Making statistics intuitive
Concurrent validity is the degree to which assessment scores correlate with a criterion variable when researchers measure both variables at approximately the same time (i.e., concurrently). This method validates an assessment instrument by comparing its scores to another test or variable that researchers had validated previously. [Read more…] about Concurrent Validity: Definition, Assessing & Examples
Criterion validity (aka criterion related validity) is the degree to which scores from a construct assessment correlate with a manifestation of that construct in the real world (the criterion). [Read more…] about Criterion Validity: Definition, Assessing & Examples
Predictive validity is the degree to which a test score or construct scale predicts a criterion variable measuring a future outcome, behavior, or performance. Evaluating predictive validity involves assessing the correlation between the pre-test score and the subsequent criterion outcome. [Read more…] about Predictive Validity: Definition, Assessing & Examples
A retrospective study looks back in time and assesses events that have already occurred. The researchers already know the outcome for each subject when the project starts. Instead of recording data going forward as events happen, these studies use participant recollection and data that were previously recorded for reasons not relating to the project. These studies typically don’t follow patients into the future. [Read more…] about Retrospective Study: Definition & Examples
Political polls provide crucial information during elections. When done correctly, small samples can predict the outcomes. We’re approaching election time here in the U.S., and campaigns are switching into high gear along with political polls!
You’d think that conducting a poll is straightforward. You ask a bunch of people who they’ll vote for and count the results, right? But it’s not quite that simple.
For starters, political polls face the same challenges as other polls. However, a poll taken for political reasons also has some unique issues. When pollsters do everything correctly, the small, sampled group accurately reflects the entire population. The trick is to do it correctly!
In this post, learn how statistical concepts apply to political polls and the extra difficulties they face. [Read more…] about Political Polls and Their Challenges
Survivorship bias, or survivor bias, occurs when you tend to assess successful outcomes and disregard failures. This sampling bias paints a rosier picture of reality than is warranted by skewing the mean results upward. [Read more…] about Survivorship Bias: Definition, Examples & Avoiding
Sampling bias in statistics occurs when a sample does not accurately represent the characteristics of the population from which it was drawn. When this bias occurs, sample attributes are systematically different from the actual population values. Hence, sampling bias produces a distorted view of the population. Sampling bias often involves human subjects, but it can also apply to samples of objects and animals. Medical researchers refer to this problem as ascertainment bias. [Read more…] about Sampling Bias: Definition & Examples
Purposive sampling is a non-probability method for obtaining a sample where researchers use their expertise to choose specific participants that will help the study meet its goals. These subjects have particular characteristics that the researchers need to evaluate their research question. In other words, the researchers pick the participants “on purpose.” [Read more…] about Purposive Sampling: Definition & Examples
Snowball sampling is a non-probability method for acquiring a sample that uses participants to recruit additional participants. Researchers call it snowball sampling because if the initial participant recruits two more, and those two recruits each bring in two more, and so on, the number of participants can grow exponentially like a rolling snowball. This method is also known as chain sampling or network sampling. [Read more…] about Snowball Sampling: Definition and Example
Quota sampling is a non-random selection of subjects from population subgroups that the researchers define. Researchers use quota sampling when random sampling isn’t feasible, and they want more control over who they select compared to other non-probability methods, such as convenience sampling. [Read more…] about Quota Sampling: Definition & Examples
An experimental design is a detailed plan for collecting and using data to identify causal relationships. Through careful planning, the design of experiments allows your data collection efforts to have a reasonable chance of detecting effects and testing hypotheses that answer your research questions. [Read more…] about Experimental Design: Definition and Types
A representative sample is one where the individuals in the sample reflect the properties of an entire population. Use a representative sample when you want to generalize the results from the sample to a population. By studying a representative sample, you can approximate the properties of the population from which it was drawn. [Read more…] about Representative Sample: Definition, Uses & Methods
Sampling methods are the processes by which you draw a sample from a population. When performing research, you’re typically interested in the results for an entire population. Unfortunately, they are almost always too large to study fully. Consequently, researchers use samples to draw conclusions about a population—the process of making statistical inferences. [Read more…] about Sampling Methods: Different Types in Research
A cohort study is a longitudinal experimental design that follows a group of participants who share a defining characteristic. For example, a cohort study can select subjects who have exposure to a risk factor, are in the same profession, population or generation, or experience a particular event, such as a medical procedure. This design determines whether exposure to a risk factor affects an outcome. [Read more…] about Cohort Study: Definition, Benefits & Examples
A case control study is a retrospective, observational study that compares two existing groups. Researchers form these groups based on the existence of a condition in the case group and the lack of that condition in the control group. They evaluate the differences in the histories between these two groups looking for factors that might cause a disease. [Read more…] about Case Control Study: Definition, Benefits & Examples
Simple random sampling (SRS) is a probability sampling method where researchers randomly choose participants from a population. All population members have an equal probability of being selected. This method tends to produce representative, unbiased samples. [Read more…] about Simple Random Sampling: Definition & Examples
Convenience sampling is a non-probability sampling method where researchers use subjects who are easy to contact and obtain their participation. Researchers find participants in the most accessible places, and they impose no inclusion requirements. Convenience sampling is also known as opportunity or availability sampling. [Read more…] about Convenience Sampling: Definition & Examples
Systematic sampling is a probability sampling method for obtaining a representative sample from a population. To use this method, researchers start at a random point and then select subjects at regular intervals of every nth member of the population. Like other probability sampling methods, the researchers must identify their population of interest before sampling from it. [Read more…] about Systematic Sampling: Definition, Advantages & Examples
Validity in research, statistics, psychology, and testing evaluates how well test scores reflect what they’re supposed to measure. Does the instrument measure what it claims to measure? Do the measurements reflect the underlying reality? Or do they quantify something else? [Read more…] about Validity in Research and Psychology: Types & Examples
Internal and external validity relate to the findings of studies and experiments. [Read more…] about Internal and External Validity