The linregress() method in scipy module is used to fit a simple linear regression model using “Reaction” (reaction time) as the response variable and “Drinks” as the predictor variable. The output is shown below. What is the correct regression equation based on this output? Is this model statistically significant at 5% level of significance (alpha = 0.05)? Select one. Python script outputs for the linregress method. Slope equals 6.0000, intercept = 3.9999, rvalue = 0.9728, pvalue = 0.0011, stderror = 0.7141. Note: Python output shows many decimal places. All values Question 2 options: Reaction = 6.0000 + 3.9999 Drinks, model is not statistically significant Reaction = 6.0000 + 3.9999 Drinks, model is statistically significant Reaction = 3.9999 + 6.0000 Drinks, model is not statistically significant Reaction = 3.9999 + 6.0000 Drinks, model is statistically signi
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
The linregress() method in scipy module is used to fit a simple linear regression model using “Reaction” (reaction time) as the response variable and “Drinks” as the predictor variable. The output is shown below. What is the correct regression equation based on this output? Is this model statistically significant at 5% level of significance (alpha = 0.05)? Select one.
Python script outputs for the linregress method. Slope equals 6.0000, intercept = 3.9999, rvalue = 0.9728, pvalue = 0.0011, stderror = 0.7141. Note: Python output shows many decimal places. All values
Question 2 options:
Reaction = 6.0000 + 3.9999 Drinks, model is not statistically significant
Reaction = 6.0000 + 3.9999 Drinks, model is statistically significant
Reaction = 3.9999 + 6.0000 Drinks, model is not statistically significant
Reaction = 3.9999 + 6.0000 Drinks, model is statistically significant
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