Superabsorbent polymer (SAP) is a hydrogel capable of absorbing liquids through hydrogen bonding. A homecare products company is looking to increase the absorbency of its leading diaper brand by incorporating a newly improved low-density cross-linked SAP into the product. To test whether the improved SAP statistically significantly improves the absorbency of the diaper, the company randomly selects 100 of its original diapers without the improved SAP and 50 newly designed diapers with the improved SAP. Each sample is then subjected to an absorbency test during which an aqueous solution is administered at a rate of 10 milliliters per second until the diaper leaks. The maximum absorbency is then recorded. Consider the data below:

Diaper without improved SAP	Newly designed diaper with improved SAP
Units: n = 100	Units: n = 50
Mean absorbency (ml): M=998	Mean absorbency (ml): M=1001
Sum of Squares (SS) = 12,650	Sum of Squares (SS) = 8,300

FOR ALL CALCULATIONS, ROUND TO THE NEAREST TWO DECIMAL PLACES.

1. The company is only interested in upgrading to the improved SAP design if there is evidence that it statistically significantly increases the absorbency of their diaper. Conduct an appropriate hypothesis test to verify which decision they should make. The company wants to be 99% certainthat the SAP actually improves their product (in other words, they are willing to accept a 1% risk of committing a Type I error).

Complete all four steps of the hypothesis test. Show your work for all necessary calculations. Be as thorough and detailed as possible. Draw the distribution indicating critical values and appropriate statistics.

Based on your test results, do you recommend that the company invest in the improved SAP product, or should it retain its original diaper? Explain.

1.Construct a 99% confidence interval for the probable values from the previous test.

2.What percentage of the variance is explained by introduction of the new SAP diaper? Would you categorize this proportion of variance explained as a small, medium, or large effect?

3. Consider the hypothesis test that you just conducted. Did it utilize the z-distribution or the t-distribution? Explain your answer.

4. Consider the hypothesis test that you just conducted. Was it an example of an Independent Samples t-test or a Repeated Measures t-test? Given the context of this research question, would it have been possible to conduct the test the other way around?

In other words, if it was an independent samples test, would it be possible to redesign the experiment such that it is a repeated measures test? If it was a repeated measures test, would it be possible to redesign the experiment such that it is an independent samples test?