Exam 12: Simple Regression

Using the ordinary least squares method ensures that the residuals will be normally distributed.

In linear regression between two variables,a significant relationship exists when the p-value of the t test statistic for the slope is greater than α.

In a sample of n = 23,the critical value of the correlation coefficient for a two-tailed test at α = .05 is:

In a two-tailed test for correlation at α = .05,a sample correlation coefficient r = 0.42 with n = 25 is significantly different than zero.

The fitted intercept in a regression has little meaning if no data values near X = 0 have been observed.

Bob thinks there is something wrong with Excel's fitted regression.What do you say?

The least squares regression line is obtained when the sum of the squared residuals is minimized.

In a simple regression,there are n - 2 degrees of freedom associated with the error sum of squares (SSE).

The least squares regression line gives unbiased estimates of β₀ and β₁.

A scatter plot is used to visualize the association (or lack of association)between two quantitative variables.

Which is not an assumption of least squares regression?

In simple linear regression,the coefficient of determination (R²)is estimated from sums of squares in the ANOVA table.

The sample coefficient of correlation does not have which property?

A common source of spurious correlation between X and Y is when a third unspecified variable Z affects both X and Y.

Using a two-tailed test at α = .05 for n = 30,we would reject the hypothesis of zero correlation if the absolute value of r exceeds:

Find the slope of the simple regression = b₀ + b₁x.

If r = .55 and n = 16,then the correlation is significant at α = .05 in a two-tailed test.

The width of a prediction interval for an individual value of Y is less than standard error s_e.

If SSR is 2592 and SSE is 608,then:

Find the sample correlation coefficient for the following data.