Statistics By Jim

Making statistics intuitive

interpreting results

Positive Predictive Value: Meaning, Formula, and Interpretation

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What is Positive Predictive Value (PPV)?

Positive Predictive Value (PPV) assesses a diagnostic test’s accuracy by calculating the probability that a person who tests positive truly has the condition. PPV focuses on how trustworthy a positive result is in real-world testing scenarios. Hence, it is the best measure for interpreting an individual positive test result. Mammography, for example, is a well-known case where PPV plays a central role in understanding what a positive test result really means. [Read more…] about Positive Predictive Value: Meaning, Formula, and Interpretation

Sensitivity vs Specificity: Definition, Formulas & Interpreting

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Sensitivity and specificity are two key metrics used to evaluate the performance of diagnostic tests or classification systems in statistics, medicine, and machine learning. These measures assess the intrinsic capabilities of a test. [Read more…] about Sensitivity vs Specificity: Definition, Formulas & Interpreting

Inferential Statistics Definition & Examples

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What are Inferential Statistics?

Inferential statistics use samples to draw conclusions about populations. Typically, it is impractical to measure every population member. Instead, we collect a random sample from a small portion of the population, measure them, and use their data to estimate population properties. Using correct inferential statistics procedures, you can use samples to draw reasonable conclusions about whole populations. [Read more…] about Inferential Statistics Definition & Examples

Descriptive Statistics Definition and Examples

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What are Descriptive Statistics?

Descriptive statistics summarize the properties of a dataset using summary statistics, tables, and graphs. These descriptions characterize vital information about the variables, their relationships, and trends. Ideally, they provide a clearer picture of the data than the raw values. In short, they describe the essential features of a sample. [Read more…] about Descriptive Statistics Definition and Examples

Multinomial Logistic Regression: Overview & Example

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What is Multinomial Logistic Regression?

Multinomial logistic regression statistically models the probabilities of at least three categorical outcomes that do not have a natural order. This technique uses a linear combination of independent variables to explore correlations with outcome likelihoods and to predict outcomes using specific input conditions. This analysis is also known as nominal logistic regression. [Read more…] about Multinomial Logistic Regression: Overview & Example

Logistic Regression Overview with Example

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What is Logistic Regression?

Logistic regression statistically models the probabilities of categorical outcomes, which can be binary (two possible values) or have more than two categories. These models use a linear combination of independent variables to help you understand how they correlate with the likelihood of the outcomes and predict them based on specific conditions you enter into the model. [Read more…] about Logistic Regression Overview with Example

Poisson Regression Analysis Overview with Example

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What is Poisson Regression?

Poisson regression statistically models events that you count within a specified observation space. Frequently, analysts define the observation space using time, but it can also relate to a volume, area, or item. These models allow you to understand the independent variables that affect the counts and predict them given specific conditions you enter into the model. [Read more…] about Poisson Regression Analysis Overview with Example

Hypothesis Testing: Uses, Steps & Example

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What is Hypothesis Testing?

Hypothesis testing in statistics uses sample data to infer the properties of a whole population. These tests determine whether a random sample provides sufficient evidence to conclude an effect or relationship exists in the population. Researchers use them to help separate genuine population-level effects from false effects that random chance can create in samples. These methods are also known as significance testing. [Read more…] about Hypothesis Testing: Uses, Steps & Example

One Way ANOVA Overview & Example

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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

One Sample T Test: Definition, Using & Example

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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

T Test Overview: How to Use & Examples

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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

Likert Scale: Survey Use & Examples

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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

Two-Way Table Explained

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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 cross tabulation and contingency tables. [Read more…] about Two-Way Table Explained

Kruskal Wallis Test Explained

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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

Mann Whitney U Test Explained

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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