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Front end : use ONLY the first few # Relative size : use the FULL # and round it

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โˆ™ 2012-06-20 01:58:05
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A polynomial of degree zero is a constant term

The grouping method of factoring can still be used when only some of the terms share a common factor A True B False

The sum or difference of p and q is the of the x-term in the trinomial

A number a power of a variable or a product of the two is a monomial while a polynomial is the of monomials

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Q: What is the diffrerence between front-end and relative-size estimation?
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What is the difference between an estimation and an approximation?

estimation is to think of an answer before measuring the quantity and approximation is to round off.

Why is it helpful to make an estimate before finding the zize of a piece of a circle graph?

Mr. Kevin thinks that estimation can help students get real sense of conversion between fraction and percentage.

How do you find distance in a speed time graph?

The distance from the origin at time t, in the direction of motion, is the area under the graph between time 0 and time t. In a simple speed-time graph the area may be calculated using simple formulae for the areas of triangles, rectangles, trapeziums. In more complicated cases you will need to integrate for the area under the speed-time curve. And in seriously complex cases, you will have to use numerical estimation for the area.

What are the advantages and disadvantages of presenting a relationship between two variables in a graph?

Advantages:The nature of the relationship is generally easier to see: linear, polynomial, exponential, power etc;The range and domain of the data sets are immediately apparent,Estimation for intermediate values (interpolation) is relatively straightforward.Disadvantages:Not very useful if the observations are unevenly spread over a large range or domain (very skewed distribution).Exact values not given,Exact parameters describing relationship not available,Tendency of naive users to extrapolate.

How do you interpret residual values?

The residuals in regression estimation are estimates of error. Most commonly, the errors are assumed to be statistically independent, identically distributed and normally distributed, that is, to have a Gaussian distribution.If these were the assumptions under which the regression was calculated then the residuals could (at least potentially) be examined for any departures from the assumptions. Usually they are plotted against the independent variable to see if there is any systematic relationship between the two sets of values. The residuals might also be tested for normality.It's worth reading more about this subject.

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