Related Experiment Video
Updated: Apr 29, 2026

12:44
Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
7.7K
Are all data created equal?--Exploring some boundary conditions for a lazy intuitive statistician
Marcus Lindskog1, Anders Winman1
1Department of Psychology, Uppsala University, Uppsala, Sweden.
Plos One
|May 20, 2014
Summary
Presentation order of numeric data does not affect judgments of descriptive statistics. Participants remained responsive to data properties, showing immunity to order effects, supporting random sampling memory models.
Area of Science:
- Cognitive Psychology
- Decision Making
- Memory Research
Background:
- The naïve sampling model posits independence between data's temporal encoding and memory retrieval.
- This model implies random sampling from long-term memory for judgments.
- Investigating presentation order effects on statistical judgments is crucial for understanding memory retrieval.
Purpose of the Study:
- To examine how the order of numeric information presentation influences retrospective judgments of descriptive statistics.
- To test the assumptions of the naïve sampling model regarding memory retrieval and order independence.
- To assess the impact of repeated judgments on accuracy and potential anchoring effects.
Main Methods:
- Experiment 1: Participants judged descriptive statistics (mean, variability, shape) of number sequences with varying orders.
- Experiment 2: Employed a repeated judgment procedure with a mid-sequence change in data distribution.
- Utilized Arabic numerals and focused on retrospective subjective judgments.
Main Results:
- Neither experiment revealed significant effects of presentation order on judgments of mean, variability, or distribution shape.
- Experiment 2 confirmed that explicit judgments did not impair subsequent accuracy, refuting anchoring and insufficient adjustment.
- Participants demonstrated high responsiveness to data properties, yet were largely unaffected by presentation order.
Conclusions:
- Results align with naïve sampling models, suggesting data are stored as exemplars and randomly sampled from memory.
- Order effects in retrospective statistical judgments appear minimal, even with explicit judgment tasks.
- Cognitive processes involved in statistical judgment are robust to presentation sequence variations.
Related Concept Videos
Central Limit Theorem
17.7K
The central limit theorem, abbreviated as clt, is one of the most powerful and useful ideas in all of statistics. The central limit theorem for sample means says that if you repeatedly draw samples of a given size and calculate their means, and create a histogram of those means, then the resulting histogram will tend to have an approximate normal bell shape. In other words, as sample sizes increase, the distribution of means follows the normal distribution more closely.
The sample size, n, that...
The sample size, n, that...
17.7K
Interpretation of Confidence Intervals
8.8K
A confidence interval is a better estimate of the population than a point estimate, as it uses a range of values from a sample instead of a single value.
Confidence intervals have confidence coefficients that are crucial for their interpretation. The most common confidence coefficients are 0.90, 0.95, and 0.99, which can be written as percentages–90%, 95%, and 99%, respectively.
Suppose a person calculates a confidence interval with a confidence coefficient of 0.95. In that case, they can...
Confidence intervals have confidence coefficients that are crucial for their interpretation. The most common confidence coefficients are 0.90, 0.95, and 0.99, which can be written as percentages–90%, 95%, and 99%, respectively.
Suppose a person calculates a confidence interval with a confidence coefficient of 0.95. In that case, they can...
8.8K
Introduction to Statistics
45.5K
The science of statistics involves collecting, analyzing, interpreting, and presenting data. The method of collecting, organizing, and summarizing data is called descriptive statistics. The systematic method of drawing inferences from the sample data and predicting unknown characteristics of a population is called inferential statistics.
In statistics, the collection of individuals or objects under study is called population. The idea of sampling is to select a portion of the larger population...
In statistics, the collection of individuals or objects under study is called population. The idea of sampling is to select a portion of the larger population...
45.5K
Introduction to Nonparametric Statistics
1.6K
Nonparametric statistics offer a powerful alternative to traditional parametric methods, useful when assumptions about the population distribution cannot be made. Unlike parametric tests, which require data to follow a specific distribution with well-defined parameters (such as the mean and standard deviation), nonparametric tests do not require such constraints. This makes them particularly valuable when dealing with small sample sizes, skewed data, or ordinal and categorical variables.
One of...
One of...
1.6K
Probability in Statistics
18.6K
Probability is the likelihood of an event occurring. The term event is defined as a collection of results of a procedure. An event is a simple event when an outcome cannot be divided into simpler parts.
An example of a simple event is a coin toss. The result of a coin toss is either a head or a tail. Here, head and tail are two simple events. These two simple events make up the sample space. Further, the probability of an event occurring falls within the range of 0 to 1. The probability of an...
An example of a simple event is a coin toss. The result of a coin toss is either a head or a tail. Here, head and tail are two simple events. These two simple events make up the sample space. Further, the probability of an event occurring falls within the range of 0 to 1. The probability of an...
18.6K
The Squeeze Theorem
453
Certain mathematical functions exhibit unpredictable or highly variable behavior near specific input values, making direct evaluation of their limits challenging. This complexity may arise from rapid oscillations or irregular patterns that obscure the function’s trend. In such cases, the Squeeze Theorem offers a reliable method for determining limits.According to the Squeeze Theorem, if a function is confined between two other functions near a particular point, and both outer functions...
453

