The residual sum of squares (RSS) measures the difference between your observed data and the model’s predictions. It is the portion of variability your regression model does not explain, also known as the model’s error. Use RSS to evaluate how well your model fits the data. [Read more…] about Residual Sum of Squares (RSS) Explained
What is One Way ANOVA?
Use one way ANOVA to compare the means of three or more groups. This analysis is an inferential hypothesis test that uses samples to draw conclusions about populations. Specifically, it tells you whether your sample provides sufficient evidence to conclude that the groups’ population means are different. ANOVA stands for analysis of variance. [Read more…] about One Way ANOVA Overview & Example
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
What is a One Sample T Test?
Use a one sample t test to evaluate a population mean using a single sample. Usually, you conduct this hypothesis test to determine whether a population mean differs from a hypothesized value you specify. The hypothesized value can be theoretically important in the study area, a reference value, or a target. [Read more…] about One Sample T Test: Definition, Using & Example
What is a Parsimonious Model?
A parsimonious model in statistics is one that uses relatively few independent variables to obtain a good fit to the data. [Read more…] about What is a Parsimonious Model? Benefits and Selecting
What is a T Test?
A t test is a statistical hypothesis test that assesses sample means to draw conclusions about population means. Frequently, analysts use a t test to determine whether the population means for two groups are different. For example, it can determine whether the difference between the treatment and control group means is statistically significant. [Read more…] about T Test Overview: How to Use & Examples
What is the Wilcoxon Signed Rank Test?
The Wilcoxon signed rank test is a nonparametric hypothesis test that can do the following:
- Evaluate the median difference between two paired samples.
- Compare a 1-sample median to a reference value.
What is a Likert Scale?
The Likert scale is a well-loved tool in the realm of survey research. Named after psychologist Rensis Likert, it measures attitudes or feelings towards a topic on a continuum, typically from one extreme to the other. The scale provides quantitative data about qualitative aspects, such as attitudes, satisfaction, agreement, or likelihood. [Read more…] about Likert Scale: Survey Use & Examples
What is a Two-Way Table?
A two-way table displays frequencies for combinations of two categorical variables. Columns correspond to the values of one variable, while the rows relate to the other. The intersection of each row and column displays a frequency or relative frequency of observations having a pair of categorical attributes. Statisticians also refer to them as contingency tables. [Read more…] about Two-Way Table Explained
What is the Kruskal Wallis Test?
The Kruskal Wallis test is a nonparametric hypothesis test that compares three or more independent groups. Statisticians also refer to it as one-way ANOVA on ranks. This analysis extends the Mann Whitney U nonparametric test that can compare only two groups. [Read more…] about Kruskal Wallis Test Explained
What is the Mann Whitney U Test?
The Mann Whitney U test is a nonparametric hypothesis test that compares two independent groups. Statisticians also refer to it as the Wilcoxon rank sum test. The Kruskal Wallis test extends this analysis so that can compare more than two groups. [Read more…] about Mann Whitney U Test Explained
What is Covariance?
Covariance in statistics measures the extent to which two variables vary linearly. The covariance formula reveals whether two variables move in the same or opposite directions. [Read more…] about Covariance: Formula, Definition & Example
What is the Root Mean Square Error?
The root mean square error (RMSE) measures the average difference between a statistical model’s predicted values and the actual values. Mathematically, it is the standard deviation of the residuals. Residuals represent the distance between the regression line and the data points. [Read more…] about Root Mean Square Error (RMSE)
A least squares regression line represents the relationship between variables in a scatterplot. The procedure fits the line to the data points in a way that minimizes the sum of the squared vertical distances between the line and the points. It is also known as a line of best fit or a trend line. [Read more…] about Least Squares Regression: Definition, Formulas & Example
What is ANCOVA?
ANCOVA, or the analysis of covariance, is a powerful statistical method that analyzes the differences between three or more group means while controlling for the effects of at least one continuous covariate. [Read more…] about ANCOVA: Uses, Assumptions & Example
What is a Cumulative Distribution Function?
A cumulative distribution function (CDF) describes the probabilities of a random variable having values less than or equal to x. It is a cumulative function because it sums the total likelihood up to that point. Its output always ranges between 0 and 1. [Read more…] about Cumulative Distribution Function (CDF): Uses, Graphs & vs PDF
What is Slope Intercept Form?
The slope intercept form of linear equations is an algebraic representation of straight lines: y = mx + b. [Read more…] about Slope Intercept Form of Linear Equations: A Guide
What is Monte Carlo Simulation?
Monte Carlo simulation uses random sampling to produce simulated outcomes of a process or system. This method uses random sampling to generate simulated input data and enters them into a mathematical model that describes the system. The simulation produces a distribution of outcomes that analysts can use to derive probabilities. [Read more…] about Monte Carlo Simulation: Make Better Decisions
What is Principal Component Analysis?
Principal Component Analysis (PCA) takes a large data set with many variables per observation and reduces them to a smaller set of summary indices. These indices retain most of the information in the original set of variables. Analysts refer to these new values as principal components. [Read more…] about Principal Component Analysis Guide & Example
What is a Z Test?
Use a Z test when you need to compare group means. Use the 1-sample analysis to determine whether a population mean is different from a hypothesized value. Or use the 2-sample version to determine whether two population means differ. [Read more…] about Z Test: Uses, Formula & Examples