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Regression analysis can be created easily with Basic Reporter as well, which will make the job of energy managers much easier. (demand power specification, energy usage forecasting). More at www.konsys-international.com
The most common statistical approach for any human health studies is correlation and regression analysis. Suppose, consider a vaccine effectiveness study, and the researcher wants to identify the effectiveness of vaccine among the gender or age category. The correlation technique will be useful to identify the relationship between these two variables. Statswork offers statistical services as per the requirements of the customers. When you Order statistical Services at Statswork, we promise you the following always on Time, outstanding customer support, and High-quality Subject Matter Experts.
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Correlation and Regression
What is a correlation:
Correlation is a test in statistics to get to know if there is any relationship exist between two datasets or not. Correlation is of two types positive and negative. A positive correlation means if one variable is increasing then 2nd variable is also increasing while a negative correlation shows if one variable increases then 2nd variable decreases.
Correlation between two data sets will be measured by the coefficient of correlation. The value of the coefficient of correlation lies between -1 and 1.If the value is zero it means there is no correlation between data sets. If the value is greater than 0 it means positive correlation and +1 will show a perfect positive correlation. While if the value is less than zero it shows -negative correlation between data sets and -1 means a perfectly negative correlation.
An example of correlation would be high weather temperature vs use of woolen cloth(-ve correlation) and use of ice cream(+ve correlation).
To calculate correlation in excel we will use the CORREL formula while for visualizing it we will use a Scatter chart. As in the below image, we can see we have 3 data sets X1, X2, and X3. We will try to find a correlation between X1 vs X2 and X2 vs X3.
In the above example, we can see a correlation between X1 vs X2 is positive while the correlation between X2 vs X3 is negative. Both graphs also show the same.
datawitzz.com/correlation-and-regression-when-to-use-thes...
Approach to Predictive Analytics based on Regression analysis, Choice modeling, Rule induction, Network/Link Analysis.
eluminoustechnologies.com/blog/2018/01/approach-to-predic...
#predictiveanalytics #regressionanalysis #choicemodeling #networkanalysis #linkanalysis #businessintelligence
Correlation and Regression
What is a correlation:
Correlation is a test in statistics to get to know if there is any relationship exist between two datasets or not. Correlation is of two types positive and negative. A positive correlation means if one variable is increasing then 2nd variable is also increasing while a negative correlation shows if one variable increases then 2nd variable decreases.
Correlation between two data sets will be measured by the coefficient of correlation. The value of the coefficient of correlation lies between -1 and 1.If the value is zero it means there is no correlation between data sets. If the value is greater than 0 it means positive correlation and +1 will show a perfect positive correlation. While if the value is less than zero it shows -negative correlation between data sets and -1 means a perfectly negative correlation.
An example of correlation would be high weather temperature vs use of woolen cloth(-ve correlation) and use of ice cream(+ve correlation).
To calculate correlation in excel we will use the CORREL formula while for visualizing it we will use a Scatter chart. As in the below image, we can see we have 3 data sets X1, X2, and X3. We will try to find a correlation between X1 vs X2 and X2 vs X3.
In the above example, we can see a correlation between X1 vs X2 is positive while the correlation between X2 vs X3 is negative. Both graphs also show the same.
datawitzz.com/correlation-and-regression-when-to-use-thes...