Exam 14: Experimental Designonline Only

You are filling in the ANOVA table values for an experiment using a two-factor factorial design.In the experiment, there are two Factor A treatments, five Factor B treatments, and two replications.The p-value for Factor B turns out to be .026.If the significance level for the test is set at 5%, we can conclude that the Factor B be effect is not statistically significant.

In an experiment using a randomized complete block design, if the p-value for F_stat is less than the significance level of the test, we can conclude that one of more of the treatment means is different from the others.

You are filling in the ANOVA table values for an experiment using a randomized complete block design.In the experiment, there are 2 treatment groups, 20 blocks.The treatments F value (Fstat) turns out to be 3.662.In finding the critical F value to use in an "equal treatment means" hypothesis test here, you should use df1 = 1 and df2 = 19.

An experimental design that allows us to examine potentially important interactions among the independent variables is a(n)

You are filling in the ANOVA table values for an experiment using a randomized complete block design.In the experiment, there are 4 treatment groups and 6 blocks.The number of experimental units is

An experimental design that represents an extension of the matched samples idea is a(n)

Below are the results from an experiment using a randomized complete block design. Part of the ANOVA table for the results is shown below: Report the appropriate Fstat value for the test of treatment means and your conclusion.The significance level for the test is set at 5%.

You are filling in the ANOVA table values for an experiment using a randomized complete block design.In the experiment, there are 3 treatment groups and 9 blocks.The treatments F value (Fstat) turns out to be 5.080.In determining the p-value for this result, you should use df1 = 2 and df2 = 16.

In a factorial experiment, all possible treatment combinations of the various levels of the factors under study are examined.

Below is some of the ANOVA information for an experiment using a randomized complete block design.In the experiment, there are four treatment groups and five blocks.Report the indicated F value in the partially completed ANOVA table.

Below are the results from an experiment using a randomized complete block design. Part of the ANOVA table for the results is shown below: Report the treatments mean square here.

Below is some of the ANOVA information for a two-factor factorial experiment in which the significance level is set at 5%.Indicate which, if any, of the following conclusions are supported by the information in the table.

The independent variables in an experimental study are called

You are filling in the ANOVA table values for an experiment using a randomized complete block design.In the experiment, there are 5 treatment groups, 16 blocks.The treatments F value (Fstat) turns out to be 6.253.In determining the p-value for this result, you should use df1 = 4 and df2 = 15.

In an observational study, information from a population of interest is gathered without any attempt on the part of those conducting the study to influence the population or to intervene in any way.

You are filling in the ANOVA table values for an experiment using a randomized complete block design.In the experiment, there are 4 treatment groups and 10 blocks.The error sum of squares value is 5400.The mean square error value must be

Below is some of the ANOVA information for an experiment using a randomized complete block design.In the experiment, there are four treatment groups and four blocks.The significance level for the test is set at 1%.Report the indicated F value and your conclusion.

A factorial design allows us to examine potentially important interactions among the independent variables.

You are filling in the ANOVA table values for an experiment using a randomized complete block design.In the experiment, there are 3 treatment groups and 12 blocks.The error sum of squares value is 4400.The mean square error value must be

In a two-factor factorial experiment, there are four treatments for Factor A and five treatments for Factor B.Two replications are being used for each factor combination.Total sample size here