Module 2: Statistical Terminology and Examples by

Variable

2023-11-20 01:55:00 UTC

Variable: Trait or characteristic that varies or changes. Variables may be qualitative or quantitative.

Lisa Moser

Quantitative Variables

2023-11-20 01:58:38 UTC

Variables that have values that are numeric. (Example: Systolic blood pressure of 120)

Lisa Moser

Qualitative Variables

2023-11-20 02:00:38 UTC

Variables that have values that are non-numeric. (Example: Systolic blood pressure can be low, normal, or high)

Lisa Moser

Random Error

lizbethmor22 — 2023-11-21 05:58:58 UTC

is the difference between the measured versus the true values of something, that can occur due to chance.

Lizbeth Moreno

Independent Variables

lizbethmor22 — 2023-11-21 06:01:16 UTC

It is a variable that stands alone, that is manipulated or controlled in a study to assess its effects.

Lizbeth Moreno

Levels of Measurement

lizbethmor22 — 2023-11-21 06:06:25 UTC

This includes the following levels: Nominal, Ordinal, Interval, or Ratio. It tells you how variables are recorded.

Lizbeth Moreno

Content validity

2023-11-26 16:04:36 UTC

The degree to which a measurement tool captures the elements of the concept of interest.

Danielle

Criterion-related validity

2023-11-26 16:06:06 UTC

The degree to which measurements from one tool or instrument may be correlated with measurements from other valid and reliable instruments.

Danielle

Construct validity

2023-11-26 16:10:25 UTC

The degree to which an instrument or tool measures the specific idea of interest.

Danielle

Content validity

dkbissell — 2023-11-27 05:09:35 UTC

The degree to which a measurement tool captures the elements of the concept of interest.

For example, when developing a final exam to assess a student's understanding of Biostatistics, the exam content would need to comprehensively cover all aspects of the course to be considered a valid measurement.

Danielle Bissell

Criterion-related validity

dkbissell — 2023-11-27 05:10:29 UTC

The degree to which measurements from one tool or instrument may be correlated with measurements from other valid and reliable instruments.

It's a relationship measure of how good a screening or test is at predicting a specific outcome. For example, how well the MCAT exam is at predicting the success of a student in med school.

Danielle Bissell

Construct validity

dkbissell — 2023-11-27 05:12:04 UTC

The degree to which an instrument or tool measures the specific idea of interest.

The test/survey/assessment is said to have construct validity if it accurately measures all aspects of whatever it is measuring rather than just components of it.

Danielle Bissell

Reliability

deannaehanna — 2023-11-28 03:18:51 UTC

Tells us weather or not a test or tool can consistently measure a variable.

Test–retest reliability

deannaehanna — 2023-11-28 03:20:25 UTC

Used to address the consistency of the measurement from one time to another. If the tool is reliable, the subjects' scores should be similar at different times of measurement.

systematic error

deannaehanna — 2023-11-28 03:21:36 UTC

systematic errors are errors that occur constantly because of known causes, and random errors occur by chance and are the result of unknown causes. One cause of systematic errors is the incorrect use of tools or instruments.

Random Error

2023-11-30 04:22:20 UTC

An error that occurs out of chance and has unknown causes. It is entirely unpredictable and inconsistent with how variable to results may be. Such can be seen through human and environmental factors within a given study.

Christian Bacong

Systematic Error

2023-11-30 04:22:37 UTC

An error that occurs consistently and predictably because of its known causes. Much of these errors occur from flaws in the experiment/ measurement process. It being predictable allows for improvements in accuracy and consistency in outcomes.

Christian Bacong

Reliability

2023-11-30 04:33:18 UTC

Within the realm of measurement or assessment, reliability refers to the consistency or stability of a given measurement tool. A measurement/ assessment tool is considered to be reliable the more consistently and reproducible the results are through repeat applications.

Christian Bacong

Construct validity

2024-06-12 22:50:22 UTC

how well a test measures the concept it was designed to evaluate.

patricia bamburg

External validity

2024-06-12 22:50:58 UTC

degree to which results can be generalized to other populations, settings, and times.

patricia bamburg

Random error

2024-06-12 22:51:33 UTC

is a chance difference between the observed and true values of something.

patricia bamburg

Ratio Level of Measurement

2024-06-17 21:43:00 UTC

The highest level of measurement and will include properties of lower levels for example(nominal, ordinal, and interval). It has a really meaningful zero point.

