*We may earn money or products from the companies mentioned in this post.*

A residual is the difference between the observed value of a variable and the predicted value of that variable. A positive residual means that the observed value is greater than the predicted value. This can happen when the model underestimates the true value of the variable.

In statistics, a residual is the difference between the observed value of a data point and the predicted value of that data point. A positive residual means that the observed value is higher than the predicted value, while a negative residual means that the observed value is lower than the predicted value.
Residuals are important because they can be used to assess the accuracy of a predictive model.

If the model is accurate, then the residuals should be randomly distributed around zero. If the model is not accurate, then the residuals will tend to be non-random, which can be used to identify the source of the error.
Positive residuals can be caused by a variety of factors, including incorrect data, outliers, and errors in the predictive model.

Negative residuals can also be caused by incorrect data, but are more likely to be caused by the predictive model under-predicting the value of the data point.

## What is a residual? What does it mean when a residual is positive?

## What is a residual explain?

A residual is the amount of money left over after all deductions have been made from a person’s salary or other income. In the context of an annuity, a residual is the value of the annuity after all periodic payments have been made.

## What is a residual explain when a residual is positive negative and zero quizlet?

A residual is the difference between the actual value and the predicted value. A positive residual means that the actual value is higher than the predicted value, while a negative residual means that the actual value is lower than the predicted value. A residual of zero means that the actual value is exactly the same as the predicted value.

## Is residual negative or positive?

Residual income is a measure of financial performance used to evaluate the profitability of an organization. It is the difference between a company’s operating income and its net income. In other words, it is the company’s net income after taxes and interest expenses have been deducted from operating income.

There are two types of residual income: positive and negative. Positive residual income indicates that a company’s earnings are more than sufficient to cover its operating costs and produce a profit. Negative residual income indicates that a company’s earnings are not enough to cover its operating costs, and as a result, it is operating at a loss.

In general, companies with positive residual income are more profitable than those with negative residual income. This is because positive residual income indicates that a company is generating more revenue than it is spending on expenses. Therefore, it is able to reinvest this excess revenue in order to grow and expand its business.

However, there are some exceptions to this rule. For example, companies in cyclical industries tend to have negative residual income during periods of economic downturn. This is because their revenue tends to decline during these times, while their expenses remain relatively constant.

As a result, they are unable to reinvest their excess revenue in order to grow their business, and their profits suffer as a result.

## Is residual value always positive?

No, residual value is not always positive. In fact, it can be negative in some instances. This occurs when the market value of a asset at the end of its lease period is less than the amount still owed on the lease.

In such cases, the lessee would be responsible for making up the difference.

Credit: study.com

## Quizlet what is a residual? what does it mean when a residual is positive?

In statistics, a residual is the difference between the observed value of a dependent variable (y) and the value of that variable predicted by the regression line (ŷ). A residual is also referred to as an error term.
If the residual is positive, it means that the observed value is higher than the predicted value.

This could be due to chance, or it could indicate that there is some other factor influencing the dependent variable that is not accounted for by the regression model.

## What is a residual? what does it mean when a residual is positive? chegg

In statistics, a residual is the difference between the observed value of a variable and the predicted value of the variable. A residual is positive when the observed value is greater than the predicted value.

## Explain what each point on the least-squares regression line represents.

In statistics, the least-squares regression line is the line that best fits the data on a scatter plot. This line minimizes the sum of the squares of the vertical distances between the data points and the line. Each point on the least-squares regression line represents a predicted value of the dependent variable, based on the value of the independent variable.

## Conclusion

A residual is the difference between what is observed and what is predicted. A positive residual means that the observed value is greater than the predicted value.