M Clin Path 2025 - Statistics Flashcards

Vocabulary flashcards based on lecture notes from M Clin Path 2025, covering key statistical terms and concepts.

Statistics

A collection of tools that help people interpret quantitative data in a meaningful way.

Categorical (qualitative) data

Characteristics that are classified into groups.

Numerical (quantitative) data

Measurements conveying information regarding amount.

Descriptive statistics

Describing data using summary values such as counts, percentages, mean/median, standard deviation, range.

Data visualization

Using graphs and charts to represent and interpret data effectively.

Correlation

Measuring the strength and direction of a relationship between two variables.

Regression

Examining the relationship between two or more variables.

Probability

Understanding the likelihood of events.

Inferential statistics

Drawing conclusions about a larger population based on a sample.

Hypothesis testing

Assessing the credibility of a statement about a population based on sample data.

Nominal data

Data classified by some quality rather than a numerical measure (e.g., Dead/Alive).

Ordinal data

Ordered category (e.g., level of agreement).

Discrete data

Whole values (e.g., numbers of events, objects, people etc.).

Continuous data

Measures that can take any value within an observed range (e.g., length, weight, ratio).

Frequency

The number (count) of observations that fall into each category.

Relative frequency

The proportion of observations that fall into each category (count/total number).

Mean

Numeric average of the data; add together all the values and divide by the total number of observations.

Median

The value that splits the data in half; sort the data, then take the value in the middle.

Variance

Average of squared deviations of the observations from the mean.

Interquartile range

The middle 50% of the data; difference between the 1st and 3rd quartiles (IQR = Q3 – Q1).

Sample standard deviation

Square root of sample variance estimate; a single positive number on the same scale as the observations that describes a “typical” deviation from the sample mean.

Coefficient of variation

A standardized measure of dispersion (ie spread); used to aid in the selection of a new method for routine use and to monitor the inherent variability (precision) of a method already in routine use.

Symmetric data

Similarly spread either side of the mean (mean ≈ median).

Right-skewed data

Long right tail; median is less than mean.

Left-skewed data

Long left tail; median is greater than mean.

Distribution

Describes the pattern of the values that data take when drawn from that population.

Association

Two variables are associated if knowing the value of one tells us something about the values of the other variable.

Scatterplots

Display of 2 quantitative variables measured on the same individuals/experimental units; useful for showing patterns, trends, relationships, outliers.

Pearson’s sample correlation coefficient

Measure of linear association between y and x.

Spearman’s rank correlation coefficient

Measure of strength and direction of the monotonic relationship between two ranked variables.

Simple linear regression

Describes the relationship between 2 numeric variables in terms of a predictor, x, and a response variable, y; models the relationship as a straight line.

Residual

Distance between the point and the fitted value on the line of best fit; Observed value – Fitted value.

R-squared (R2)

Explained variation/Total variation (proportion of the variation in the response variable that is explained by the variation in the predictor variable).

Analytical variation

Observed differences in the value of an analyte once it has been prepared for analysis.

Intra-individual variation

Variability in true values of an analyte obtained from the same individual.

Inter-individual variation

Variability due to differences in true (mean) values of an analyte between individuals.

Accuracy

How close are the measurements to their “true” value?

Precision

How close are independent measurements of the same thing to each other?

Sample statistics

Calculated summaries describing SAMPLE characteristics (e.g., sample mean, sample standard deviation).

Population parameters

Defining characteristics of the population, usually unknown, and typically labelled with a Greek symbol (e.g., μ for population mean, σ for population standard deviation).