Candy Rubalcava

Interrater Reliability

2024-06-17 21:49:37 UTC

It is a measure of how similar two or more independent observers/raters score or how they categorize an item. It is all about consistency.

Candy Rubalcava

Quantitative Variables

2024-06-17 21:52:42 UTC

Variables that can be measured or counted.

Candy Rubalcava

Independent Variable

2024-06-18 22:04:25 UTC

An independent variable is a variable that is manipulated or changed in an experiment to observe its effect on another variable. Its value is determined by the researchers and is not influenced by the other variables in the study. In simpler terms, it's the like the "cause" and you are testing how it affects something else, the "effect."

Tamlyn Pinzon

Systematic Error

2024-06-18 22:08:58 UTC

Systematic error, also sometimes called bias, hides in the data in a way, sneaking in errors in a consistent way. Unlike random errors, which are usually all over the place, systematic errors always skew the results in the same direction, either overestimating or underestimating the true value. Because they're consistent, systematic errors can skew your entire dataset, making it hard to see the real picture.

Tamlyn Pinzon

Interrater Reliability

2024-06-18 22:13:19 UTC

Interrater reliability is about how much agreement there is between different raters, observers, or examiners. In simpler terms, it tells you how consistent people are in their evaluations. consistent ratings are crucial. If different raters give wildly different scores, it's hard to trust the data that was collected. Interrater reliability helps ensure the findings are meaningful because they're not necessarily dependent on who did the scoring.

Tamlyn Pinzon

Dependent Variables

2024-06-18 23:12:32 UTC

These are outcomes or responses that are measured in a study. It is what the researcher is trying to understand and explain based on various predictors.

Afoma Ogbuefi

Independent Variables

2024-06-18 23:22:30 UTC

These are factors that can be introduced, manipulated, and controlled by the researcher to affect or change the dependent variable. These outcomes are monitored and analyzed to make inferences.

Afoma Ogbuefi

Reliability

2024-06-18 23:55:29 UTC

This refers to the consistency of a test or measurement results. It is the percentage or probability of which a test repeated severally under the same conditions would give the same results. The higher the reliability, the more valid it is.

Afoma Ogbuefi

Measurement Error

2024-06-19 01:36:09 UTC

The difference between the actual value of something being measured and the observed value, or the result of the measurement.

Example: You measure the length of a table as 100 cm, but its actual length is 98 cm. The difference of 2 cm is the measurement error.

Rachel Harris

Test-Retest Reliability

2024-06-19 01:39:38 UTC

This is a measure of consistency used to assess the reliability of a test or measurement. It involves administering the same test to the same group of people at two different points in time and then comparing the results to see if they are consistent.

Rachel Harris

Systematic Error

2024-06-19 01:48:46 UTC

Consistent repetition of the same mistake or error in multiple experiments or observations

Example: you have a scale that always adds 2 pounds to your weight. Every time you step on it, it shows your weight as 2 pounds more than you actually weigh.

Rachel Harris

Systematic Error: Michel Demma

2024-06-19 02:49:02 UTC

Michel Demma: Persistent inaccuracy or bias that is present in every measurement is referred to as systematic error. It is the opposite of random error, which varies from trial to trial and tends to average out. Identifying and correcting systematic errors is crucial for ensuring the accuracy and precision of scientific results.

Content validity: Michel Demma

2024-06-19 02:53:05 UTC

Michel Demma: How well a test or assessment represents the content it should look like is called "content validity." Did the test capture everything it was designed to capture? Was anything left out? On a test aimed at diagnosing thyroid problems, for instance, would it be reasonable to ask questions about what a litmus test is? No. Then not putting any thyroid-related questions on that same test also wouldn't make any sense. A test has content validity when it passes this kind of common sense check. And that's what the instrument in our study appeared to do.

