s edwards discussion

Assignment instructions

Hey Girl, yes! Here is the whole assignment with the chart attached ! Linking Concepts: Writing Projects Discuss each of the following topics in class or review the topics on your own. Then write a brief but complete essay in which you summarize the main points. Please include formulas and graphs as appropriate. In this chapter, you studied the chi-square distribution and three principal applications of the distribution. Outline the basic ideas behind the chi-square test of independence. What is a contingency table? What are the null and alternate hypotheses? How is the test statistic constructed? What basic assumptions underlie this application of the chi-square distribution? Outline the basic ideas behind the chi-square test of goodness of fit. What are the null and alternate hypotheses? How is the test statistic constructed? There are a number of direct similarities between tests of independence and tests of goodness of fit. Discuss and summarize these similarities. Outline the basic ideas behind the chi-square method of testing and estimating a standard deviation. What basic assumptions underlie this process? Outline the basic ideas behind the chi-square test of homogeneity. What are the null and alternate hypotheses? How is the test statistic constructed? What basic assumptions underlie the application of the chi-square distribution? The � distribution is used to construct a one-way ANOVA test for comparing several sample means. Outline the basic purpose of ANOVA. How does ANOVA avoid high risk due to multiple Type I errors? Outline the basic assumption for ANOVA. What are the null and alternate hypotheses in an ANOVA test? If the test conclusion is to reject the null hypothesis, do we know which of the population means are different from each other? What is the � distribution? How are the degrees of freedom for numerator and denominator determined? What do we mean by a summary table of ANOVA results? What are the main components of such a table? How is the final decision made? Analysis of Variance (One-Way ANOVA) The following data comprise a historic winter mildness/severity index for three European locations near 50 ° north latitude. For each decade, the number of unmistakably mild months minus the number of unmistakably severe months for December, January, and February is given. 2Table is based on data from Exchanging Climate by H. H. Lamb. Reprinted by permission of Routledge, UK. We wish to test the null hypothesis that the mean winter indices for Britain, Germany, and Russia are all equal against the alternate hypothesis that they are not all equal. Use a 5 % level of significance. What is the sum of squares between groups? Within groups? What is the sample � ratio? What is the � -value? Shall we reject or fail to reject the statement that the mean winter indices for these locations in Britain, Germany, and Russia are the same? What is the smallest level of significance at which we could conclude that the mean winter indices for these locations are not all equal?

3.7 chart

Hey! I hope this helps! I couldn't copy/paste in a way that works so the data falls into three categories: Age: 16-17 National Percentage: 3.7 Number in Fremont County: 8 Age: 18-24 National Percentage: 18.9 Number in Fremont County: 35 Age: 25-29 National Percentage: 12.9 Number in Fremont County: 23 Age: 30-34 National Percentage: 10.3 Number in Fremont County: 19 Age: 35-39 National Percentage: 8.5 Number in Fremont County: 12 Age: 40-44 National Percentage: 7.9 Number in Fremont County: 14 Age: 45-49 National Percentage: 8.0 Number in Fremont County: 16 Age: 50-54 National Percentage: 7.9 Number in Fremont County: 13 Age: 55-59 National Percentage: 6.8 Number in Fremont County: 10 Age: 60-64 National Percentage: 5.7 Number in Fremont County: 9 Age: 65 and over National Percentage: 9.4 Number in Fremont County: 15 Total percentage is 1005 and total number in Freemont is 174