If you rounded up, it's an overestimate, if you rounded down, it's an underestimate. If you did both, whatever you did more of will prevail.
Explain how you know whether an estimate of a product is an overestimate or an underestimate?
You know when to overestimate when the last number is over five then you round it up. Under is the last number below five you round down.
Compatible numbers would be easier. Rounding gives you 14 x 47. Compatible numbers could be 13 x 50 which would be closer to the actual product.
The questioner needs to make up his/her mind whether the question is about the sum or product.
Given any number, there is an even number that exists greater than it. That even number is a product: of 2 and some number. Therefore, the number that you started with is less than the product of a pair of numbers.
Explain how you know whether an estimate of a product is an overestimate or an underestimate?
well i would think since you pknow how to estimate is that you should give up and take a nap
You know when to overestimate when the last number is over five then you round it up. Under is the last number below five you round down.
look at the scales
If someone were to overestimate or underestimate based on how it would make them feel, they would certainly overestimate their wealth and underestimate their weight. But for what's most helpful depends on what one is calculating. It's best to underestimate one's income so they can enjoy a little extra without fearing debt. It's best to overestimate one's spending for the same reason.
To determine whether 83790 is an overestimate or an underestimate, we need context regarding what it is being compared to. If 83790 is meant to represent a quantity or value that is expected to be lower, then it is an overestimate. Conversely, if it is compared to a value that is expected to be higher, then it is an underestimate. Without additional information, it's not possible to definitively categorize 83790.
You can identify an overestimate by recognizing that the predicted value exceeds the actual outcome, while an underestimate occurs when the prediction falls short of the actual result. To determine this, compare the estimated values to the true values. If the estimate is higher than reality, it's an overestimate; if it's lower, it's an underestimate. Additionally, analyzing the context and the methods used for estimation can help clarify whether estimates are likely to be inflated or deflated.
Small samples and large population variances imply that the estimate for the mean will be relatively poor. Whether or not it will result in an underestimate or overestimate depends on the distribution: with a symmetric distribution the two outcomes are equally likely.
because its just helpful!! lol gotcha
Deciding whether an overestimate or underestimate is more useful depends on the context and the potential consequences of each. For example, in project management, an overestimate of time may be beneficial to ensure that deadlines are met without stress, while an underestimate might lead to missed deadlines and project failure. Conversely, in resource allocation, an underestimate of costs could result in budget shortfalls, making a more conservative approach preferable. Ultimately, the choice hinges on the balance between risk tolerance and the desired outcomes.
well, it mostly depends on the reason...... if you are throwing a party, then you want to overestimate so that you dont have to go to the store again and if you are going shopping and you only got $20, then you want to underestimate.So, ya it mostly depends on the reason.
Relative bias refers to the difference between the expected value of an estimator and the true value of the parameter being estimated, expressed as a proportion of the true value. It provides a measure of the accuracy of the estimation process, indicating whether the estimator tends to overestimate or underestimate the parameter. Relative bias is often used in statistical analysis to assess the performance of different estimators, especially in contexts where the magnitude of the parameter varies significantly.