This question relates to the patterns that occur when trying to draw inferences about one or two population means or population proportions. It is assumed in this question that any confidence intervals or tests will be completed using a t-distribution or the standard normal distribution.

In a confidence interval estimate for a population mean or proportion, or comparing two means or two proportions, the center of the confidence interval will be:

	a critical value from a standard distribution
	the value of the relevant parameter
	the sample statistic that is used to estimate the relevant parameter
	the standard deviation of the sampling distribution of the relevant parameter

In simple linear regression, select the correct interpretation of the regression sum of squares (SSR): Please pick correct response.

	SSR is the amount of variation in the response variable that is accounted for by the explanatory variable.
	SSR is the amount of variation in the explanatory variable that is accounted for by the response variable.
	SSR is the amount of variation in the explanatory variable that is not accounted for by the response variable.
	SSR is the amount of variation in the response variable that is not accounted for by the explanatory variable.

A simple linear regression equation is to be constructed to determine if there is a linear relationship between a response variable (Y) and an explanatory variable (X). A random sample of size n has been collected and the values x_i and y_i for i = 1, 2, ..., n have been recorded. The residuals (e_i) in this analysis are defined as the difference between the observed values of Y and the values of Y predicted by the regression equation.

The scatterplot or residual plots can be used to see if the regression equation is an appropriate model for the data. An assumption required for the simple linear regression equation to be valid is: Please pick correct response.

	the residuals are normally distributed
	X and Y are independent
	the variance of X is equal to the variance of Y
	the residuals are constant

A regression model has been developed to analyze the relationship between a response variable Y and an explanatory variable X. A prediction interval is to be constructed for an individual value of Y for a given value of X.

Select whether each change would increase, decrease, or not affect the width of the prediction interval.Please pick correct response.

a)	Decreasing the level of confidence
b)	Using a larger sample size
c)	Choosing a value of X further away fromx
d)	Having less variation in the values of the response variable about the prediction line