Missing data refers to the absence of data entries in a dataset where values are expected but not recorded. They’re the blank cells in your data sheet. Missing values for specific variables or participants can occur for many reasons, including incomplete data entry, equipment failures, or lost files. When data are missing, it’s a problem. However, the issues go beyond merely reducing the sample size. In some cases, they can skew your results. [Read more…] about Missing Data Overview: Types, Implications & Handling

# Basics

## Data Aggregation: Strengths & Weaknesses of Aggregated Data

## What is Data Aggregation?

Data aggregation is a crucial process that involves collecting data and summarizing it in a concise form. This method transforms atomic data rows—sourced from diverse origins—into comprehensive totals or summary statistics. Aggregated data, typically housed in data warehouses, enhances analytical capabilities and significantly speeds up querying large datasets. [Read more…] about Data Aggregation: Strengths & Weaknesses of Aggregated Data

## Prospect Theory Overview & Examples

## What is Prospect Theory?

Prospect Theory states that individuals place greater weight on losses than gains while making decisions. It is a descriptive model of how individuals make decisions involving risk and uncertainty proposed by Daniel Kahneman and Amos Tversky in 1979. Prospect theory describes how people evaluate and choose between different options. [Read more…] about Prospect Theory Overview & Examples

## Gage R&R Overview & Example

## What is Gage R&R?

Gage R&R assesses the amount and sources of measurement variation in a measurement system. It evaluates a measurement system’s precision and helps you target improvement efforts where they’re most needed. It does not assess accuracy or bias. [Read more…] about Gage R&R Overview & Example

## Regression to the Mean: Definition & Examples

## What is Regression to the Mean?

Regression to the mean is the statistical tendency for an extreme sample or observed value to be followed by a more average one. It is also known as reverting to the mean, highlighting the propensity for a later observation to move closer to the mean after an extreme value. The concept applies only to random variation in a process or system and does not pertain to interventions or events that affect the outcome. [Read more…] about Regression to the Mean: Definition & Examples

## Self Selection Bias Overview & Examples

## What is Self Selection Bias?

Self selection bias can occur when individuals choose to participate in a study, survey, or experiment. The bias exists when volunteers have different characteristics than those who do not participate. It is a form of sampling bias stemming from using a nonprobability sampling method, such as volunteer or convenience sampling. [Read more…] about Self Selection Bias Overview & Examples

## Attrition Bias: Definition & Examples

## What is Attrition Bias?

Attrition bias in research occurs when study participants who drop out have characteristics that differ significantly from those who remain. This selective dropout can lead to skewed results and misinterpretations if the researchers don’t adequately address it. This threat is higher for longitudinal studies and those with relatively high attrition rates. [Read more…] about Attrition Bias: Definition & Examples

## Quasi Experimental Design Overview & Examples

## What is a Quasi Experimental Design?

A quasi experimental design is a method for identifying causal relationships that does not randomly assign participants to the experimental groups. Instead, researchers use a non-random process. For example, they might use an eligibility cutoff score or preexisting groups to determine who receives the treatment. [Read more…] about Quasi Experimental Design Overview & Examples

## Covariance vs Correlation: Understanding the Differences

Covariance vs correlation both evaluate the linear relationship between two continuous variables. While this description makes them sound similar, there are stark differences in how to interpret them.

Although these statistics are closely related, they are distinct concepts. How are they different?

In this post, learn about the differences between covariance vs correlation and what you can learn from each. [Read more…] about Covariance vs Correlation: Understanding the Differences

## What is a Case Study? Definition & Examples

## Case Study Definition

A case study is an in-depth investigation of a single person, group, event, or community. This research method involves intensively analyzing a subject to understand its complexity and context. The richness of a case study comes from its ability to capture detailed, qualitative data that can offer insights into a process or subject matter that other research methods might miss. [Read more…] about What is a Case Study? Definition & Examples

## Sample Mean vs Population Mean: Symbol & Formulas

In statistics, the symbols and formulas for basic concepts such as the mean provide a foundational understanding of data analysis. Understanding the mean involves more than just knowing how to calculate an average; it’s about recognizing the nuances that differentiate a population mean from a sample mean. This distinction is crucial in statistical analysis, as the approach and symbol used for each vary (mu vs. x bar). [Read more…] about Sample Mean vs Population Mean: Symbol & Formulas

## Correlational Study Overview & Examples

## What is a Correlational Study?

A correlational study is an experimental design that evaluates only the correlation between variables. The researchers record measurements but do not control or manipulate the variables. Correlational research is a form of observational study. [Read more…] about Correlational Study Overview & Examples

## Cross Sectional Study: Overview, Examples & Benefits

## What is a Cross Sectional Study?

A cross-sectional study is an experimental design that analyzes data from a representative sample at a specific point in time. Researchers usually evaluate multiple attributes at once when using this design. Unlike longitudinal studies, these studies don’t track changes over time. [Read more…] about Cross Sectional Study: Overview, Examples & Benefits

## Longitudinal Study: Overview, Examples & Benefits

## What is a Longitudinal Study?

A longitudinal study is an experimental design that takes repeated measurements of the same subjects over time. These studies can span years or even decades. Unlike cross-sectional studies, which analyze data at a single point, longitudinal studies track changes and developments, producing a more dynamic assessment. [Read more…] about Longitudinal Study: Overview, Examples & Benefits

## Correlation vs Causation: Understanding the Differences

Correlation vs causation in statistics is a critical distinction. And you’ve undoubtedly heard that correlation doesn’t imply causation. Why is that the case, what are the differences between them, and why do they matter? Those are the topics of this post! [Read more…] about Correlation vs Causation: Understanding the Differences

## Observational Study vs Experiment with Examples

## Comparing Observational Studies vs Experiments

Observational studies and experiments are two standard research methods for understanding the world. Both research designs collect data and use statistical analysis to understand relationships between variables. Beyond that commonality, they are vastly different and have dissimilar sets of pros and cons. [Read more…] about Observational Study vs Experiment with Examples

## Goodness of Fit: Definition & Tests

## What is Goodness of Fit?

Goodness of fit evaluates how well observed data align with the expected values from a statistical model. [Read more…] about Goodness of Fit: Definition & Tests

## Placebo Effect Overview: Definition & Examples

## What is the Placebo Effect?

The placebo effect occurs when a fake medical treatment produces real medical benefits psychosomatically. In short, believing in the treatment and the power of the mind can help someone feel better. The placebo effect can be so powerful that it mimics genuine medicine. Consequently, scientists need to control for it when conducting clinical trials. [Read more…] about Placebo Effect Overview: Definition & Examples

## Randomized Controlled Trial (RCT) Overview

## What is a Randomized Controlled Trial (RCT)?

A randomized controlled trial (RCT) is a prospective experimental design that randomly assigns participants to an experimental or control group. RCTs are the gold standard for establishing causal relationships and ruling out confounding variables and selection bias. Researchers must be able to control who receives the treatments and who are the controls to use this design. [Read more…] about Randomized Controlled Trial (RCT) Overview

## Prospective Study: Definition, Benefits & Examples

## What is a Prospective Study?

A prospective study is an experimental design that looks forward in time and observes events as they happen. Participants begin the study without having a condition of interest. Then researchers gather data and take measurements at regular intervals to identify the occurrence of specific outcomes along with other data that might relate to them. [Read more…] about Prospective Study: Definition, Benefits & Examples