Parameters are numbers that describe the properties of entire populations. Statistics are numbers that describe the properties of samples. [Read more…] about Parameter vs Statistic: Examples & Differences
conceptual
Spurious Correlation: Definition, Examples & Detecting
What is a Spurious Correlation?
A spurious correlation occurs when two variables are correlated but don’t have a causal relationship. In other words, it appears like values of one variable cause changes in the other variable, but that’s not actually happening. [Read more…] about Spurious Correlation: Definition, Examples & Detecting
Contingency Table: Definition, Examples & Interpreting
What is a Contingency Table?
A contingency table displays frequencies for combinations of two categorical variables. Analysts also refer to contingency tables as cross tabulation and two-way tables. [Read more…] about Contingency Table: Definition, Examples & Interpreting
Permutation vs Combination: Differences & Examples
In mathematics and statistics, permutations vs combinations are two different ways to take a set of items or options and create subsets. For example, if you have ten people, how many subsets of three can you make? While permutation and combination seem like synonyms in everyday language, they have distinct definitions mathematically.
- Permutations: The order of outcomes matters.
- Combinations: The order does not matter.
Let’s understand this difference between permutation vs combination in greater detail. And then you’ll learn how to calculate the total number of each. [Read more…] about Permutation vs Combination: Differences & Examples
Cumulative Frequency: Finding & Interpreting
What is Cumulative Frequency?
Cumulative frequency is the running total of frequencies in a table. Use cumulative frequencies to answer questions about how often a characteristic occurs above or below a particular value. It is also known as a cumulative frequency distribution.
For example, how many students are in the 4th grade or lower at a school? [Read more…] about Cumulative Frequency: Finding & Interpreting
Chi-Square Goodness of Fit Test: Uses & Examples
What is the Chi Square Goodness of Fit Test?
The chi-square goodness of fit test evaluates whether proportions of categorical or discrete outcomes in a sample follow a population distribution with hypothesized proportions. In other words, when you draw a random sample, do the observed proportions follow the values that theory suggests. [Read more…] about Chi-Square Goodness of Fit Test: Uses & Examples
Sampling Error: Definition, Sources & Minimizing
What is Sampling Error?
Sampling error is the difference between a sample statistic and the population parameter it estimates. It is a crucial consideration in inferential statistics where you use a sample to estimate the properties of an entire population. [Read more…] about Sampling Error: Definition, Sources & Minimizing
Cohort Study: Definition, Benefits & Examples
What is a Cohort Study?
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. Cohort studies are a type of longitudinal study because they track the same set of subjects over time. They hold a mid-to-high position in the level of evidence ranking, providing valuable observational insights over time. [Read more…] about Cohort Study: Definition, Benefits & Examples
Inter-Rater Reliability: Definition, Examples & Assessing
What is Inter-Rater Reliability?
Inter-rater reliability measures the agreement between subjective ratings by multiple raters, inspectors, judges, or appraisers. It answers the question, is the rating system consistent? High inter-rater reliability indicates that multiple raters’ ratings for the same item are consistent. Conversely, low reliability means they are inconsistent. [Read more…] about Inter-Rater Reliability: Definition, Examples & Assessing
How to Find the Mode
There are several ways to find the mode depending upon the data type and sample size. In statistics, the mode is the most frequently occurring value in a data set. It is a measure of central tendency. To learn more about the mode, read my post, Measures of Central Tendency. [Read more…] about How to Find the Mode
Bimodal Distribution: Definition, Examples & Analysis
A bimodal distribution has two peaks. In the context of a continuous probability distribution, modes are peaks in the distribution. The graph below shows a bimodal distribution. [Read more…] about Bimodal Distribution: Definition, Examples & Analysis
Margin of Error: Formula and Interpreting
What is the Margin of Error?
The margin of error (MOE) for a survey tells you how near you can expect the survey results to be to the correct population value. For example, a survey indicates that 72% of respondents favor Brand A over Brand B with a 3% margin of error. In this case, the actual population percentage that prefers Brand A likely falls within the range of 72% ± 3%, or 69 – 75%. [Read more…] about Margin of Error: Formula and Interpreting
Quartile: Definition, Finding, and Using
What are Quartiles?
Quartiles are three values that split your dataset into quarters. They are a type of quantile that splits the data into four equal-sized groups and tells you where a score stands relative to other scores. [Read more…] about Quartile: Definition, Finding, and Using
Construct Validity: Definition and Assessment
What is Construct Validity?
Construct validity relates to the soundness of inferences that you draw from test scores and other measurements. Specifically, it addresses whether a test measures the intended construct. For example, does a test that evaluates self-esteem truly measure that construct or something else? [Read more…] about Construct Validity: Definition and Assessment
Qualitative Research: Goals, Methods & Benefits
Qualitative research aims to understand ideas, experiences, and opinions using non-numeric data, such as text, audio, and visual recordings. The focus is on language, behaviors, and social structures. Qualitative researchers want to present personal experiences and produce narrative stories that use natural language to provide meaningful answers to their research questions. [Read more…] about Qualitative Research: Goals, Methods & Benefits
What is a Variable?
The definition of a variable changes depending on the context. Typically, a letter represents them, and it stands in for a numerical value. In algebra, a variable represents an unknown value that you need to find. For mathematical functions and equations, you input their values to calculate the output. In an equation, a coefficient is a fixed value by which you multiply the variable.
In statistics, a variable is a characteristic of interest that you measure, record, and analyze. Statisticians understand them by defining the type of information they record and their role in an experiment or study. [Read more…] about What is a Variable?
Linear Regression Explained with Examples
What is Linear Regression?
Linear regression models the relationships between at least one explanatory variable and an outcome variable. This flexible analysis allows you to separate the effects of complicated research questions, allowing you to isolate each variable’s role. Additionally, linear models can fit curvature and interaction effects. [Read more…] about Linear Regression Explained with Examples
Null Hypothesis: Definition, Rejecting & Examples
What is a Null Hypothesis?
The null hypothesis in statistics states that there is no difference between groups or no relationship between variables. It is one of two mutually exclusive hypotheses about a population in a hypothesis test. [Read more…] about Null Hypothesis: Definition, Rejecting & Examples
Confidence Intervals: Interpreting, Finding & Formulas
What is a Confidence Interval?
A confidence interval (CI) is a range of values that is likely to contain the value of an unknown population parameter. These intervals represent a plausible domain for the parameter given the characteristics of your sample data. Confidence intervals are derived from sample statistics and are calculated using a specified confidence level. [Read more…] about Confidence Intervals: Interpreting, Finding & Formulas
Kurtosis: Definition, Leptokurtic & Platykurtic
What is Kurtosis?
Kurtosis is a statistic that measures the extent to which a distribution contains outliers. It assesses the propensity of a distribution to have extreme values within its tails. There are three kinds of kurtosis: leptokurtic, platykurtic, and mesokurtic. Statisticians define these types relative to the normal distribution. Higher kurtosis values indicate that the distribution has more outliers falling relatively far from the mean. Distributions with smaller values have a lower tendency for producing extreme values. When you’re assessing a sample, outliers have the greatest impact on this statistic. [Read more…] about Kurtosis: Definition, Leptokurtic & Platykurtic