Question

How different assumptions of error influence regression analysis? Explain the difference between least square method and sum of absolute errors method in regression analysis.

Answer #1

For a least-square regression question, the error vector's
entries always sum up to zero. Explain why this is always the case
for the error vector for a least-squares regression line?

Explain the difference between the mean square error and the
standard error.

what's the difference between USGS regression method
and results from stream stats?
why they are different?
which method is most usefull?

In simple linear regression, the method of least squares
determines the line that minimizes the sum of squared deviations
between the observed y values and: a. the average of the y values
b. the average of the x values c. the fitted line d. the line of
residual errors

What is the Difference between linear regression and multiple
regression analysis?

1.
What are the limitations of chi-square? Explain
2. Explain contingency table analysis and how is it
applied?
3. How many types of test are considered non-parameteric data
and briefly explain each?
4. What are the elements and assumptions of the Wilcoxon
Signed Rank Test?
5. What are the steps needed to calculate the Wilcoxon Rank
Sum Test?
6. Explain the summary of the chi-square steps.
7. Describe the Kruskal-Wallis Test

explain the difference between engineering method of cost
estimation and the account analysis method.what is the risk and
benefits of using each approach

The standard error of estimate (SE) is the
___________________.
standard difference between the regression line and the predicted
mean
standard distance between the regression line and the mean
standard distance between the y values and predicted values
standard distance between the sample and population mean

Explain the difference between simple and multiple linear
regression.
A. Simple linear regression is faster
B. The difference is in how many independent variables used in
the regression model
C. There is no difference
D. There is a difference in the linearity

Explain how different factors influence the hemoglobin binding
curve, and how they affect the transition between the T and the R
state. Also explain the physiological consequences of shifting the
hemoglobin binding curve to higher affinity or lower affinity.

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