Module 2 lab3 Flashcards
Correlation Analysis
both independent variables are continuous
Continuous variable
infinite number of possible values
(human height and weight)
null hypothesis
no relationship exists between variables
Alternative hypothesis
values of the dependent variable are caused by the independent variable
(real explainable relationship between the two)
p-value
probability that the null hypothesis is correct (there is no relationship)
As the P-value gets higher
There is a greater and greater chance of the null hypothesis being correct
R^2 value
tells you how much of the variance(fluctuation) in the dependent variable(y) is due to the effect of the independent variable
The larger the R^2
the more the variation in the dependent variable is explained by the independent variable
R^2 value near zero
there is a random, nonlinear relationship between the two variables
trendline
represents any trend in the data
the R^2 value measures
how well the trendline represents the data
High R^2(close to 1)
- data points are closely aligned with trendline
- independent variable explains a significant proportion of the variation in the dependent variable
Moderate R^2
- data points are more dispersed around the trendline
- independent variable explains some of the variation in the dependent variable
Low R^2
- data points are widely scattered around the trendline
- independent variable explains a little, but not much, of the variation in the dependent variable
- can still be significant