STAT TECH IN BUSINESS & ECON LL\AC
STAT TECH IN BUSINESS & ECON LL\AC
18th Edition
ISBN: 9781264720545
Author: Lind
Publisher: MCG
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Chapter 16, Problem 1.8PT
To determine

State the major difference between Kruskal–Wallis test and Wilcoxon rank-sum test.

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Is the proportion of wildfires caused by humans in the south lower than the proportion of wildfires caused by humans in the west? 360 of the 501 randomly selected wildfires looked at in the south were caused by humans while 435 of the 588 randomly selected wildfires looked at the west were caused by humans. What can be concluded at the  = 0.10 level of significance?   For this study, we should use Select an answer t-test for the difference between two dependent population means z-test for the difference between two population proportions t-test for a population mean t-test for the difference between two independent population means z-test for a population proportion  The null and alternative hypotheses would be:          Select an answer μ1 p1  Select an answer < ≠ > =  Select an answer μ2 p2  (please enter a decimal)       Select an answer μ1 p1  Select an answer > ≠ < =  Select an answer p2 μ2  (Please enter a decimal) The test statistic ? z t  =  (please show your…
How should you enter your data into SPSS to conduct a related samples t-test? There is no standard way to enter your data into SPSS when conducting a related samples t-test. O Enter the level of the independent variable for each participant in one column, with their score on the dependent variable in the other column. Put all of your data for all of your participants into one column. Put all of the data for one group of participants in one column and put all of the data for the other group of participants in another column. What is a related samples t-test called in SPSS? Independent Samples T Test One-Way ANOVA Paired-Samples T Test One-Sample T Test
The correlation coefficient r is a sample statistic. What does it tell us about the value of the population correlation coefficient ρ (Greek letter rho)? You do not know how to build the formal structure of hypothesis tests of ρ yet. However, there is a quick way to determine if the sample evidence based on ρ is strong enough to conclude that there is some population correlation between the variables. In other words, we can use the value of r to determine if ρ ≠ 0. We do this by comparing the value |r| to an entry in the correlation table. The value of α in the table gives us the probability of concluding that ρ ≠ 0 when, in fact, ρ = 0 and there is no population correlation. We have two choices for α: α = 0.05 or α = 0.01.   (a) Look at the data below regarding the variables x = age of a Shetland pony and y = weight of that pony. Is the value of |r| large enough to conclude that weight and age of Shetland ponies are correlated? Use α = 0.05. (Use 3 decimal places.) x 3 6 12 22 26…
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