How Do You?
How do you know how much of the variation in y is explained by x
R-Squared
What does it mean if R-squared is .9568
That 95.68% of the variance in y is explained by the linear relationship with x
what is the r-squared for Dataset A
0.9886
What is the regression equation for Dataset D
y= 2758.21x + 31373.08
Using Dataset A what would be the expected Exam Score if someone studied for 13 hours
82.79
How do you know what the value of the y value is when x is 0
the Intercept
What does it mean if the intercept is 10 and x = exam scores and y = hours studied
That with 0 hours of study, the expected score would be 10
what is the intercept for Dataset B and what does it mean in context
5.33, when there are zero TV, Radio, and Online ad's we can expect 5.33 dollars in sales
what is the b_1 value in Dataset E and what does it mean
-0.8980, that for every additional unit of X1 we can expect Y to decrease by 0.8980 when holding X2 and X3 constant
Using Dataset C what would be the expected price for a house with 1,000 sqft, 3 bedrooms, & was 25 years old
$94,481.15
How do you know what the change in y will be for each one-unit change in x
the slope
What does it mean if y=5x+10 when x=revenue in dollars and y=amount spent in ad's in dollars
that for every additional dollar spent on ad's 5 additional dollars in revenue can be expected and when 0 dollars is spent on ad's then 10 dollars can be expected in revenue
What is the intercept for Dataset A and what does it mean
50.88, with 0 hours of study, we can expect an exam score of 50.88
What is the R-squared for Dataset D and what does it mean
0.9379, that 93.79% of the variance in salary is explained the linear relationship to experience
Using Dataset D what is the expected Salary for someone with 14 years of experience
$69,988.09
How do you calculate the residual?
Actual - Predicted
What does in mean if the R-squared is .0548
that 5.48% of the variance in y can be explained by the linear relationship to x
what is the regression equation for Dataset C
y= 113.98x1 + 334.38x2 -1147.31x3 + 8180.68
what is the value of b_2 for Dataset C and what does it mean
334.38, For every additional Bedroom a home has, we can expect an increase of 334.38 if price when holding SqFt and Age constant
Using Dataset B what are the expected Sales with 150 TV ad's, 40 Radio ad's, and 2 Online ad's
$17,345.02
How do you know if the linear relationship between x and y is significant
the p-value
What does it mean when y=-10x+20
for every additional unit of x you can expect -10 of y and when x = 0 you can expect y to equal 20
What is the R-squared for Dataset C and what does it mean
0.9770, 97.7% of the variance in price is explained by the linear relationship to SqFt, number of Bedrooms, and Age
what is the b_1 value for Dataset D and what does it mean
2758.21, For every additional year of experiance, an increase of 2758.21 in Salary can be expected
Prediction of the value of the dependent variable outside the experimental region
Extrapolation