Linear regression model
can be used to estimate the mean value of y given xi, or it can be used to predict the value of y given n
Confidence interval
the interval estimate of the mean value of y for a given value of x
Predictor interval
Used when we want to predict an individual value of y
In...
linear regression model can be used to estimate th
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Linear regression model
can be used to estimate the mean value of y given xi, or it can
be used to predict the value of y given n
Confidence interval
the interval estimate of the mean value of y for a given value of
x
Predictor interval
Used when we want to predict an individual value of y
Intercept (b0)
The estimated value of Y when X is 0
x variable
independent variable
regression coefficient intercept
estimated results for the y intercept
regression coefficient independent variable
estimated results about the independent variable
regression standard error
standard deviation of the coefficients
, Regression summary output (multiple R)
sample correlation coeffocoent
Regression summary output (R-square)
coefficient of determination
Regression summary output( adjusted r-square)
not applicable for a simple linear regression
Regression summary output (standard error)
estimate of sigma
Regression summary output (observations)
n
error term
random variable with a mean = 0
variance of error term is same for all values of x
Values are independent
Normal distributed random variable for all values of x
Testing for Significance
To test for a significant regression relationship, we
must conduct a hypothesis test to determine whether
the value of b1 is zero.
t-test
a statistical test used to evaluate the size and significance of the
difference between two means
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