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Statistical Analysis of Garbage Population Mean Weights in Waste Management

Conduct analysis on the weights of metal, paper, plastic, and glass waste to determine if their population means are equivalent. Utilize ANOVA testing with Fisher’s LSD to compare differences in means.

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Statistical Analysis of Garbage Population Mean Weights in Waste Management

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  1. Lesson 3:

  2. Determine mean for each group • Compact cars • Midsize cars • Full-size cars

  3. Determine Test Statistic, F • F = MSTR / MSE; k-1 and n-k d.f. • Calculate p-value • If p < alpha, reject null hypothesis

  4. Summarize data in an ANOVA table

  5. Example 2: • The City Resource Recovery Co. (CRRC) collects the waste discarded by households in a region. The waste must be separated into metals, paper, plastic and glass. In planning for the equipment needs to collect and process the garbage, CRRC uses the sample information below. The weights are in pounds. At a significance level of 5%, test the claim that the four specified garbage population have the same mean.

  6. Factor = weight • Treatment levels are 4 populations • Mu (sub 1) = mean weight of all metal waste • Null hypothesis • Alternative hypothesis

  7. ANOVA TABLE

  8. Conclusion

  9. Fisher’s LSD (Least Significant Difference) • ONLY USED if you reject null hypothesis • If we reject the null and conclude that not all population means are the same, we still don’t know exactly where those differences lie. We could do individual 2-sample t-tests on each pair of population means OR a better way (and easier) is to calculate the difference in means and compare it to Fisher’s LSD statistic.

  10. Test Stat: • Reject • LSD

  11. Example 2 cont.

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