Looking at how quickly polyester fibers decay in landfills, A researcher buried

Question

Looking at how quickly polyester fibers decay in landfills, A researcher buried polyester strips in the soil for different lengths of time then dug up a portion of the strips and measured the force required (Pounds) to break them, a good indicator of decay lower strength means the fabric has decayed 1) 2) 3) 4) State the null and alternate hypotheses? Identify independent and dependent variables? Do we need a post hoc analysis? Why or why not? What is the effect size? Between-Subjects Factors Weeks 2 5 Descriptive Statistics Dependent Vaniable Pounds Weeks Mean Std. Deviation 2 12380 123.60 134.40 4.604 6.542 9.529 8 455 Total 127 27 15 Tests of Between-Subjects Efects Dependent Variable Pounds Type IIl Sum of Partial Eta df Mean Square Sig 361 Corrected Model 381 733 242952 067 381.733 619 200 243953.000 1000 933 190 867 3.699 1 242952 0674 4708.373058 301 190.887 51.600 3 690 12 15 Total Corrected Total a R Squared : 381 (Adjusted R Squared 278)

Explanation / Answer

1)) Null hypothesis: H0: there is no difference between the average force required to break the strips for different duration in weeks.

Alternative hypothesis: H1: there is the difference between the average force required to break the strips for the different duration in weeks.

2)) Here, Force required (pounds) are the dependent variable whereas different weeks is the independent variable.

3)) the ANOVA (Analysis of variance) test tells about overall difference between groups whereas post hoc tests finds which specific groups differed. Firstly, you have to show that there is an overall statistically significant difference between group means. The, you can run the post hoc test. These tests also known as the posterior tests.

Here from the table we can observe that ANOVA is not statistically significant (0.058 for season). Now we can apply the post hoc test. Thus, we fail to reject the null hypothesis.

4)) Now, we calculate the effect size:

Effect size = (Treatment SS for season)/(Total SS)

                  = (381.733)/(1000.933)

                  = 0.38137.

This can be interpreted as the 38% of the variation in average force to break the strips is due to different durations.

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