A university's health department is conducting a study to understand the factors that influence students' overall health scores. The health score is a composite index based on various health parameters, and it ranges from 0 to 100; a higher value implies a healthier lifestyle. The university has collected data on several potential predictor variables that could influence students' health scores. Here's a list of the variables available:

• HealthScore: Composite index of health, measured on a scale from 0 to 100.
• ExerciseHours: Average number of hours spent on exercise per week.
• CalorieIntake: Daily calorie intake in kilocalories (kcal).
• SleepHours: Average number of hours slept per night.
• ScreenTime: Average number of hours spent on screen (TV, computer, smartphone) per day.
• JunkFoodConsumption: Weekly consumption of junk food measured in servings.

Your task is to determine which predictors are most useful when predicting HealthScore for this population of students.

Using R, we created the following correlogram:

Question 2.1 Skill Builder: Scenario IQ2.1Skill Builder: Scenario I0 PointsGrading comment:

Which variable is the most helpful for predicting HealthScore?

Choice 1 of 6:HealthScoreChoice 2 of 6:ScreenTimeChoice 3 of 6:ExerciseHoursChoice 4 of 6:JunkFoodConsumptionChoice 5 of 6:CalorieIntakeChoice 6 of 6:SleepHoursSave AnswerQuestion 2.1: Skill Builder: Scenario ILast saved onJun 17 at 4:13 PMQuestion 2.2 Skill Builder: Scenario II

Q2.2Skill Builder: Scenario II0 PointsGrading comment:

Which variable is the least helpful for predicting HealthScore?

Choice 1 of 6:ScreenTimeChoice 2 of 6:ExerciseHoursChoice 3 of 6:CalorieIntakeChoice 4 of 6:HealthScoreChoice 5 of 6:SleepHoursChoice 6 of 6:JunkFoodConsumptionSave AnswerQuestion 2.2: Skill Builder: Scenario IILast saved onJun 17 at 4:14 PMQuestion

2.3 Skill Builder: Scenario IIIQ2.3Skill Builder: Scenario III0 PointsGrading comment:

If you were to remove one predictor to address multicollinearity issues, which of the following pairs of variables should you consider to eliminate one of them?

Choice 1 of 4:ExerciseHoursandSleepHoursChoice 2 of 4:ScreenTimeandHealthScoreChoice 3 of 4:SleepHoursandScreenTimeChoice 4 of 4:CalorieIntakeandJunkFoodConsumptionSave AnswerQuestion 2.3: Skill Builder: Scenario IIILast saved onJun 17 at 4:14 PMQuestion

2.4 Skill Builder: Scenario IVQ2.4Skill Builder: Scenario IV0 Points Grading comment:

Suppose you are considering adding ExerciseHours and SleepHours to your multiple regression model. Which of the following applies to your regression model?

Choice 1 of 3:An interaction term between these predictors should be included.Choice 2 of 3:Including both predictors is likely safe since they are not collinear.Choice 3 of 3:One of the predictors should be removed to avoid redundancy.Save AnswerQuestion 2.4: Skill Builder: Scenario IVLast saved onJun 17 at 4:14 PMQuestion 2.5 Skill Builder: Scenario V

Q2.5Skill Builder: Scenario V 0 PointsGrading comment:

Given that SleepHours and ScreenTime have a correlation close to 0.30.3, how should this affect your predictor selection strategy?

Choice 1 of 3:You should include both predictors without any concerns.Choice 2 of 3:You should consider removing one of the predictors due to moderate multicollinearity.Choice 3 of 3:You should come up with an interaction term betweenSleepHoursandScreenTime.

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