Simple_Linear_Regression

Simple linear regression is

• unstandardized

• standardized

• only an inferential statistic

• only used when the predictor is a continuous variable

When researchers decide to use regression instead of correlation, they must

• 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

What is the predicted final examination score if the slope is equal to zero?

• Cannot answer this question with the information provided

• 0

• 8.36

• 52.79

In Simple Linear Regression, the researcher is trying to describe as much of _____________ as possible

• Sum of Squares Residual

• Sum of Squares for X

• Sum of Squares for Y

• Sum of Squares Model

Describe the slope for this scenario

• 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

When attendance equals zero, the predicted midterm grade equals

• Do not have enough information to answer this question

• 52.24

• .426

• 4.78

Using the output, you will

• 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 line of best fit is the model with

• the steepest slope

• the smallest residuals

• the smallest distance between the basic model and the regression model

• the greatest sum of squared residual

The line of best fit is

• 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

If a researcher's alpha = .01 and the regression results tell us the p = .032, the researcher should

• Reject the Null Hypothesis

• Accept the Null Hypothesis

• Fail to Reject the Null Hypothesis

• Fail to Prove the Alternative Hypothesis