Terminologie et définitions des données numériques

Important Numerical Data: Terminology and Definitions

• Data: Raw facts, figures, and observations. In a numerical context, data are values that can be measured or counted.

• Variables: Characteristics or attributes that can take on different values. Numerical variables can be discrete (e.g., number of students in a class) or continuous (e.g., height).

• Measures of Central Tendency: These describe the typical or central value of a dataset.

• Mean: The average value, calculated by summing all values and dividing by the total count.

• Median: The middle value when the data is ordered.

• Mode: The most frequent value.

• Measures of Dispersion: These describe the spread or variability of the data.

• Range: The difference between the highest and lowest values.

• Variance: A measure of how spread out the data is from the mean.

• Standard Deviation: The square root of the variance, providing a more interpretable measure of spread.

• Frequencies and Distributions: Explaining the occurrences of different data points.

• Frequency table: A table showing the count of each distinct value in a dataset.

• Histogram: A graphical representation of the frequency distribution.

• Descriptive Statistics: Numerical summaries of data to describe characteristics (e.g., central tendency, variability).

• Inferential Statistics: Using sample data to make inferences about a larger population. Numerical data are often central to these inferences.

• Parameters: Numerical values that describe the entire population (e.g., population mean).

• Statistics: Numerical values that describe a sample drawn from the population (e.g., sample mean).

• Population: The complete set of all items of interest. Numerical data can be collected from the entire population or a sample.

• Sample: A subset of the population. Often, numerical data is only collected on a sample due to cost, time, or feasibility issues. Numerical analysis of the sample is used to infer information about the larger population.

• Statistical Significance: The likelihood that a result obtained from a sample is not due to chance. Numerical data play a critical role in testing for this significance.

• Correlation and Regression: Methods to analyze how variables relate to one another numerically, commonly used in research. For example, a researcher might quantify how "Number of hours studied" (variable) relates to "Test score" (variable) with numerical analysis.

• Data Analysis: The process of inspecting, cleansing, transforming, and modelling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making. Numerical data plays a pivotal role in almost all data analysis processes.

Testez vos connaissances sur la terminologie et les définitions importantes concernant les données numériques. Ce quiz couvre des concepts clés comme les variables, les mesures de tendance centrale et les mesures de dispersion. Préparez-vous à plonger dans le monde des statistiques !