Fill in all the blanks below to complete the partial Excel output for a linear regression between the independent variable x and the dependent variable y. Summary Output Regression Statistics Multiple R Standard Error ANOVA R Square Observations Regression Residual Total X Intercept df 13 8.2 0.27 (Round to 4 decimal places) 0.1358 SS (Round to 4 decimal places) Coefficients Standard Error 2.2177 3.4278 0.5601 2.6500 MS F (Round to 2 decimal places) (Round to 2 decimal places) 11.75 t Stat (Round to 3 decimal places) P-value 0.0030 0.6434 Significance F 0.6434
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- A group of Maternal and Child Health public health practitioners are interested in the relationship between bacterial vaginosis (BV) and a number of negative health outcomes. Suppose the research team gathers information on a group of participants, and constructs a multiple linear regression model looking at the relationship between BV and depression, controlling for maternal age. The following is a computerized output displaying the results of their analysis.Parameter Intercept Maternal Age DepressionEstimate StandardError tValue Pr>|t|0.2186206635 -.0046496845 0.19124124150.06635040 0.00221338 0.031518843.29 0.0010 -2.10 0.0360 6.07 <.0001 A) What are the dependent and independent variables in this investigation?B) Based on the information above, was the research team justified in controlling for maternal age in this population? Why or why not?C) Write out the model in symbols. Round to 3 decimal places.D) Is there a significant association between BV and depression?Use the following table to calculate the simple linear regression to determine if the amount of time spent on homework can be predicted by amount of sleep. Graph the relationship and determine, numerically, if there are any outliers. Interpret all results in a paragraph citing the appropriate statistics. Show all work [edit] ID School Enrolled Months Enrolled Birthday Month Distance to Work (whole miles) Height (whole inches) Foot Size (whole inches) Hand Size (whole inches) Sleep (minutes) Homework (minutes) 1 Arts and Sciences 12 January 0 60 8 5 360 30 2 Applied Science and Technology 6 February 0 62 7 6 400 45 3 Business and Management 8 April 5 66 10 7 420 60 4 Nursing 10 June 10 68 12 8 440 15 5 Public Service 48 July 15 68 14 8 540 75 6 Arts and Sciences 48 June 30 70 12 9 480 120 7 Applied Science and Technology 36…Write out the full linear model including all dummy variables below. Don’t worry about estimating regression coefficients just yet. Feel free to abbreviate variable names so long as they are clearly distinguishable.
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