transform the data to z scores

ensure the alternative hypothesis depicts a direction for the slope

now evaluate assumptions (correlation does not have assumptions)

interpret two parameter estimates

Cannot answer this question with the information provided

0

8.36

52.79

Sum of Squares Residual

Sum of Squares for X

Sum of Squares for Y

Sum of Squares Model

For every .426 increase in attendance, the mean midterm grade increases by one unit

The slope is equal to zero because the 95% CI does not include 1

For every unit increase in attendance, the mean midterm grade increases by .426

For every unit increase in attendance, the mean midterm grade increases by .757

Do not have enough information to answer this question

52.24

.426

4.78

Reject the null hypothesis

Fail to reject the null hypothesis

I need the ANOVA Table to answer this question

I need the Model Summary Table to answer this question

the steepest slope

the smallest residuals

the smallest distance between the basic model and the regression model

the greatest sum of squared residual

the simple linear regression model in the population

the simple linear regression model in the sample

the correlation in the population that we estimate via the intercept and slope

the population intercept and slope that we adjust down because we are using a sample

Reject the Null Hypothesis

Accept the Null Hypothesis

Fail to Reject the Null Hypothesis

Fail to Prove the Alternative Hypothesis

slope

residual

intercept

outcome

If the confidence interval does not contain 0, Amanda

I don't have enough information to answer this question

There is only one instructor at this day/time for this course, therefore no model is needed. It is Amanda and this is an exact solution (no probability statement necessary)

If p < .05, Amanda

t statistic not equal to zero

the sample slope is not equal to zero

the slope in the population is equal to zero

the slope in the sample equals the slope in the population

The Mean Square Model

Smallest Mean Square Error

t-test of the slope

One sample t-test

 $\frac{b_1}{se_{b_1}}$  

 $t\ critical\ \times\frac{alpha}{2}$  

standardized beta  $\times.05$  

 $\frac{b_1}{b_0}$