Test–retest reliability: Michel Demma

2024-06-19 02:56:49 UTC

Michel Demma: Reliability is vital when it comes to the performance of a test or assessment. It is the measure of how consistent a tool is in producing the same results when the same individuals take it on two or more different occasions. A high test-retest reliability measure is one that says, 'Don't worry; the results you see today are almost certainly the results you'll see next week, next month, or even next year.' A low test-retest reliability measure, on the other hand, says, 'Hmm. When the same people take this test again, we certainly don't see the same thing we saw the first time.' For a mental health assessment tool to be trustworthy, it, of course, needs to have a high test-retest reliability measure. After all, a mental health condition isn't something that should change much in weeks, months, or years.

LEVEL OF MEASURMENT

2024-06-19 04:42:57 UTC

variables can be quantified and categorized. They include four primary levels: nominal, ordinal, interval, and ratio scales. For each of these they feature different data and how it is recorded. Veronica Magana

DATA SET

2024-06-19 04:50:15 UTC

is a collection about data points or values that are organized or in structured format. Each data set has a data point which represents specific measurements or observation. It is used for analysis.

Veronica Magana

EXTERNAL VALIDITY

2024-06-19 04:54:35 UTC

examines the ability to apply its findings to other settings, populations, times, and measures. Research with high external validity is applicable to real-world scenarios and diverse groups. It is considered in research to confirm the conclusions from a study were not limited to specific sample or context.

Confounding Variables:

2024-06-19 16:58:00 UTC

A factor othe than the one being studied that is associated with both the dependent variable and independent variable

Content validity:

2024-06-19 17:05:53 UTC

Evaluates how well and instrument covers all relevant parts of the construct, such as a theme or idea, it aims to measure

Measurement error:

2024-06-19 17:12:32 UTC

The difference between the observed value and the actual value of what we someone is measuring

Interrater reliability/Data set/Variables

2024-06-19 22:20:37 UTC

Interrater reliability

Definition: In statistics, inter-rater reliability is a way to measure the level of agreement between multiple raters or judges. It is used as a way to assess the reliability of answers produced by different items on a test.

Example: If multiple teachers give grades using the same rubric, it demonstrates high inter-rater relationship in their grading criteria.

Data Set

Definition: Refers to any collection of data.

Example: In tabular data, a dataset corresponds to one or more database tables, where every column of the table represents a particular variable.

Variables

Definition: A quantity which during a calculation is assumed to vary or be capable of varying in value. This quantity may be changed according to the mathematical problem.

Example: A variable is a symbol for a number where the value is not known, (x + 6 = 10) Here "x" is a variable.

Kristen Heard

Internal Validity

2024-06-19 23:31:25 UTC

is the degree of confidence that the casual relationship you are testing is not influenced by other factors or variables.

Gina Hargis

Independent Variable

2024-06-19 23:34:11 UTC

a variable that stands alone and is not changed by the other variables you are trying to measure.

Gina Hargis

Random Error

2024-06-19 23:35:48 UTC

is a chance difference between the observed and true value of something.

Gina Hargis

Test Retest Reliability

2024-06-20 02:32:24 UTC

This essentially assess the consistency of a measurement tool over time. It gauges if the a test or measurement will provide similar results for an individual when performed on separate occasions. If the measurements are similar every time, a high correlation is noted signifying a strong test-retest reliability.

Fernando Ibarra

External Validity

2024-06-20 02:39:17 UTC

This simply means the ability to express the results of a study from the small group of people and be able to generalize these results among the general population.

Fernando Ibarra

Quantitative Variables

2024-06-20 02:45:38 UTC

Quantitative Variables essential represent characteristics that are measurable and can be expressed as numerical value. These variables can be broken down into Discrete Variables or Continuous variables. Discrete variables include things like test score results, number of words in a sentence, or even the number of siblings one has. Continuous variables incorporate things like a persons height, their weight, and the current temperature.

Fernando Ibarra

3 Padlet Definitions by Veronica Magana

2024-06-23 18:26:05 UTC

LEVEL OF MEASURMENT

variables can be quantified and categorized. They include four primary levels: nominal, ordinal, interval, and ratio scales. For each of these they feature different data and how it is recorded.

DATA SET

is a collection about data points or values that are organized or in structured format. Each data set has a data point which represents specific measurements or observation. It is used for analysis.

External Validity

Examines if the findings of a study can be generalized to other contexts such as people, settings, and time.