided into exclusive clusters. Then entire clusters are selected at random and enter the sample in full. - [Slide 133: Sampling](slide-133.html.md) — 4.1 Non-probability Sampling · 4.2 Probability Sampling · 4.3 Choosing Non-probability vs. Probability Sampling · 4.4 Sample Size - [Slide 134: Strengths and Weaknesses of Basic Sampling Techniques](slide-134.html.md) — Comparison of all techniques - [Slide 135: Sampling](slide-135.html.md) — 4.1 Non-probability Sampling · 4.2 Probability Sampling · 4.3 Choosing Non-probability vs. Probability Sampling · 4.4 Sample Size - [Slide 136: Determining the Sample Size](slide-136.html.md) — The sample size does not depend on the size of the population — it is determined by the qualitative aspects of the study: - [Slide 137: Sample Sizes Used in Marketing Research Studies](slide-137.html.md) — Rules of thumb from practice - [Slide 138: A survey result — and how certain is it?](slide-138.html.md) — name social media as their main information channel. - [Slide 139: Margin of Error Approach to Determining Sample Size](slide-139.html.md) — Margin of error is the measure of a survey's precision. - [Slide 140: Margin of error approach: two formulas](slide-140.html.md) — Calculating the margin of error - [Slide 141: Margin of Error Approach: Two Formulas](slide-141.html.md) — The Problem of Unknown Dispersion - [Slide 142: Margin of Error Approach: Two Formulas](slide-142.html.md) — Worst-Case Assumption π = 0.5 - [Slide 143: z-Values and Maximum Margin of Error](slide-143.html.md) — With z = 1.96 and the maximum π = 0.5 the formula simplifies to: - [Slide 144: What Is the Margin of Error?](slide-144.html.md) — "Which sources do you prefer to get your information from?" - [Slide 145: How Large Must the Sample Be?](slide-145.html.md) — The higher the desired accuracy, the larger the sample must be. - [Slide 146: What If the Population Is Small?](slide-146.html.md) — If the sample is larger than 10% of the population, corrections are necessary. - [Slide 147: Correcting the Sample Size](slide-147.html.md) — Computationally you would need n = 10,000 — with only 100 elements in the population: - [Slide 148: Correction for a small population: ± 1 %](slide-148.html.md) — Calculations show approximate values for a 95% confidence level - [Slide 149: Correction for a small population: ± 5 %](slide-149.html.md) — Calculations show approximate values for a 95% confidence level - [Slide 150: Correction for a small population: ± 10 %](slide-150.html.md) — Calculations show approximate values for a 95% confidence level - [Slide 151: Confidence Interval and Confidence Level](slide-151.html.md) — An estimated range of values together with the probability that this range contains the unknown parameter value. - [Slide 152: Confidence Interval, Margin of Error, and Sample Size](slide-152.html.md) — The higher the certainty (confidence probability) we need, the wider the confidence interval becomes — and the larger the margin of error. - [Slide 153: What the Margin of Error Formula Tells Us](slide-153.html.md) — The only lever to lower the margin of error is a larger n — everything else is fixed. --- *Part of [Principles of Survey Research](../index.md) · Dr. Paul Marx*