"Determining which variables in multiple regression account for the most variance in the dependent variable."
"It's all about variance. That's why it's called analysis of variance."
"Do not panic. This will pass over. This is all due to this new variance scare."
"An infinite world produces uncountable variance... oddly occur an endless number of times."
"PCA is a way of trying to find direction in the space with the largest variance."
"People are not the same emotionally and psychologically any more than they're the same athletically or artistically."
"The most interesting thing is that men have one ideal, but women have more variance in what is attractive in terms of body type or facial features."
"The question is not just to minimize bias but to balance bias and variance."
"I like the luck factor, I like the variance, the unpredictability."
"15 percent is explaining a lot of variance in the behavioral sciences and this is just in the last couple years."
"It's all about creating that variance."
"Regularization introduces a penalty by shrinking the coefficients towards zero, reducing the overall model variance."
"This level of coherence contrasts with the many other ancient textual traditions like Greek, which often show a great degree of variance due to factors like scribal errors, intentional edits, distortions, or regional variations."
"You have to embrace variance and the more difficult spots."
"Averages are misleading because what matters is variance."
"The role of variance in poker is complex and also paramount."
"Luck and variance obviously exist but really what they are are in many ways I think misunderstood."
"It's not genetic determinism. Yeah, we're talking about explaining modest proportions of the variance."
"Cash games or sit and goes will result in a consistent climb, tournaments will have lots of variance."
"It started off a lot better than it ended. I guess I was running super hot in like the first hour or two."
"For a given torque, you might have a bolt tension variance of 225%, using an antiseize you can typically drive that down somewhere in the sub 5% variance."
"There's quite a lot of variance in terms of what we think normal is."
"43% of the variance in weight can be accounted for by the height measures."
"This is really variance analysis, and we want to know if our sales and our profit are moving from pricing, volume, the mix of our products, or cost."
"You might want to test for differential, for example, changes in variance."
"Principal component analysis is a dimensionality reduction technique that finds the directions of maximal variance in the data."
"The first principal components tend to capture a large amount of the variance in our data."
"The trade-off is that you decide what is the level you will tolerate for your bias and what is the level you will tolerate for variance."
"Heritability means the percent variance in a trait that is dependent on genetics as opposed to the environment."
"The variance based method means there's a total variation that we have in our response output, and we'd like to evaluate to what extent some input parameter contributes to that total variance."
"By combining them I can explain almost 90 percent of the variance in the data."
"Schedule Variance is Earned Value minus Planned Value."
"Cost Variance is Earned Value minus Actual Cost."
"There's a lot of variance in the short run, anyone can win in the short run; there's almost no variance in the long run."
"If you're good, you're going to win all the time in the long run, but there's variance in the short run. Get used to it."
"Variance is going to measure how far a set of numbers is spread out."
"Every once in a while, variants such as Loki veer off their predetermined paths and cause nexus events which, left unchecked, could branch off into madness, leading to another multiversal war."
"But you will be able to impress your Harvard friends if you tell them that I can actually calculate the variance of how much I can spend."
"Variance is described as the average of the squared differences from the mean."
"The moderation effect tests residual variance, meaning you want to already know what the main effects are."
"If you can overcome your bias towards long-running shonen manga, you'll find a surprising amount of variance in how people react to each one."
"You have to be able to accept variance in sports betting, it's an incredibly important concept to understand."
"This one's better because it's closer on average, of smaller variance."
"Any normal distribution can be defined based on the mean value or mu, and the variance of that normal distribution."
"The variance of Z is larger than both variables, meaning we found a new direction with the largest variance possible."
"The decrease in variance that you get from doing this, is much larger than the slight increase in bias you get from randomized subsampling."
"Decision trees are high variance, low bias okay? And this right here sort of explains why they're a pretty good fit for bagging."
"The total variance of the signal in time is the same as the total variance of the signal in the frequency domain."
"If we want to maximize the amount of variance then we must choose the eigenvector corresponding to the largest eigenvalue of the matrix."
"As we increase the complexity of the model, we can reduce the bias down to very small amounts, but from a certain point onwards, we start increasing the variance."
