An experiment is conducted to study the effects of two sales approaches-high-pressure (H) and low-pressure (L)-and to study the effects of two sales pitches (1 and 2) on the weekly sales of a product. The data in Table 10.14 are obtained by using a completely randomized design, and Figure 10.13 gives the Excel output of a two-way ANOVA of the sales experiment data... (Please see attached)
a Perform graphical analysis to check for interaction between sales pressure and sales pitch.
b Test for interaction by setting alpha = .05.
c Test for differences in the effects of the levels of sales pressure by setting alpha = .05. That is, test the significance of sales pressure effects with alpha = .05.
d Calculate and interpret a 95 percent individual confidence interval for muH. _ muL.
e Test for differences in the effects of the levels of sales pitch by setting alpha = .05. That is, test the significance of sales pitch effects with alpha = .05.
f Calculate and interpret a 95 percent individual confidence interval for mu.1 _ mu.2.
g Calculate a 95 percent (individual) confidence interval
... This is an example of a balanced two-way analysis of variance (ANOVA). ... This is an example of a balanced two-way analysis of variance (ANOVA). ...
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... between one-way and two-way ANOVA. Hello from Cleveland, Ohio. Glad to help you out with the differences between a one way and a two way analysis of variance. ...
When running an analysis of variance (ANOVA): two-factor with replication (two-way test), you get a p-value for the interaction effect, indicating whether it ...
Hypothesis Testing: Analysis of Variance Example Problems. ... Use technology tool and the block design to perform a two-way ANOVA test. Use alpha = .10. ...
