Construct a 90% confidence interval for the true population slope coefficient B1. Test using a MODEL test whether or not there is a linear relationship between the dependent and independent variables. Test whether the results based upon the sample data support your anticipated population expectation. (5 pts) Identify an anticipated direction for the relationship between the two variables in this scenario. Predict the value of the dependent variable when the value of the independent variable equals its mean. Interpret the estimated slope coefficient: (4 pts) d. Use the appropriate variable names (those in the excel spreadsheet) to label things. Write out the estimated regression equation. Use the Regression option in Data Analysis in Excel to produce the appropriate simple regression output for the data set supplied in the Excel spreadsheet (12 pts) b. 4-Decision Rule.for what p-value Ho is rejected) 5-What test is the best test to use?Why? 6-Check the assumptions of the tests 7-Preform the test 8-Analyze the results 9-Write a conclusion and a recommendation based on the results aph overall model diagram,and write a general conclusion for your results. To get the maximum possible grade on your project.you should have all possible tests of differences and relations that you have learned in class once at least and you need to have the following in your report: 1-Graphing and interpreting bar chart,pic chart and histogram for each DV and important IVsIVs with significant relation or differences particularly the demographic factors such as age and gender etc 2-State the alternative and null Hypothesis correctly 3-Set the Significance level (or confidence level it's 95% confidence level for this class. For example if you use a categorical variable(factor in regression analysis,your test is wrong and not acceptable.Or if you run ANOVA on a categorical variable as your DV.that would be wrong and you may lose some credit. Maximum number of outlier test is one time,maximum number of outliers to delete is 3 rows or cases onlyīefore performing the tests you need to check the assumptions. You can analyze the effect of each factor by adding or deleting factors in the model. For the hypothesis test of relation you can use scatter plot matrix,correlation matrix,correlation analysis,simple and multiple correlation,Chi Square,Cramer's Vsimple and multiple regression.
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