balanced variance

USAGE SUMMARY

The phrase "balanced variance" is correct and usable in written English.
It can be used in contexts related to statistics, finance, or any field where variance is analyzed and needs to be balanced or adjusted. Example: "To ensure accurate results, we need to calculate the balanced variance of the data set before proceeding with the analysis."

✓ Grammatically correct

Science

Computers & Industrial Engineering

Wiki

Human-verified similar examples from authoritative sources

Similar Expressions

60 human-written examples

Scaling factors have been proposed to balance variance contributions from response variables, quantitative and categorical variables.

Computers & Industrial Engineering

The allocation sequence was created by Medpace using a Williams design to balance variance from potential carry-over effects.

Annals of the Rheumatic Diseases

The paper aims to find variance balanced and variance partially balanced incomplete block designs when observations within blocks are autocorrelated and we call them BIBAC and PBIBAC designs.

Journal of Statistical Planning and Inference

As the haplotype means were not variance balanced, we used the method of Piepho [ 38] to generate a letter display showing the significance of comparisons.

BMC Plant Biology

In both cases, statistical concerns to minimize variance are balanced by logistical concerns to minimize number of assessments.

BMC Medical Research Methodology

Penalized likelihood in regression is a technique used to obtain minimum mean squared error (MSE) of estimated regression coefficients by balancing bias and variance.

BMC Plant Biology

Balanced one-way analysis of variance for all observers indicated that for compression ratios 48 and 64, there was significant difference between mean absolute error of uncompressed and compressed images (P <.05).

Oral Surgery, Oral Medicine, Oral Pathology, Oral Radiology, and Endodontology

For balanced designs the analysis of variance is optimal; for unbalanced ones, however, these estimators are not necessarily the best, and the analysis by residual maximum likelihood (reml) will usually be preferable.

Computers & Geosciences

This phenomenon may relate to the balance between variance and bias of generalization error in statistics.

Brain Informatics

This strategy found a 16-class system as an attractive solution for this data as it provided a balance between variance explained and potential sample size.

Environmental Health: A Global Access Science Source

Therefore, we choose to illustrate the approach with k = 16 as this number of classes suggests a reasonable mapping of our data given the sufficient balance between variance explained (mean R = 0.67) and expected class sample size (n = 170 days).

Environmental Health: A Global Access Science Source

Expert writing Tips

Best practice

When discussing statistical models, clearly define what aspects of the variance are being balanced and why. This provides context and enhances clarity.

Common error

Avoid assuming that "balanced variance" automatically implies improved model performance. Consider the specific goals and constraints of your analysis to determine if balancing variance is truly beneficial.

Linguistic Context

The phrase "balanced variance" functions as a descriptor, modifying the noun "variance" to indicate a state of equilibrium or careful adjustment. Ludwig AI suggests its use in contexts requiring statistical precision.

Expression frequency: Rare

Frequent in

Science

40%

Formal & Business

30%

News & Media

15%

Less common in

Wiki

5%

Encyclopedias

5%

Social Media

5%

Ludwig's WRAP-UP

The term "balanced variance" is used to describe a state of equilibrium or careful adjustment of variance, especially in statistical and analytical contexts. Ludwig AI confirms its grammatical correctness and usability, mostly in scientific domains. When employing this phrase, it's crucial to specify what constitutes the balance and why it's significant. Alternatives like "equitable variance" or "adjusted variance" may be suitable depending on the context. The phrase contributes to the precision required in professional, scientific, and formal discussions.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

equitable variance

Replaces "balanced" with "equitable", emphasizing fairness and even distribution in the variance.

adjusted variance

Focuses on the modification of variance to achieve a desired state.

normalized variance

Highlights the standardization of variance to a common scale.

controlled variance

Emphasizes the management and regulation of variance within specific parameters.

harmonized variance

Suggests an agreement or consistency in variance across different elements.

stabilized variance

Indicates that the variance has been made more consistent and less prone to fluctuation.

optimized variance

Focuses on the process of finding the best possible variance for a specific outcome.

regulated variance

Highlights the control of variance through specific rules or mechanisms.

equalized variance

Emphasizes the process of making variances equal across different groups or conditions.

counteracted variance

Suggests an action has been taken to reduce the impact of variance.

FAQs

How can I use "balanced variance" in a statistical context?

In statistics, "balanced variance" often refers to a state where the spread of data is managed to avoid undue influence from any single variable or factor. For example, in experimental design, researchers might aim for a "balanced variance" to ensure fair comparisons between treatment groups.

What's the difference between "balanced variance" and "equal variance"?

"Equal variance" implies that the variances of different groups or samples are the same. "Balanced variance", on the other hand, suggests that variance is being managed or adjusted to achieve a specific analytical goal, which might not necessarily mean making variances equal but rather achieving an "optimized variance" distribution.

What are some techniques for achieving a "balanced variance" in data analysis?

Techniques for achieving a "balanced variance" include data transformation, weighting, and the use of specific experimental designs like balanced incomplete block designs. The choice of technique depends on the nature of the data and the research question.

In machine learning, how does "balanced variance" relate to the bias-variance tradeoff?

In machine learning, the concept of "balanced variance" is closely tied to the bias-variance tradeoff. Models with high variance are sensitive to noise in the training data, while models with high bias oversimplify the data. Achieving a good balance between bias and variance is crucial for building models that generalize well to new data.