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If the following data were linearized using logarithms what would be the equation of the regression line Round the slope and y-intercept of the regression line to three decimal places. x y 1 13 2 19 3?
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How do you solve logarithmic simultaneous equations?
That would depend a lot on the specific equations. Often the following tricks can help: (a) Take antilogarithms to get rid of the logarithms. (b) Use the properties of logarithms, especially: log(ab) = log a + log b; log(a/b) = log a - log b; log ab = b log a. (These properties work for logarithms in any base.)
What defines the slope value in a regression solution?
Don't write "the following" if you don't provide a list. It just doesn't make any sense.
Why log you is unmdefined?
I am not quite sure what you mean with "log you"; the log is calculated for numbers. The following logarithms are undefined: For real numbers: the logarithm of zero and of negative numbers is undefined. For complex numbers: the logarithm of zero is undefined.
How can you find an equation for a trend line?
There are numerous ways to do this. I think the easiest is to put the data in excel and have excel show the trend line, equation, andcorrelation coefficient. Excel gives you several options to choose for the trend line analysis. The other way is if it is a linear relationship, you can do the linear regression analysis following the steps listed in the related link. If you are not familiar with regression analysis, it may not be easy for you to follow.
When you use your regression line to predict values that are not in the sample and discovered large residual values in each prediction what can you say about your regression line?
There are several possible explanations: Leaving aside the two most obvious reasons: calculation error and attempted extrapolation, there are the following possibilities: The true relationship is non-linear. A relevant variable has been missed omitted. The observations are very variable: leading to a very large residual error. There is not enough variation in the independent (or predictive) variable so that Sxx is very small.
The value 11.7 represents the of the graph of the following linear regression equation?
slope
What are the synonyms for fixation?
The following are synonyms for fixation:Synonyms: obsession, infantile fixation, arrested development, regression, fixing.
How do you solve logarithmic simultaneous equations?
That would depend a lot on the specific equations. Often the following tricks can help: (a) Take antilogarithms to get rid of the logarithms. (b) Use the properties of logarithms, especially: log(ab) = log a + log b; log(a/b) = log a - log b; log ab = b log a. (These properties work for logarithms in any base.)
What defines the slope value in a regression solution?
Don't write "the following" if you don't provide a list. It just doesn't make any sense.
What has the author A K Md Ehsanes Saleh written?
A. K. Md. Ehsanes Saleh has written: 'A collection of three papers on estimation of quantiles based on selected order statistics' -- subject(s): Order statistics, Distribution (Probability theory) 'Nonparametric estimation following a preliminary test on regression' -- subject(s): Regression analysis
Why log you is unmdefined?
I am not quite sure what you mean with "log you"; the log is calculated for numbers. The following logarithms are undefined: For real numbers: the logarithm of zero and of negative numbers is undefined. For complex numbers: the logarithm of zero is undefined.
Accuracy of memories recovered by hypnosis?
Memories recovered by hypnosis can be accurate or false. To get them accurate, a hypnotized person should realize a sleepwalking state of hypnosis with following age regression. When age regression is achieved and stable, special tests are being applied to make sure that recovering memories are accurate. This procedure can be performed only by a highly qualified hypnotist.
Do you need more than 10 observations in linear regression?
This is a difficult question to answer. The pure answer is no. In reality, it depends on the level of randomness in the data. If you plot the data, it will give you an idea of the randomness. Even with 10 data points, 1 or 2 outliers can significantly change the regression equation. I am not aware of a rule of thumb on the minimum number of data points. Obviously, the more the better. Also, calculate the correlation coefficient. Be sure to follow the rules of regression. See the following website: http:/www.duke.edu/~rnau/testing.htm
How do you calculate fixed cost and variable cost given total cost and quantity?
We can calculate using following methods 1 - High-Low method 2 - Regression analysis method 3 - Graphical method
What are the Causes of regression in autism?
Regression normally results from stress. For example many parents will push their autistic children to be more like neurotypical children, forcing autistic people to pretend to be neurotypical takes a lot of effort and can result in burn-out followed by regression. Often parents who will not accept their autistic children continue to force them to try to be something other than autistic, long-term this does more harm than good. Autistic people will often regress following stressful situations in their lives, again being forced to act like neurotypical people can result in burnout and regression (for example when in a toxic work environment), or in what would be stressful situations for anyone such as a result of marital problems, homelessness, illness, etc. Aging also seems to result in regression, but little research has been put into adults with autism and even less on older adults with autism.
Requirements of regression analysis in statistics?
You may get more ideas from wikipedia under regression analysis. You can do a regression analysis with as little as 2 x,y points- but is it meaningful? Requirements for valid or meaningful relationships can be subjective. However, in my opinion, if meaningful relationships are to be created using regression analysis, the following are important: a) The independent variable should have values that are independent (no relation exists between them). b) There should be a good rational or experimental basis for identifying the independent variables and the resultant dependent variable. c) Sufficient data should be collected in a controlled environment to identify the relationship. d) The validity of the relationship should easy to identify both visually and by numbers (see "goodness of fit" tests).
How can you find an equation for a trend line?
There are numerous ways to do this. I think the easiest is to put the data in excel and have excel show the trend line, equation, andcorrelation coefficient. Excel gives you several options to choose for the trend line analysis. The other way is if it is a linear relationship, you can do the linear regression analysis following the steps listed in the related link. If you are not familiar with regression analysis, it may not be easy for you to follow.