"The variance of the residual terms should be the same for all observations; if not, we have heteroscedasticity."
"A principal component is simply the normalized linear combination of a feature that has the largest variance."
"The variance essentially quantifies uncertainty."
"The variance is the expected value of the squared deviations from the random variable's expected value."
"A high variance means that the data is very spread out, so the project is more risky. A low variance means that the data is not too spread out, which means the project is relatively low risk."
"The goals of PCA: to drastically reduce our data, to take a high dimensional data set and give it a lower dimension with a lower amount of variance."
"It extracts all the important features of the data and finds a few features that explain the minimum variance."
"We're missing about 22 percent of our variance within our data."
"Principal Component Analysis essentially maximizes the variance while minimizing the amount of features."
"The chi-square test is used for hypothesis tests concerning the variance of a normally distributed population."
"Principal component is simply the normalized linear combination of a feature that has the largest variance."
"Variance is going to measure how data is spread around the mean."
"Covariance is what we need to deal with variance of the sum."
"Covariance of X with itself is the variance."
"Using variance analysis could help to identify significant adverse variances."
"Ultimately with variance analysis, our job is to explain why the actual profit is different than the budgeted profit."
"We're going to look at each of those variances and analyze them."
"Unlike OLS regression, Poisson and negative binomial regression do not assume normally distributed residuals with constant variance."
"Variance is simply a difference between standard results and actual results."
"Variances must be fair; they should not be prejudiced or involved with anything which is outside the control of the managers."
"The variance measures the spread of the distribution; how spread out are the values."
"You cannot simply add standard deviations; you must add the variance first, then take the square root of the total variance to get a total standard deviation."
"The mean tells you where you'd expect the answers to fall, and the variance tells you how far on each side those answers will go."
"This defines the variance, the standard deviation; it's talking about how, if you're having a distribution that's centered on the average, how is the other data smeared around the average."
"Lower variance is actually a good thing."
"PCA tells us that the subspace onto which you want to project your data should be the one where the variance of the projected points is maximized."
"By choosing k to be, say, 95%, you can effectively say that you've retained 95% of the variance in your data."
"To fight variance, we do things like increase regularization or collect more data."
"Variance is measuring how dispersed the sampling distribution is."
"The cumulative variance of the first three modes is about 64 percent, which is good."
"If you maximize the variance then you're also increasing the overlap between the two classes which we don't want."
"The variance of the projected points along the direction is W transpose lambda W."
"Even the slightest variance could veer a conversation in a different direction."
"I like to put different backgrounds just to give some variance to your jellyfish."
"The variance is trying to measure how spread apart is this distribution in general."
"I'm looking at the portion of the variance that can be explained by the market. That's why it matters."
"The mean of uniform probability distribution is (a+b)/2 and variance is (b-a) squared over 12."
"Cost variance is the difference between the earned value and the actual cost."
"The higher the variance, the flatter the distribution becomes."
"Additive genetic variance is the proportion of the phenotypic variance due to differences in genes that behave in an additive way."
"If one sample has a very large variance... that would violate one of the assumptions for the t-test."
"It is recommended when the primary concern is to determine the minimum number of factors that will account for maximum variance."
"The principal component is the direction in which most of the variance lies."
"The step size I could choose would basically be proportional to the variance."
"Sometimes it's easier to spot design flaws in our structure or in our system when we have less variance in the input ground motions."
"The quantity \(\sigma^2\) denotes the variance."
"The width of this curve is proportional to \(\sigma^2\), which is the variance."
"The mean of this new Gaussian random variable \(X\) is \(\sum a_i\mu_i\), and the variance is \(\sum a_i^2\sigma_i^2 + \sum_{i\neq j} a_ia_j\sigma_{ij}\)."
"The variance of x is equal to the sum of x minus the mean, squared, multiplied by the probability of x."
"We will find the transformation which basically maximizes the variance."
"R-squared essentially shows how much variance is explained by the model."
"The estimator with the minimum variance is unique and is given by the expected value of HX given T."
"Covariance is a combined variance, what is variance before you do square root in this standard deviation working."