A researcher wants to determine if there is a significant difference in the average math scores of two different teaching methods (Method A and Method B). He collects a sample of 50 students from each teaching method and calculates their scores. The sample mean score for Method A is 85 and the sample mean score for Method B is 80. The sample standard deviation for Method A is 4 and the sample standard deviation for Method B is 3. Conduct an independent samples t-test to determine if there is a significant difference in the average math scores of the two teaching methods at a significance level of 0.01.

In the US, 45.1% of all people have type O blood, 39.6% have type A blood, 10.9% have type B blood and 4.4% have type AB blood. A researcher wants to see if the distribution of blood type is different for millionaires. The table below shows the results of a random sample of 614 millionaires. What can be concluded at the significant level of a = 0.05. For this study, we should use Chi-Square test for Goodness of Fit Your friend Caroline helped you with the null and alternative hypotheses... Ho : The distributions of blood types are the same between the general population and the millionaires. Ha: The distributions of blood types are NOT the same between the general population and the millionaires. You drew 614 samples, and the observed frequencies are recorded below. Please complete the table (round answers to at least 4 decimal places). Blood Type 0 A B AB Observed Count 274 230 57 53 Expected Count Click Download CSV to download csv file of data or copy/paste the data into Excel.…

Earlier this semester, we learned to use 2-Sample-TTest to compare the population means of two independent populations. One-way ANOVA is more powerful because it could compare the population means of three or more independent populations. However, use of one-way ANOVA also requires the assumption that the populations have the same variance. In this exercise, we will compare and contrast One-way ANOVA and 2-Sample-TTest. With the 2-Sample- TTEST, we will first choose 'No' for the pooled variances option, then re-run the test while choosing 'Yes' for the pooled variances option. Use the following data to complete these tasks. Depending on if you choose to do this by hand or using code, use the data format that suits you best - LONG form on top or WIDE form on bottom. Treatment One One One One One One One One Two Two Two Two Two Two Two Two Treatment Treatment One Two 5.6 4.7 3.6 3.9 5.2 4.3 4.1 4.8 Response 5.6 4.7 3.6 3.9 5.2 4.3 4.1 4.8 3.4 2.3 4.4 3.5 3.7 5.8 2.8 4.7 p-value= 3.4 2.3…