Explain if this association is linear or nonlinear.

Part I: SPSS OutputThe data set includes data from 10 students in a health and fitness class. After their lesson on meditation, students were asked to track their exercise and meditation habits over 6 weeks. Their age, weight difference (current weight – ideal weight), average hours of exercise per week, average meditation minutes per week, and systolic and diastolic blood pressure were recorded. The dataset variables include: Age: age recorded in yearsWeightDif: current weight minus ideal weight in poundsHoursEx: average number of hours exercised per week.MedMins: average number of minutes meditated per week.SBP: systolic blood pressure at the end of the 6 weeksDBP: diastolic blood pressure at the end of the 6 weeks Using SPSS, complete the following: Calculate descriptive statistics of mean and standard deviation for each variable.Analyze each variable for outliers.Create a scatterplot of the data for WeightDif (x-axis) and DBP (y-axis).Using an alpha = 0.5, run a simple correlation between WeightDif and DBP.Using an alpha = 0.5, run a simple linear regression equation with WeightDif and DBP. Part II: Written Results In a 2-3-page paper using APA formatting, describe your results by identifying the following: You are interested in whether there is a relationship between WeightDif and DBP.Describe the direction and apparent strength of the association between WeightDif and DBP. Explain if this association is linear or nonlinear.What is the value of r? In your own words, what does this mean?Create appropriate tables using APA 7 to display this data.You are now interested in whether WeightDif can successfully predict DBP.Describe the independent and dependent variables.State the null hypotheses (there will be two: one for the simple correlation and one for the simple linear regression equation).Describe your results of the correlation.Describe the assumptions that need to be tested before running a regression equation.State your regression equation. Based on your equation, state the predicted DBP for someone with a WeightDif of 10.Create appropriate tables to display this data.Explain how you could use multiple regression analysis to investigate the additional variables’ relationships further. (Note: you do not have to run a multiple regression analysis, explain how it could be used.)

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