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I utilize the feature for certificates of insurance. It’s very nice to have the mobile app to be able to use that when I’m on the go .
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I utilize the feature for certificates of insurance. It’s very nice to have the mobile app to be able to use that when I’m on the go .
What do you dislike?
The way it saves documents or re-saves them or use as a template is very confusing . And not all of the options on the desktop version are also available on the mobile version .
What problems are you solving with the product? What benefits have you realized?
Certificates of insurance
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Why do we log time series data?
For forecasting and economic analysis many variables are used in logarithms (logs). In time series analysis, this transformation is often considered stabilizing the variance of a series. Using logs can be damaging for the forecast precision if a stable variance is not achieved.
Why do we take log of data?
There are two main reasons to use logarithmic scales in charts and graphs. The first is to respond to skewness towards large values. i.e., cases in which one or a few points are much larger than the bulk of the data. The second is to show percent change or multiplicative factors.
Why do we apply log transformation?
Using the log transformation to make data conform to normality. If the original data follows a log-normal distribution or approximately so, then the log-transformed data follows a normal or near normal distribution. In this case, the log-transformation does remove or reduce skewness.
How do you interpret log transformed data?
Only the dependent/response variable is log-transformed. Exponential the coefficient, subtract one from this number, and multiply by 100. Only independent/predictor variable(s) is log-transformed. Both dependent/response variable and independent/predictor variable(s) are log-transformed.
What does a log transformation do?
Log Transformations. The log transformation can be used to make highly skewed distributions less skewed. This can be valuable both for making patterns in the data more interpretable and for helping to meet the assumptions of inferential statistics.
How do you back transform log data?
For the log transformation, you would back-transform by raising 10 to the power of your number. For example, the log transformed data above has a mean of 1.044 and a 95% confidence interval of ±0.344 log-transformed fish. The back-transformed mean would be 101.044=11.1 fish.
When should you log transform data?
The log transformation can be used to make highly skewed distributions less skewed. This can be valuable both for making patterns in the data more interpretable and for helping to meet the assumptions of inferential statistics. Figure 1 shows an example of how a log transformation can make patterns more visible.
How do I back transform log in Excel?
0:33 2:38 Suggested clip How to use the LOG10 (Log Transformation) function in Excel YouTubeStart of suggested client of suggested clip How to use the LOG10 (Log Transformation) function in Excel
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