Working with Large Data SetsIn Exercises, use the technology of your choice to do the following tasks.a. Decide whether conducting a Kruskal–Wallis test on the data is reasonable. If so, also do parts (b)–(d).b. Use a Kruskal–Wallis test to decide, at the 5% significance level, whether the data provide sufficient evidence to conclude that a difference exists among the means of the populations from which the samples were taken.c. Interpret your results from part (b).d. If a one-way ANOVA test was performed on the data in Section 16.3, compare your results there to those obtained here. Note: All data sets are on the WeissStats site.Fish of Lake Laengelmaevesi. The data from Exercise on weight (in grams) and length (in centimeters) from the nose to the beginning of the tail for four species of fish caught in Lake Laengelmaevesi, Finland. Consider both the weight and length data for possible analysis.In Exercises, use the technology of your choice to do the following tasks.a. Obtain individual normal probability plots and the standard deviations of the samples.b. Perform a residual analysis.c. Use your results from parts (a) and (b) to decide whether conducting a one-way ANOVA test on the data is reasonable. If so, also do parts (d) and (e).d. Use a one-way ANOVA test to decide, at the 5% significance level, whether the data provide sufficient evidence to conclude that a difference exists among the means of the populations from which the samples were taken.e. Interpret your results from part (d)Fish of Lake Laengelmaevesi. An article by J. Puranen of the Department of Statistics, University of Helsinki, discussed a classic study on several variables of seven different species of fish caught in Lake Laengelmaevesi, Finland. On theWeissStats site, we present the data on weight (in grams) and length (in centimeters) from the nose to the beginning of the tail for four of the seven species. Perform the required parts for both the weight and length data.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
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Chapter4: Equations Of Linear Functions
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Working with Large Data Sets
In Exercises, use the technology of your choice to do the following tasks.
a. Decide whether conducting a Kruskal–Wallis test on the data is reasonable. If so, also do parts (b)–(d).
b. Use a Kruskal–Wallis test to decide, at the 5% significance level, whether the data provide sufficient evidence to conclude that a difference exists among the means of the populations from which the samples were taken.
c. Interpret your results from part (b).
d. If a one-way ANOVA test was performed on the data in Section 16.3, compare your results there to those obtained here. Note: All data sets are on the WeissStats site.
Fish of Lake Laengelmaevesi. The data from Exercise on weight (in grams) and length (in centimeters) from the nose to the beginning of the tail for four species of fish caught in Lake Laengelmaevesi, Finland. Consider both the weight and length data for possible analysis.
In Exercises, use the technology of your choice to do the following tasks.
a. Obtain individual normal probability plots and the standard deviations of the samples.
b. Perform a residual analysis.
c. Use your results from parts (a) and (b) to decide whether conducting a one-way ANOVA test on the data is reasonable. If so, also do parts (d) and (e).
d. Use a one-way ANOVA test to decide, at the 5% significance level, whether the data provide sufficient evidence to conclude that a difference exists among the means of the populations from which the samples were taken.
e. Interpret your results from part (d)
Fish of Lake Laengelmaevesi. An article by J. Puranen of the Department of Statistics, University of Helsinki, discussed a classic study on several variables of seven different species of fish caught in Lake Laengelmaevesi, Finland. On theWeissStats site, we present the data on weight (in grams) and length (in centimeters) from the nose to the beginning of the tail for four of the seven species. Perform the required parts for both the weight and length data.

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