gross regression coefficient - meaning, definition, translation, pronunciation
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gross regression coefficient (english) - meaning, definition, translation, pronunciation


Part of Speech

Noun Phrase

Phonetic Transcription

/ɡroʊs rɪˈɡrɛʃən koʊˈɛfɪʃənt/

Meaning and Usage

The term "gross regression coefficient" refers to a statistical measure that quantifies the relationship between one dependent variable and one or more independent variables in a regression analysis. Specifically, it indicates how much the dependent variable is expected to change when one of the independent variables changes by one unit, assuming all other variables remain constant.

This term is frequently used in written contexts, particularly in academic papers, research reports, and statistical analyses, rather than in oral speech. The usage of this term is common in fields such as economics, social sciences, and data science.

Frequency of Use

The term is relatively specialized and may not be widely used outside of statistical or academic contexts, making it less common in everyday conversation.

Example Sentences

  1. The researchers calculated the gross regression coefficient to evaluate the impact of education on income levels.
    Исследователи рассчитают коэффициент грубой регрессии, чтобы оценить влияние образования на уровень дохода.

  2. Understanding the gross regression coefficient helps in identifying the strength of the relationship between variables.
    Понимание коэффициента грубой регрессии помогает выявить силу связи между переменными.

  3. In their preliminary analysis, they reported a high gross regression coefficient, suggesting a strong link between the variables.
    В своем предварительном анализе они сообщили о высоком коэффициенте грубой регрессии, что свидетельствует о сильной связи между переменными.

Idiomatic Expressions

The term "gross regression coefficient" itself is not commonly part of idiomatic expressions. However, regression analysis contains several key concepts that may be idiomatized within statistical discussions. Here are some related expressions:

  1. "To see the big picture," in regression analysis, one might look at the gross regression coefficient for a clearer understanding of trends. "Увидеть общую картину," в регрессионном анализе, можно, обращая внимание на коэффициент грубой регрессии для лучшего понимания тенденций.

  2. "Plug and play," can refer to how one can easily enter new variables into a model to calculate the gross regression coefficient. "Вставь и работай," может относиться к тому, как можно легко вводить новые переменные в модель для вычисления коэффициента грубой регрессии.

  3. "A picture is worth a thousand words," which applies when visualizing data helps clarify the impact of the gross regression coefficient. "Лучше один раз увидеть, чем сто раз услышать," что применимо, когда визуализация данных помогает прояснить влияние коэффициента грубой регрессии.

  4. "On the right track," may apply when analyzing the gross regression coefficient leads to valid conclusions. "На верном пути," может применяться, когда анализ коэффициента грубой регрессии приводит к правильным выводам.

  5. "Cross your T's and dot your I's," emphasizes the importance of meticulousness when reporting the gross regression coefficient in a study. "Перепроверять каждую деталь," подчеркивает важность тщательности при представлении коэффициента грубой регрессии в исследовании.

Etymology

The term "gross" comes from the Latin word "grossus," meaning "thick" or "large." "Regression" derives from the Latin "regressio," based on "regredi," meaning "to go back" or "retreat." "Coefficient" originates from the Latin "coefficientem," meaning "working together." In the context of statistics, this term has been established in the early 20th century as a formal method to analyze relationships among variables.

Synonyms and Antonyms

Synonyms: - Regression coefficient - Parameter estimate

Antonyms: - Regression intercept (in some contexts, though they reflect different concepts) - Constant (in the context of disregard for variables)



25-07-2024