BUAL 2650 EXAM 3 - AUBURN UNI QUESTIONS.
When setting up null hypothesis - Answer -slope is usually set equal to zero
Use the standard error of the regression slope to estimate - Answer -the standard
deviation of the regression slope
Three things that affect variability of the slope: - Answer -1. Spread around the line (se)
- want to be linear and close
2. Spread of x values (sx) - don't want the data clustered
3. Sample size (n) - want a large sample size
Degrees of freedom for confidence interval - Answer -n-2
Regression equation - Answer -intercept coefficient + independent variable
coefficient(x)
SE(b1) aka standard error of regression slope - Answer -is standard error of
independent variable
What does the intercept in the regression equation tell you - Answer -what y hat would
equal if x=0
The slope tells you - Answer -with an increase in x you get ____ amount times x
increase/decrease
B1 is an estimate of change in y for a one unit change in x
Assumptions and conditions - Answer -1. Linearity assumption
2. Independence assumption
3. Equal variance assumption
4. Normal population assumption
Check in that order
Linearity assumption - Answer -This condition is satisfied if the scatterplot of x and y
looks straight when viewing a scatterplot. A scatterplot of the residuals against x should
have no pattern
Independence Assumption - Answer -look for randomization, check plot for lack of
patter or clumping
Equal variance assumption - Answer -the variability of y should be about the same for
all values of x
, Normal population assumption - Answer -Assume the errors around the idealized
regression line at each value of x follow a Normal model.
No pattern
If p value is small and we reject - Answer -We have evidence that the slope of the
regression line differs from 0 and can conclude that there is a linear relationship
HA for multiple regression - Answer -AT LEAST ONE does not equal 0
Check p value to determine - Answer -if F is significant or not
If we reject Ho - Answer -relationship is significant
P value - Answer -is significance f column
R squared - Answer -tells us what proportion of variance is accounted for in the y-
variable by knowing the x-variable
Varies from 0-1
The closer to 0 R squared is - Answer -the smaller the relationship between x and y
If R Squared = 1 - Answer -then the x-variable perfectly explains all the variation in the
y-variable.
Data from scientific experiments often have R2 - Answer -80%-90% range
Data from observational studies may have an acceptable R2 - Answer -in the 30%-50%
range
In general, R2 - Answer -always increases as more independent variables are added to
the model.
Larger SSE means - Answer -the residuals are more variable and our predictions will
be less precise.
Larger SSR means - Answer -our model accounts for a large portion of the variability in
y
The total variation of the response variable y. We have no control over SST, but we'd
like SSE to be - Answer -as small as possible by finding good predictor variables.
Review anova table for multiple regressions - Answer -17.4 in powerpoints (practice
example)
When setting up null hypothesis - Answer -slope is usually set equal to zero
Use the standard error of the regression slope to estimate - Answer -the standard
deviation of the regression slope
Three things that affect variability of the slope: - Answer -1. Spread around the line (se)
- want to be linear and close
2. Spread of x values (sx) - don't want the data clustered
3. Sample size (n) - want a large sample size
Degrees of freedom for confidence interval - Answer -n-2
Regression equation - Answer -intercept coefficient + independent variable
coefficient(x)
SE(b1) aka standard error of regression slope - Answer -is standard error of
independent variable
What does the intercept in the regression equation tell you - Answer -what y hat would
equal if x=0
The slope tells you - Answer -with an increase in x you get ____ amount times x
increase/decrease
B1 is an estimate of change in y for a one unit change in x
Assumptions and conditions - Answer -1. Linearity assumption
2. Independence assumption
3. Equal variance assumption
4. Normal population assumption
Check in that order
Linearity assumption - Answer -This condition is satisfied if the scatterplot of x and y
looks straight when viewing a scatterplot. A scatterplot of the residuals against x should
have no pattern
Independence Assumption - Answer -look for randomization, check plot for lack of
patter or clumping
Equal variance assumption - Answer -the variability of y should be about the same for
all values of x
, Normal population assumption - Answer -Assume the errors around the idealized
regression line at each value of x follow a Normal model.
No pattern
If p value is small and we reject - Answer -We have evidence that the slope of the
regression line differs from 0 and can conclude that there is a linear relationship
HA for multiple regression - Answer -AT LEAST ONE does not equal 0
Check p value to determine - Answer -if F is significant or not
If we reject Ho - Answer -relationship is significant
P value - Answer -is significance f column
R squared - Answer -tells us what proportion of variance is accounted for in the y-
variable by knowing the x-variable
Varies from 0-1
The closer to 0 R squared is - Answer -the smaller the relationship between x and y
If R Squared = 1 - Answer -then the x-variable perfectly explains all the variation in the
y-variable.
Data from scientific experiments often have R2 - Answer -80%-90% range
Data from observational studies may have an acceptable R2 - Answer -in the 30%-50%
range
In general, R2 - Answer -always increases as more independent variables are added to
the model.
Larger SSE means - Answer -the residuals are more variable and our predictions will
be less precise.
Larger SSR means - Answer -our model accounts for a large portion of the variability in
y
The total variation of the response variable y. We have no control over SST, but we'd
like SSE to be - Answer -as small as possible by finding good predictor variables.
Review anova table for multiple regressions - Answer -17.4 in powerpoints (practice
example)
